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Han, Bijun. "Analyzing car ownership and route choices using discrete choice models." Doctoral thesis, KTH, Infrastructure and Planning, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3215.
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This thesis consists of two parts. The first part analyzesthe accessibility, generation and license holding effects incar ownership models. The second part develops a route choicemodeling framework with an attempt to address the differencesin drivers' route choice behavior. These two parts of work areboth based on the discrete choice theory - the car ownershipmodels are built up on the standard logit model, whereas theroute choice models are formulated in a mixed logit form.
The study result of the first part shows that measuring theaccessibility by the monetary inclusive value reasonably wellcaptures the mechanism of the accessibility impact. Otheraccessibility proxies such as the parking costs, parking typeand house type are correlated with the accessibility but not toa great extent. Both young and old households are less likelyto have a car. The reduction of the propensity to own a car issignificant for households with average birth year before 1920,whereas this reduction is moderate for households with birthyear between 1920 and 1945. It is also demonstrated thatdriving license holding choice is conditional on the carownership level choice, and that these two choices need to bemodeled in a dynamic framework.
The second part of the work investigates the performance ofthe mixed logit model using both simulated data and empiricalroute switching data. The empirical study mainly focused on theimpacts of information and incident related factors on drivers'route switching behavior.
The result shows that using mixed logit gives a significantimprovement in model performance as well as a more sensitiveexplanation of drivers' decision-making behavior. For apopulation with greatly varying tastes, simply using thestandard logit model to analyze its behavior can yield veryunrealistic results. However, care must be taken when settingthe number of random draws for simulating the choiceprobability of the mixed logit model in order to get reliableestimates.
The empirical results demonstrate that incident relatedfactors such as delay and information reliability havesignificant impacts on drivers' route switching, where themagnitude of the response to the change in the delay is shownto vary significantly between individuals. Other factors, suchas confidence in the estimated delay, gender, frequency of cardriving and attitude towards congestion, also make majorcontributions. In addition, it is found that individual's routeswitching behavior may differ depending on the purpose of thetrip and when the choice is made, i.e. pre-trip oren-route.
Keywords: car ownership, accessibility, logit model,route choice, heterogeneity, mixed logit model
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Fadaei, Oshyani Masoud. "Estimating route choice models using low frequency GPS data." Thesis, KTH, Transportvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-41546.
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GPS data are increasingly available to be used in transportation planning. Route choice models are estimated to address the behavior of individuals choosing a route in a given network. When data is collected with low frequency, it is unknown which path was traversed between the GPS data points. Furthermore, GPS data has measurements error. In this thesis we design an algorithm to consistently estimate a given route choice model in the presence of sparse GPS data and measurement errors. We present an extension on a new method presented by Kalström et al. (2011) to estimate a route choice model. This method focuses on a given simple way to estimate the true parameter of a model. For this purpose the indirect inference method is employed as a structured procedure. In our context, a simple multinomial logit model is used as the auxiliary model with the simulated data sets and in a structured way returns the estimated parameter. This version of discrete choice model is simple and fast which qualifies it as an appropriate auxiliary model. We estimate a model with random link costs which allows for a natural correlation structure across paths and is also useful for simulating paths in order to make choice sets. In this study Monte Carlo evidence is provided to show the feasibility and accuracy of the proposed algorithm using a real world network from Borlänge, Sweden. The main conclusion is that indirect inference is an exciting option in the tool box for route choice estimation which can be used for estimating route choice models using low frequency GPS sampling data.
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Samadzad, Mahdi. "Space disaggregation in models of route and mode choice : method and application to the Paris area." Thesis, Paris Est, 2013. http://www.theses.fr/2013PEST1058/document.
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La repr?sentation spatiale de l?aire de mod?lisation dans les mod?les de la demande de transports a peu chang? au cours des derni?res d?cennies. A cet ?gard, l??tat-de l?art repose encore largement sur le syst?me de centro?de-connecteur qui est utilis?e dans les mod?les classiques. Elle est une approche agr?g?e qui ignore la variabilit? physique li?e ? la dispersion des lieux d?sagr?g?s de r?sidence et d?activit? dans l?espace local. En cons?quence, le pouvoir explicatif des mod?les quant aux comportements de choix d?itin?raire et de mode demeure limit? ? l??chelle locale : Par exemple, la localisation d?sagr?g?e influence sur le choix entre une autoroute dont l??changeur est ?loign?, et un autre itin?raire non-autoroutier. Egalement, le rabattement terminal influence sur le partage modal auto vs. transports en commun. Nous pr?sentons une approche d?sagr?g?e pour la repr?sentation spatiale. Dans un d?coupage zonal, l?espace ? l?int?rieur d?une zone est repr?sent? de mani?re d?sagr?g?e stochastique. Pour chaque zone, les points d?ancrage sont d?finis relative aux n?uds du r?seau qui peuvent ?tre utilis?s pour acc?der au r?seau. Un itin?raire entre une paire de zones est ensuite consid?r? comme une chaine, compos?e de deux trajets terminaux, correspondants aux sections intrazonales de l?itin?raire, et d?un trajet principal correspondant ? la section entre deux points d?ancrage. En cons?quence, le mod?le de choix d?itin?raire est transform? ? un mod?le de choix conjoint d?une paire de point d?ancrage. Le vecteur des temps al?atoires terminaux est Normal Multidimensionnel donnant lieu ? un mod?le Probit de choix conjoint de points d?ancrage.Pour ?tendre au cadre multimodal, un mode collectif composite est d?fini comme une chaine compos?e des trois trajets modaux d?acc?s, principal, et de sortie, et les stations sont consid?r?es comme les points d?ancrage, connectant les trajets de rabattement au trajet principal. Un mod?le Logit Multinomial de choix de mode est estim? ? partir de l?Enqu?te Globale de Transport de 2001 pour le mode auto et le faisceau des modes collectifs composites, et est combin? avec les deux mod?les Probit correspondants au choix des stationsSpatial representation of modeling area in travel demand models has changed little over the course of last several decades. In this regard, the state-of-the-art still widely relies on the same centroid-connector system that has been used in classic models. In this approach continuum bidimensional space is lumped on centroids. It is an aggregate approach which ignores the physical variability linked to the scatteredness of disaggregate residence- and activity-places over the local space. Consequently the modeling performance in explaining route and mode choice behavior degrades at local scales: In route choice, disaggregate location influences the propensity between a distant interchange to a highway, or a nearby road. In mode choice, feeder service to public transportations influences the auto vs. transit modal share. We propose a disaggregate approach for spatial representation. Based on a zoning system, a stochastic disaggregate representation is used to characterize the space within a traffic analysis zone. For each zone, anchor-points are defined as the network nodes that are used for accessing to the network from within the local space. An itinerary between a pair of zones is then considered as a chain of legs composed of two terminal legs, corresponding to the intrazonal route sections, and one main leg between two anchor points. The route choice problem is transformed to a joint choice of a pair of anchor points. The vector of random terminal travel times is Multivariate Normal resulting in a Multinomial Probit model of choice of a pair of anchor points. To extend to the multimodal context, a transit composite mode is defined as a chain of access, main, and egress modal legs, and transit platforms are considered as anchor points connecting the feeder legs to the main line-haul leg. A Multinomial Logit mode choice model is estimated based on the 2001 Paris Household Travel Survey for the auto mode and the composite transit modes. It is joined with the two Multinomial Probit models corresponding to the choice of anchor points. The result is a joint model of mode and station choice with a disaggregate representation of the local space
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González, Ramírez Humberto. "Study of the choice behaviour of travellers in a transport network via a “simulation game” Travel time and bounded rationality in travellers’ route choice behaviour : a computer route choice experiment Unravelling travellers’ route choice behaviour at full-scale urban network by focusing on representative OD pairs in computer experiments." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSET008.
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L'objectif de cette thèse est de trouver des modèles de choix d'itinéraire qui évoluent au niveau du réseau, c'est-à-dire des modèles qui rapprochent les choix des voyageurs sur la diversité des situations rencontrées dans un réseau de transport. L'approche de cette thèse pour étudier le comportement des voyageurs dans les réseaux de transport passe par des expériences informatiques à grande échelle, pour lesquelles une plateforme nommée Mobility Decision Game (MDG) a été développée. Le MDG permet d'observer les choix des participants sur un ensemble diversifié de scénarios (paires OD et itinéraires) avec des conditions de circulation et des informations de temps de trajet variables. Dans cette thèse, les expériences se concentrent sur les choix d'itinéraire des trajets en voiture qui sont basés sur la carte de la ville de Lyon, France. Pour atteindre l'objectif de cette thèse, une méthodologie de recherche de couples OD représentatifs du réseau est tout d'abord proposée. Les paires OD représentatives sont utilisées dans les expériences de choix de route pour obtenir des modèles de choix qui se généralisent aux différentes configurations OD dans le réseau. Deuxièmement, les choix des participants aux expériences sont analysés du point de vue du comportement rationnel et borné, afin d'établir le principe qui décrit le mieux leurs choix. Enfin, les modèles de choix sont évalués en fonction de leur précision prédictive. Cette thèse fait partie d'un projet européen ERC intitulé MAGnUM: Approche de modélisation du trafic multi-échelle et multimodale pour la gestion durable de la mobilité urbaineThe objective of this thesis is to find route choice models that scale-up at network level, i.e., models that predict the choices of travellers over the diversity of situations found in a transport network. The approach in this thesis to investigate travellers' behaviour in transportation networks is through computer-based experiments at large scale, for which a platform named the Mobility Decision Game (MDG), has been developed. The MDG permits to observe the choices of the participants on a diverse set of scenarios (OD pairs and routes) with varying traffic conditions and travel time information. In this thesis, the experiments focus on the route choices of uni-modal car trips that are based on the map of the city of Lyon, France. To attain the objective of this thesis, firstly a methodology to find OD pairs that are representative of the network is proposed. The representative OD pairs are used in route choice experiments to obtain choice models that generalise to the various OD configurations in the network. Secondly, the choices of participants in the experiments are analysed from the rational and boundedly rational behaviour perspectives, in order to establish the principle that best describe their choices. Finally, the choice models are assessed in terms of their predictive accuracy. This thesis is part of a European ERC project entitled MAGnUM: Multiscale and Multimodal Traffic Modeling Approach for Sustainable Management of Urban Mobility
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Bai, Tongzhou. "Consistently estimating route choice models using indirect inference based on emprical observation data." Thesis, KTH, Transportvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-43389.
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In the thesis, a proposed route choice model is tested on the empirical observation data. The model gives link specific errors to the links in the network, which allows natural correlation structure among paths. Indirect inference method is used to consistently estimate the route choice model, and a logit model is chosen to be the auxiliary model. The observation data with multiple OD pairs was collected in the Borlänge, a city located in the middle part of Sweden. Two main experiments are carried out, one with only one attribute, length to be specific in the route choice model and the other with two attributes, namely length and speed bump dummy. The final estimates of parameters have positive signs as anticipated and the magnitudes are reasonable. In addition, judging from the estimated binding functions, parameters in the cost function have negative effect on utility in the logti model and the parameter in the logit model are more apparently affected by its indirectly inferred parameter in the route choice model than the others do. Some other trials of the model are also carried out, but the estimates are not satisfying. This may be due to lack of attributes in the route choice model and further suggestion on better defined model is given out. A Monte Carlo experiment is also carried out to test the efficiency of model with unfixed scale parameter to the random term in the route choice model.
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Unnikrishnan, Avinash. "Equilibrium models accounting for uncertainty and information provision in transportation networks." [Austin, Tex. : University of Texas Libraries, 2008. http://www.lib.utexas.edu/etd/d/2008/unnikrishnana67041/unnikrishnana67041.pdf#page=3.
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Vargas, Júlio Celso Borello. "Forma urbana e rotas de pedestres." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/127812.
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O estímulo aos modos ativos de viagem através de modificações na forma urbana - infraestrutura, edificações e atividades - é objeto do planejamento das cidades contemporâneas desde que os problemas do transporte motorizado se revelaram críticos e contrários à ideia de sustentabilidade urbana. Congestionamentos, poluição, custos monetários e sociais elevados estão associados ao modelo de urbanização e mobilidade da maioria das cidades, especialmente nos países em desenvolvimento, onde a explosão da frota motorizada é concomitante à aceleração dos processos de urbanização e espalhamento urbano. Mais recentemente, a revelação de relações de causalidade entre o excesso de utilização dos veículos particulares e problemas de saúde crônica das populações urbanas levou a um crescimento das pesquisas e iniciativas de estímulo às caminhadas como modo de transporte. Também o interesse pela qualidade da experiência da vida na cidade veio somar-se a este corpo de conhecimento, trazendo as ideias de vitalidade urbana e urbanidade para junto dos estudos de caminhabilidade. O interesse extrapolou a análise de demanda agregada que visa o incremento do modo a pé e passou a dar atenção aos caminhos pelos quais as pessoas se movimentam, conectando origens e destinos nos interior das cidades. Este trabalho procura avançar neste aspecto ao propor um método de avaliação dos atributos da forma urbana baseado no monitoramento de caminhantes com dispositivos de posicionamento global (GPS) e modelos de escolha discreta. Um estudo na cidade de Porto Alegre acompanhou indivíduos durante os anos de 2011 a 2014 e, através da representação de diversos atributos urbanos em ambiente SIG, associou as trajetórias realizadas com as características da forma da cidade, concluindo que elas influenciam a utilidade percebida das alternativas de caminho e, portanto, atuam sobre o processo decisório dos pedestres. Para além da simples distância ou declividade, outras características como o tamanho dos trechos, a hierarquia das vias, a presença de prédios marcantes e espaços abertos e a densidade de edificações ao longo dos eixos revelaram-se influentes neste processo. Poucas intersecções e cruzamentos, predomínio de vias amigáveis ao pedestre e edificações arranjadas de forma menos densa são alguns dos atributos que apresentaram maior relevância para a decisão de “por onde ir” no âmbito deste estudo. A amostra relativamente pequena e a concentração das viagens no entorno do Parque Farroupilha e do campus da UFRGS não permitem generalizar os resultados. Porém, o estudo pode ser considerado válido enquanto exploração, pois constrói uma metodologia que pode ser ampliada e aplicada em outros contextos. Além disso, os resultados revelam particularidades da realidade local que parecem indicar a existência de diferenças comportamentais significativas em relação às cidades do primeiro mundo, tornando-o promissor como instrumento de suporte a políticas e projetos de mobilidade urbana sustentável no Brasil.Since motorized transport problems have proved to be critical and contrary to the concept of urban sustainability, the idea of increasing the active travel modes through changes in urban form is a key subject of today´s mobility agenda. Traffic congestion, air pollution and severe monetary and social costs are associated with the current patterns of urbanization and mobility, especially in developing countries, where an explosive motorized fleet growth occurs simultaneously to an acceleration of urbanization and sprawl processes. Most recently evidences of a causal relationship between massive use of private vehicles and chronic health disorders have led to an increase in research about walking as an effective and clean mode of transportation. Also, the interest about the quality of life experience in the city came to add up to this body of knowledge, bringing in ideas of livability to walkability studies. Beyond the aggregate demand studies that aim to increase the walking mode share, there is now a growing interest on more localized aspects of the walking phenomenon - the routes - trying to understand the ways in which people travel on foot when connecting origins and destinations. This work proposes a method based on assessing data from actually taken walking trips using GPS devices and on modeling pedestrian´s choice behavior using discrete choice models. A study in the city of Porto Alegre, south of Brazil, followed 82 individuals for three consecutive days and, through the representation of several layers of urban data in a GIS environment, associated their trajectories with the main urban form attributes to allow the modeling experiment. The results show that the built environment features play an important role as a decision attribute, producing perceived utility/disutility on the decision-makers´ minds. They indicated that, in addition to the basic travel effort attributes such as trip distance or street slope, other factors such as the straightness of the trip, the road hierarchy, the presence of busy intersections, landmark buildings, noticeable public spaces and the density of buildings along the walking stretches indeed influence the route choice. The relatively small sample size and the spatial clustering of trips around the city´s central area doesn´t allow to the generalization of results. However, the study can be taken as a valid exploratory analysis, since it builds up a methodology that can be expanded and applied in other urban contexts. Furthermore, the results reveal some particular local features that indicate the existence of significant behavioral differences from the developed cities where previous similar studies were performed. These qualities make the proposed framework a promising decision support tool for sustainable urban mobility projects in Brazil.
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Watling, David Paul, Thomas Kjær Rasmussen, Carlo Giacomo Prato, and Otto Anker Nielsen. "Stochastic user equilibrium with a bounded choice model." Elsevier, 2018. https://publish.fid-move.qucosa.de/id/qucosa%3A73239.
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Stochastic User Equilibrium (SUE) models allow the representation of the perceptual and preferential differences that exist when drivers compare alternative routes through a transportation network. However, as an effect of the used choice models, conventional applications of SUE are based on the assumption that all available routes have a positive probability of being chosen, however unattractive. In this paper, a novel choice model, the Bounded Choice Model (BCM), is presented along with network conditions for a corresponding Bounded SUE. The model integrates an exogenously-defined bound on the random utility of the set of paths that are used at equilibrium, within a Random Utility Theory (RUT) framework. The model predicts which routes are used and unused (the choice sets are equilibrated), while still ensuring that the distribution of flows on used routes accords to a Discrete Choice Model. Importantly, conditions to guarantee existence and uniqueness of the Bounded SUE are shown. Also, a corresponding solution algorithm is proposed and numerical results are reported by applying this to the Sioux Falls network.
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Broach, Joseph. "Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes." PDXScholar, 2016. https://pdxscholar.library.pdx.edu/open_access_etds/2702.
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For a number of reasons--congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few--the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used most effectively, accurate models sensitive to key policy variables are needed to support long-range planning and project evaluation, and to continue adding to our growing understanding of key factors driving walk and bike behavior. This research attempts to synthesize and advance the state of the art in trip-based, nonmotorized mode choice modeling.
Over the past fifteen years, efforts to model the decision to walk or bike on a given trip have been hampered by the lack of a comprehensive behavioral framework and inconsistency in measurement scales and model specification. This project develops a mode choice behavioral framework that acknowledges the importance of attributes along the specific walk and bike routes that travelers are likely to consider, in addition to more traditional area-based measures of travel environments. The proposed framework is applied to a revealed preference, GPS-based travel dataset collected from 2010-2013 in Portland, Oregon. Measurement of nonmotorized trip distance, built environment, tour-level variables, and attitudinal attributes as well as mode availability are explicitly addressed. Route and mode choice models are specified using discrete choice techniques, and predicted walking and bicycling routes are tested as inputs to various mode choice models.
Results suggest strong potential for predicted route measures to enhance walk and bicycle mode choice modeling. Findings also support the specific notion that bicycle and pedestrian infrastructure contribute not only to route choice but also to the choice of whether to bike or walk. For decisions to bicycle, availability of low-traffic routes may be particularly important to women. Model results further indicate that land use and built environments around trip ends and a person’s home still have important effects on nonmotorized travel when controlling for route quality. Both route and area travel environment impacts are mostly robust to the inclusion of residential self-selection variables, consistent with the idea that built environment differences matter even for households that choose to live in a walkable or bikeable neighborhood. The combination of area and route-based built environment measures alongside trip context, sociodemographic, and attitudinal attributes provides a new perspective on nonmotorized travel behavior relevant to both policy and practice.
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Gao, Yuhan. "Estimation of Tourist Travel Patterns with Recursive Logit Models based on Wi-Fi Data with Kyoto City Case Study." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263639.
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京都大学新制・課程博士
博士(工学)
甲第23178号
工博第4822号
京都大学大学院工学研究科都市社会工学専攻
(主査)教授 山田 忠史, 教授 藤井 聡, 准教授 SCHMOECKER Jan-Dirk
学位規則第4条第1項該当
Doctor of Philosophy (Engineering)
Kyoto University
DFAM
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Bennett, Ashlea R. "Home health care logistics planning." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/33989.
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This thesis develops quantitative methods which incorporate transportation modeling for tactical and operational home health logistics planning problems. We define home health nurse routing and scheduling (HHNRS) problems, which are dynamic periodic routing and scheduling problems with fixed appointment times, where a set of patients must be visited by a home health nurse according to a prescribed weekly frequency for a prescribed number of consecutive weeks during a planning horizon, and each patient visit must be
assigned an appointment time belonging to an allowable menu of equally-spaced times. Patient requests are revealed incrementally, and appointment time selections must be made without knowledge of future requests. First, a static problem variant is studied to understand the impact of fixed appointment times on routing and
scheduling decisions, independent of other complicating factors in the HHNRS problem. The costs of offering fixed appointment times are
quantified, and purely distance-based heuristics are shown to have potential limitations for appointment time problems unless proposed arc cost transformations are used. Building on this result, a new rolling horizon capacity-based heuristic is developed for HHNRS problems. The heuristic considers interactions between travel times, service times, and the fixed appointment time menu when inserting appointments for currently revealed patient requests into partial
nurse schedules. The heuristic is shown to outperform a distance-based heuristic on metrics which emphasize meeting as much patient demand as possible.
The home health nurse districting (HHND) problem is a tactical planning problem which influences HHNRS problem solution quality. A set of geographic zones must be partitioned into districts to be served by home health nurses, such that workload is balanced across districts and nurse travel is minimized. A set partitioning model for HHND is formulated and a column generation heuristic is developed which integrates ideas from optimization and local search. Methods for estimating district travel and workload are developed and implemented within the heuristic, which outperforms local search
on test instances.
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Shatu, Farjana M. "Built environment impact on pedestrian route choice behaviour: Shortest vs. least directional change routes." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/126392/1/Farjana_Shatu_Thesis.pdf.
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This study investigates how students choose their walking routes to a university. Their observed walking routes were compared against the shortest path routes and against the least directional change routes. The urban design features (e.g. streets, benches, fountains, buildings) of these routes were also examined through physical and virtual (e.g. Google Earth image) surveys. The study reveals that students' route choice decision is highly influenced by street configuration – less directional changes are preferred over the shortest path distance – highlighting the need to design urban streets straighter to promote walking.
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Basu, Nandita. "Pedestrian route choice behaviour: Influences of built environment on route preference, safety and security." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/236797/1/Thesis_Nandita%2BBasu_24112022.pdf.
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Built environment factors influence pedestrian route choice behaviour, but their impact is not well known. This thesis investigates the influences of the built environment factors on walking route preference and safety. By using the ‘Physical Activity through Sustainable Transport Approaches’ framework, this research studied the perceptions and preferences of pedestrian route choice in a typical suburban environment in Australia through a stated preference survey. This thesis has established the interrelationship between safety, security, and built environment factors across men and women pedestrians. The findings highlight increasing land-use diversity and providing adequate trees may improve perceived safety and security among pedestrians.
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Werberich, Bruno Rocha. "Pedestrian simulation : a route choice model to assess urban environments." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/163417.
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The design of new facilities - buildings, shopping centers, public transport stations, airports, or intersections of urban roads - should consider delays resulting from intense pedestrians’ flows in order to make its' operation more efficient. The general objective of this doctoral thesis is to propose a simulation model to represent pedestrians’ behavior in urban environments. Simulation models should allow planning these environments in order to provide greater levels of comfort and safety for the pedestrian. Agent-based abstraction has been widely used for pedestrian modeling, mainly due to its capacity to represent complex entities. Agent-based models represent agents’ decision-making ability based on their profile and perception over the environment. One of the most important pedestrians’ activities is the route choice. This document describes the development of a route choice model based on friction forces. The route cost calculation considers a balance between distance and the impedance generated by other pedestrians. Simulations runs shown that pedestrians choosing longer routes can have similar or better travel times. The ability of choosing not only the shorter route brings more realistic behaviors for the pedestrians’ representation, especially with small differences in route lengths and higher congestion. On the proposed model agents were modeled with partial knowledge of the network conditions. The knowledge was limited considering the pedestrian estimated field of view. In the real world it is not possible to know the network state before turning the corner. The model was validated and calibrated with real data. Calibrating a pedestrian route choice model is a complex task mainly for two reasons: (i) Many factors interfere on pedestrians’ route choice; (ii) data collection is difficult. To overcome these difficulties real pedestrians were studied in a controlled environment. An experiment was set up inside the university campus. After the calibration process the model was able to simulate a real scenario. Proposed model was applied to simulate a shopping mall environment. Simulate the pedestrians shopping behavior is particularly complex once route choice in shopping malls may be defined by a number of causal factors. Shoppers may follow a pre-defined schedule; they may be influenced by other people walking, or may want to get a glimpse of a familiar shopping. Analysis from simulations indicates that the agents’ behavior provides a promising approach for real case applications.
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St-Onge, Charles Patrick. "CHOICE, a model for evaluating route, mode, and departure time decisions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0010/MQ31252.pdf.
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Vrtic, Milenko. "Simultanes Routen- und Verkehrsmittelwahlmodell." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2004. http://nbn-resolving.de/urn:nbn:de:swb:14-1085480924187-53794.
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Bei verkehrspolitischen und infrastrukturellen Massnahmen folgen als wesentliche Nachfrageveränderungen vor allem Routen- und Verkehrsmittelwahleffekte. Mit der Anwendung der sequentiellen Routen- und Verkehrsmittelwahlmodelle, ist bei solchen Massnahmen aus verschiedenen Gründen eine konsistente und gesamthafte Gleichgewichtslösung nicht möglich. Das Ziel dieser Untersuchung war, ein konsistentes und verfeinertes Verfahren zu entwickeln, mit dem die Routen- und Verkehrsmittelwahl simultan bzw. in einem Schritt als eine Entscheidung berechnet werden kann. Neben dem Gleichgewicht bei der Verteilung der Verkehrsnachfrage auf die Alternativen, war die konsistente Schätzung der Modellparameter für die Bewertung von Einflussfaktoren bei den Entscheidungen hier eine weitere wichtige Anforderung. Das Modell ist in der Lage, ein realitätsentsprechendes Verhalten der Verkehrsteilnehmer, sowohl bei schwach, als auch bei stark belasteten Strassennetzen, zu beschreiben. Die unterschiedliche Wahrnehmung der Reisekosten der Verkehrsteilnehmer und die Netzüberbelastungen werden durch ein stochastisches Nutzergleichgewicht abgebildet. Das entwickelte Verfahren ermöglicht es: - die Nachfrageaufteilung mit einem konsistenten Gleichgewicht zwischen Verkehrsangebot und Verkehrsnachfrage zu berechnen. Dabei wird ein Gleichgewicht nicht nur innerhalb des Strassen- oder Schienennetzes, sondern zwischen allen verfügbaren Alternativen (unabhängig vom Verkehrsmittel) gesucht. - durch die iterative Kalibration der Modellparameter und die Nachfrageaufteilung ein konsistentes Gleichgewicht zwischen den geschätzten Modellparametern für die Nutzenfunktion und der Nachfrageaufteilung auf die vorhandenen Alternativen (Routen) zu berechnen. - mit einem stochastischen Nutzergleichgwicht die unterschiedliche Wahrnehmung der Nutzen bzw. der generalisierten Kosten der Verkehrsteilnehmer bei der Nachfrageaufteilung zu berücksichtigen. - die Auswirkungen von Angebotsveränderungen auf die Verkehrsmittelwahl und Routenwahl durch simultane Modellierung der Entscheidungen konsistent und ohne Rückkoppelungschritte zu berechnen.
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Kitthamkersorn, Songyot. "Modeling Overlapping and Heterogeneous Perception Variance in Stochastic User Equilibrium Problem with Weibit Route Choice Model." DigitalCommons@USU, 2013. https://digitalcommons.usu.edu/etd/1970.
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In this study, a new SUE model using the Weibull random error terms is proposed as an alternative to overcome the drawbacks of the multinomial logit (MNL) SUE model. A path-size weibit (PSW) model is developed to relax both independently and identically distributed assumptions, while retaining an analytical closed-form solution. Specifically, this route choice model handles route overlapping through the path-size factor and captures the route-specific perception variance through the Weibull distributed random error terms. Both constrained entropy-type and unconstrained equivalent MP formulations for the PSW-SUE are provided. In addition, model extensions to consider the demand elasticity and combined travel choice of the PSW-SUE model are also provided. Unlike the logit-based model, these model extensions incorporate the logarithmic expected perceived travel cost as the network level of service to determine the demand elasticity and travel choice. Qualitative properties of these minimization programs are given to establish equivalency and uniqueness conditions. Both path-based and link-based algorithms are developed for solving the proposed MP formulations. Numerical examples show that the proposed models can produce a compatible traffic flow pattern compared to the multinomial probit (MNP) SUE model, and these models can be implemented in a real-world transportation network.
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Vrtic, Milenko. "Simultanes Routen- und Verkehrsmittelwahlmodell." Doctoral thesis, [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=971486174.
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Fadaei, Oshyani Masoud. "Two papers on consistent estimation of a route choice model and link speed using sparse GPS data." Licentiate thesis, KTH, Transport- och lokaliseringsanalys, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122285.
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Global Positioning System and nomad devices are increasingly used to provide data from individuals in urban traffic networks. In these two papers we focus on consistent estimators of a route choice model and link speed. In many different applications, it is important to predict the continuation of an observed path, and also, given sparse data, predict where the individual (or vehicle) has been. Estimating the perceived cost functions is a difficult statistical estimation problem, for different reasons. First, the choice set is typically very large. Second, it may be important to take into account the correlation between the (generalized) costs of different routes, and thus allow for realistic substitution patterns. Third, due to technical or privacy considerations, the data may be temporally and spatially sparse, with only partially observed paths. Finally, the position of vehicles may have measurement errors. We address all these problems using an indirect inference (II) approach. We demonstrate the feasibility of the proposed estimator in a model with random link costs, allowing for a natural correlation structure across paths, where the full choice set is considered. In the second paper, we develop an estimator for the mean speed and travel time based on indirect inference when the data are spatially and temporally sparse. With sparse data, the full path of vehicles are not observed, which is typically addressed using map matching techniques. First, we show how speed can be estimated using an auxiliary model which includes map matching and a model of route choice. Next, we further develop the estimator and show how both speed and the route choice model can be jointly estimated by using iteration between an II estimator of speed and the II estimator of the route choice model (developed in Paper I). Monte Carlo evidence is provided which demonstrates that the estimator is able to accurately estimate both speed and parameters of the route choice model.QC 20130521
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Cats, Oded. "Dynamic Modelling of Transit Operations and Passenger Decisions." Doctoral thesis, KTH, Trafik och logistik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-49962.
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Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations.QC 20111201
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Danielsson, Anna, and Gabriella Gustafsson. "Link flow destination distribution estimation based on observed travel times for traffic prediction during incidents." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170080.
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In a lot of big cities, the traffic network is overloaded, with congestion and unnecessary emissions as consequence. Therefore, different traffic control methods are useful, especially in case of an incident. One key problem for traffic control is traffic prediction and the aim of this thesis is to develop, calibrate and evaluate a route flow model using only observed travel times and travel demand as input. The route flow model was used to calculate the metric link flow destination distribution, that presents to which destinations the travelers on a link are going in percentage.
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Ma, Wenbo. "Agent-based model of passenger flows in airport terminals." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/63457/1/Wenbo_Ma_Thesis.pdf.
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Passenger flow studies in airport terminals have shown consistent statistical relationships between airport spatial layout and pedestrian movement, facilitating prediction of movement from terminal designs. However, these studies are done at an aggregate level and do not incorporate how individual passengers make decisions at a microscopic level. Therefore, they do not explain the formation of complex movement flows. In addition, existing models mostly focus on standard airport processing procedures such as immigration and security, but seldom consider discretionary activities of passengers, and thus are not able to truly describe the full range of passenger flows within airport terminals. As the route-choice decision-making of passengers involves many uncertain factors within the airport terminals, the mechanisms to fulfill the capacity of managing the route-choice have proven difficult to acquire and quantify.
Could the study of cognitive factors of passengers (i.e. human mental preferences of deciding which on-airport facility to use) be useful to tackle these issues? Assuming the movement in virtual simulated environments can be analogous to movement in real environments, passenger behaviour dynamics can be similar to those generated in virtual experiments. Three levels of dynamics have been devised for motion control: the localised field, tactical level, and strategic level. A localised field refers to basic motion capabilities, such as walking speed, direction and avoidance of obstacles. The other two fields represent cognitive route-choice decision-making. This research views passenger flow problems via a "bottom-up approach", regarding individual passengers as independent intelligent agents who can behave autonomously and are able to interact with others and the ambient environment. In this regard, passenger flow formation becomes an emergent phenomenon of large numbers of passengers interacting with others.
In the thesis, first, the passenger flow in airport terminals was investigated. Discretionary activities of passengers were integrated with standard processing procedures in the research. The localised field for passenger motion dynamics was constructed by a devised force-based model. Next, advanced traits of passengers (such as their desire to shop, their comfort with technology and their willingness to ask for assistance) were formulated to facilitate tactical route-choice decision-making. The traits consist of quantified measures of mental preferences of passengers when they travel through airport terminals. Each category of the traits indicates a decision which passengers may take. They were inferred through a Bayesian network model by analysing the probabilities based on currently available data. Route-choice decision-making was finalised by calculating corresponding utility results based on those probabilities observed.
Three sorts of simulation outcomes were generated: namely, queuing length before checkpoints, average dwell time of passengers at service facilities, and instantaneous space utilisation. Queuing length reflects the number of passengers who are in a queue. Long queues no doubt cause significant delay in processing procedures. The dwell time of each passenger agent at the service facilities were recorded. The overall dwell time of passenger agents at typical facility areas were analysed so as to demonstrate portions of utilisation in the temporal aspect. For the spatial aspect, the number of passenger agents who were dwelling within specific terminal areas can be used to estimate service rates. All outcomes demonstrated specific results by typical simulated passenger flows. They directly reflect terminal capacity. The simulation results strongly suggest that integrating discretionary activities of passengers makes the passenger flows more intuitive, observing probabilities of mental preferences by inferring advanced traits make up an approach capable of carrying out tactical route-choice decision-making.
On the whole, the research studied passenger flows in airport terminals by an agent-based model, which investigated individual characteristics of passengers and their impact on psychological route-choice decisions of passengers. Finally, intuitive passenger flows in airport terminals were able to be realised in simulation.
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Dugge, Birgit. "Ein simultanes Erzeugungs-, Verteilungs-, Aufteilungs- und Routenwahlmodell." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2006. http://nbn-resolving.de/urn:nbn:de:swb:14-1162994071370-87705.
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In dieser Arbeit wird ein simultanes Quell-, Ziel-, Verkehrsmittel- und Routenwahlmodell (Modell EVA-U) entwickelt, welches ein stochastisches Nutzergleichgewicht erreicht. Die Routenwahlmodelle der Verkehrsarten sind nicht mehr Teil der Umlegungsalgorithmen, sondern in das Nachfragemodell integriert. Dadurch ist eine konsistente Bewertung aller Alternativen (der Verkehrsarten) möglich. Das Simultanmodell EVA-U stellt eine Weiterentwicklung des Simultanmodells EVA von LOHSE dar. Das EVA-U-Modell ist den universalen Logit-Modellen zuzuordnen. Die Randsummenbedingungen der Verkehrsverteilung werden beachtet. Die Bewertung der Alternativen erfolgt mittels Generalisierter Kosten. Die Abhängigkeit von Routen wird berücksichtigt, ebenso die Tagesganglinie der Verkehrsnachfrage und die Fahrpläne des ÖV-Systems. Das Modell EVA-U erlaubt auch die Berücksichtigung von Routen intermodaler Verkehrsarten (z.B. P+R). Darüber hinaus ist die Integration eines Modells des ruhenden Verkehrs möglichIn this thesis a simultaneous Trip Generation-, Distribution-, Modal-Split and Route Choice Model (modell EVA-U) is elaborated. The model tends to reach a stochastic user equilibrium. The route choice algorithms are not longer part of an assignment procedure but part of the demand model. A consistent assessment of properties of all transport systems is possible. The simultaneous model EVA-U is an advancement of the EVA-Model by Lohse. The model EVA-U is to be assigned to the generalised logit-models. All matrix constrains are taken into account. The assessment is effected by generalised costs. The dependence of routes is taken into account. Moreover, the integration of day time and the schedules of private transport lines is possible. Furthermore, it is possible to integrate a model of parked cars and circuits of inter-modal traffic forms (park and ride) in the Model EVA-U
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Dugge, Birgit. "Ein simultanes Erzeugungs-, Verteilungs-, Aufteilungs- und Routenwahlmodell." Doctoral thesis, Technische Universität Dresden, 2005. https://tud.qucosa.de/id/qucosa%3A24840.
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In dieser Arbeit wird ein simultanes Quell-, Ziel-, Verkehrsmittel- und Routenwahlmodell (Modell EVA-U) entwickelt, welches ein stochastisches Nutzergleichgewicht erreicht. Die Routenwahlmodelle der Verkehrsarten sind nicht mehr Teil der Umlegungsalgorithmen, sondern in das Nachfragemodell integriert. Dadurch ist eine konsistente Bewertung aller Alternativen (der Verkehrsarten) möglich. Das Simultanmodell EVA-U stellt eine Weiterentwicklung des Simultanmodells EVA von LOHSE dar. Das EVA-U-Modell ist den universalen Logit-Modellen zuzuordnen. Die Randsummenbedingungen der Verkehrsverteilung werden beachtet. Die Bewertung der Alternativen erfolgt mittels Generalisierter Kosten. Die Abhängigkeit von Routen wird berücksichtigt, ebenso die Tagesganglinie der Verkehrsnachfrage und die Fahrpläne des ÖV-Systems. Das Modell EVA-U erlaubt auch die Berücksichtigung von Routen intermodaler Verkehrsarten (z.B. P+R). Darüber hinaus ist die Integration eines Modells des ruhenden Verkehrs möglich.In this thesis a simultaneous Trip Generation-, Distribution-, Modal-Split and Route Choice Model (modell EVA-U) is elaborated. The model tends to reach a stochastic user equilibrium. The route choice algorithms are not longer part of an assignment procedure but part of the demand model. A consistent assessment of properties of all transport systems is possible. The simultaneous model EVA-U is an advancement of the EVA-Model by Lohse. The model EVA-U is to be assigned to the generalised logit-models. All matrix constrains are taken into account. The assessment is effected by generalised costs. The dependence of routes is taken into account. Moreover, the integration of day time and the schedules of private transport lines is possible. Furthermore, it is possible to integrate a model of parked cars and circuits of inter-modal traffic forms (park and ride) in the Model EVA-U.
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Buonocore, Chiara. "Development of a model to choose the path of cyclists using GPS data collected via smartphone." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/17199/.
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Nowadays it is impossible being indifferent to the improvement of the urbanization and the mobility and sustainable road infrastructures.It has to be taken into account the bike as a mode of transport for many reasons such as:reduction of pollution and the emissions,safety on the road,less space and healthy.Mostly in big cities,perhaps it is the fastest mode of transport because it's not subject to traffic and its bottlenecks that block the flow.The Netherlands is the most interested country to travel by bike.It's the place where there are more bikes than cars.In recent years the availability of GPS data has seen a marked improvement in terms of accuracy,continuity and quality of data,thanks to the spread of smartphones and applications for auto-location and navigation.The main advantage is to obtain information on the travel routes actually followed by a large sample of cyclists on the entire network, from their origin to their destination.When GPS tracks can be attributed to detailed transport networks, it is possible to evaluate the factors that users consider in the process of choosing a specific route.It's important to study the choice of the route that cyclists make for many reasons.The objective of this thesis is to examine the aspects that the cyclists taking into account when they choose a route instead of another one.We want to focus on the time travelled,considering the average speed per each link and its correspondent length,and the average waiting times at the intersections:how the time influences cyclists choice. This research will investigate which aspects of the bicycle infrastructures have greater or lesser repercussions on the path made by the cyclists and to model their route choices.It will explore the link between the routes chosen by the cyclists and some attributes of the transport network of the Netherlands.The chosen routes will be compare with the fastest and the shortest calculated thanks to the network analyst in ArcMap for each OD pair.
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Liu, Yulin. "Urban transit quality of service : user perception and behaviour." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61517/1/Yulin_Liu_Thesis.pdf.
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Despite its potential multiple contributions to sustainable policy objectives, urban transit is generally not widely used by the public in terms of its market share compared to that of automobiles, particularly in affluent societies with low-density urban forms like Australia. Transit service providers need to attract more people to transit by improving transit quality of service. The key to cost-effective transit service improvements lies in accurate evaluation of policy proposals by taking into account their impacts on transit users. If transit providers knew what is more or less important to their customers, they could focus their efforts on optimising customer-oriented service. Policy interventions could also be specified to influence transit users’ travel decisions, with targets of customer satisfaction and broader community welfare. This significance motivates the research into the relationship between urban transit quality of service and its user perception as well as behaviour.
This research focused on two dimensions of transit user’s travel behaviour: route choice and access arrival time choice. The study area chosen was a busy urban transit corridor linking Brisbane central business district (CBD) and the St. Lucia campus of The University of Queensland (UQ). This multi-system corridor provided a ‘natural experiment’ for transit users between the CBD and UQ, as they can choose between busway 109 (with grade-separate exclusive right-of-way), ordinary on-street bus 412, and linear fast ferry CityCat on the Brisbane River. The population of interest was set as the attendees to UQ, who travelled from the CBD or from a suburb via the CBD. Two waves of internet-based self-completion questionnaire surveys were conducted to collect data on sampled passengers’ perception of transit service quality and behaviour of using public transit in the study area.
The first wave survey is to collect behaviour and attitude data on respondents’ daily transit usage and their direct rating of importance on factors of route-level transit quality of service. A series of statistical analyses is conducted to examine the relationships between transit users’ travel and personal characteristics and their transit usage characteristics. A factor-cluster segmentation procedure is applied to respodents’ importance ratings on service quality variables regarding transit route preference to explore users’ various perspectives to transit quality of service. Based on the perceptions of service quality collected from the second wave survey, a series of quality criteria of the transit routes under study was quantitatively measured, particularly, the travel time reliability in terms of schedule adherence. It was proved that mixed traffic conditions and peak-period effects can affect transit service reliability.
Multinomial logit models of transit user’s route choice were estimated using route-level service quality perceptions collected in the second wave survey. Relative importance of service quality factors were derived from choice model’s significant parameter estimates, such as access and egress times, seat availability, and busway system. Interpretations of the parameter estimates were conducted, particularly the equivalent in-vehicle time of access and egress times, and busway in-vehicle time. Market segmentation by trip origin was applied to investigate the difference in magnitude between the parameter estimates of access and egress times. The significant costs of transfer in transit trips were highlighted. These importance ratios were applied back to quality perceptions collected as RP data to compare the satisfaction levels between the service attributes and to generate an action relevance matrix to prioritise attributes for quality improvement.
An empirical study on the relationship between average passenger waiting time and transit service characteristics was performed using the service quality perceived. Passenger arrivals for services with long headways (over 15 minutes) were found to be obviously coordinated with scheduled departure times of transit vehicles in order to reduce waiting time. This drove further investigations and modelling innovations in passenger’ access arrival time choice and its relationships with transit service characteristics and average passenger waiting time. Specifically, original contributions were made in formulation of expected waiting time, analysis of the risk-aversion attitude to missing desired service run in the passengers’ access time arrivals’ choice, and extensions of the utility function specification for modelling passenger access arrival distribution, by using complicated expected utility forms and non-linear probability weighting to explicitly accommodate the risk of missing an intended service and passenger’s risk-aversion attitude.
Discussions on this research’s contributions to knowledge, its limitations, and recommendations for future research are provided at the concluding section of this thesis.
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Al-Ogaili, Farah F. "Incorporating Environmental Factors into Trip Planning." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1508196014262712.
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Liu, I. Chun, and 劉亦群. "Adaptive route-choice and passenger assignment models for overlapping transit routes." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/22351399633092908360.
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So, Siu-Ian. "Behavioral models of multi-destination travelers." 2005. http://docs.lib.purdue.edu/dissertations/AAI3185836/.
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Razo, Michael D. "Route Choice Behavior in Risky Networks with Real-Time Information." 2010. https://scholarworks.umass.edu/theses/399.
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This research investigates route choice behavior in networks with risky travel times and real-time information. A stated preference survey is conducted in which subjects use a PC-based interactive maps to choose routes link-by-link in various scenarios. The scenarios include two types of maps: the first presenting a choice between one stochastic route and one deterministic route, and the second with real-time information and an available detour. The first type measures the basic risk attitude of the subject. The second type allows for strategic planning, and measures the effect of this opportunity on subjects' choice behavior.
Results from each subject are analyzed to determine whether subjects planned strategically for the en route information or simply selected fixed paths from origin to destination. The full data set is used to estimate route choice models that account for both risk attitude and strategic thinking. Estimation results are used to assess whether models that incorporate strategic behavior more accurately reflect route choice than do simpler path-based models.
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Jiin-Long, Leu, and 呂錦隆. "A Study on The Behavior of Disaggreate Travel Route Choice and Diversion Propensity Models." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/16354555441000409985.
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碩士國立成功大學
交通管理(科學)學系
82
The purpose of this study is to observe the important variables that will affect the route choice and route diversion propensity behavior of radio-taxi and car drivers in Tainan Area.We collected the revealed preference data of route choice behavior and stated preference data of route diversion propensity and used them to construct proper models. This study used logit model, poisson regression model and ordered probit model to construct route choice and diversion models according to different trip purpose, different market segmentation and different data.We found the following results: 1.Due to limited traffic information in Tainan Area, the effect of traffic information is not clear. 2.Of all route choice models,the models estimated by logit model were best.Of all route diversion propensity models ,the models estimated by ordered probit model were better. 3.Generally speaking,travel time is a very important varable in deciding car drivers'' route choice and diversion behavior. The influence of social economic variables were not significant. 4.The effect of different trip purpose on car drivers'' route choice behavior were not significant, but the effect of market segmentation were significant.
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Hung, Yu-Fang, and 洪玉芳. "Discrete Choice Models Considering Endogenous Explanatory Variables：A case study of highway passenger transport in Kaohsiung-Taipei route." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/16628391848570272032.
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碩士國立成功大學
交通管理學系碩博士班
91
Discrete choice model have been widely applied in consumer choice behavior researches. In earlier researches, they treated price as an exogenous variable while it should be treated as endogenous, because price is correlated with the error term in the utilities. This correlation will violate the basic assumptions of model, resulting in biased coefficient of price, producing misleading results, and seriously affecting the outcome of marketing decisions. The correlation results from that the market mechanism will increase the prices of products to reflect desirable attributes that are observed by consumers but not measured by researchers. This research aims to account for endogeneity in discrete choice model. In this thesis, we use cross-sectional data from six companies serving the Kaohsiung-Taipei route to examine if “price” or “price perception” suffered from the endogeneity problem and to what extents. By applying control function approach, we correct the biased estimate of price, and be able to interpret travelers’ choice behavior more correctly. Besides, we also construct discrete choice model considering endogeneity and individual heterogeneity simultaneously. The aim is to find out the preferences of travelers toward different companies. The empirical results are as follow: In the aspect of price endogeneity, we find (1) Since other service variables have reflected most modal attributes, there are few omitted modal attributes. Hence the endogeneity of “price” data we use is not important. (2) Since “price perception” represent individual’s preferences, it is therefore correlated with the unobserved preferences part in error term. The coefficient of “price perception” increases substantially when accounting for endogeneity. (3) The more serious the endogeneity, the more biased the coefficients are. In the aspect of heterogeneity, we find (1) Travelers’ evaluations toward highway passenger transport companies are heterogeneous, and some of them are similar. (2) Endogeneity does affect the structures of models considering heterogeneity. (3) Models which account for endogeneity are better than those that don’t. (4) When using “price perception” data, accounting for heterogeneity may lighten the endogeneity problem.
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Zimmermann, Maëlle. "Route choice and traffic equilibrium modeling in multi-modal and activity-based networks." Thèse, 2019. http://hdl.handle.net/1866/22664.
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Lownes, Nicholas Earl. "The commuter rail circulator network design problem: formulation, solution methods, and applications." Thesis, 2007. http://hdl.handle.net/2152/3352.
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Commuter rail is increasingly popular as a means to introduce rail transportation to metropolitan transportation systems. The long-term benefits of commuter rail include the addition of capacity to the transportation system, providing a quality commute alternative, and shifting land use toward transit-oriented development patterns. The success of a commuter rail system depends upon cultivating a ridership base upon which to expand and improve the system. Cultivating this ridership is dependent upon offering a quality transportation option to commuters. Characteristics of commuter rail systems in the United States present challenges to offering quality service that must be overcome. Commuter rail has been implemented only on existing rail right-of-way (ROW) and infrastructure (depending upon condition) in the United States. Existing rail ROW does not often coincide with current commercial and residential demand centers and necessitates the use of a circulator system to expand the service boundary of commuter rail to reach these demand centers. The commuter rail circulator network design problem (CRCNDP) addresses a particular aspect of the commuter rail trip, seeking to improve the performance of the entire system through accurately modeling the portion of the trip from rail station to the final destination. This final leg includes both the trip on the circulator vehicle and the walking trip from the circulator stop to the final destination. This dissertation seeks to provide an innovative mathematical programming formulation and solution methodology for the CRCNDP and apply this method to a case study.
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Unnikrishnan, Avinash 1980. "Equilibrium models accounting for uncertainty and information provision in transportation networks." 2008. http://hdl.handle.net/2152/17916.
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Researchers in multiple areas have shown that characterizing and accounting for the uncertainty inherent in decision support models is critical for developing more efficient planning and operational strategies. This is particularly applicable for the transportation engineering domain as most strategic decisions involve a significant investment of money and resources across multiple stakeholders and has a considerable impact on the society. Moreover, most inputs to transportation models such as travel demand depend on a number of social, economic and political factors and cannot be predicted with certainty. Therefore, in recent times there has been an increasing emphasis being placed on identifying and quantifying this uncertainty and developing models which account for the same. This dissertation contributes to the growing body of literature in tackling uncertainty in transportation models by developing methodologies which address the uncertainty in input parameters in traffic assignment models. One of the primary sources of uncertainty in traffic assignment models is uncertainty in origin destination demand. This uncertainty can be classified into long term and short term demand uncertainty. Accounting for long term demand uncertainty is vital when traffic assignment models are used to make planning decisions like where to add capacity. This dissertation quantifies the impact of long term demand uncertainty by assigning multi-variate probability distributions to the demand. In order to arrive at accurate estimates of the expected future system performance, several statistical sampling techniques are then compared through extensive numerical testing to determine the most "efficient" sampling techniques for network assignment models. Two applications of assignment models, network design and network pricing are studied to illustrate the importance of considering long term demand uncertainty in transportation networks. Short term demand uncertainty such as the day-to-day variation in demand affect traffic assignment models when used to make operational decisions like tolling. This dissertation presents a novel new definition of equilibrium when the short term demand is assumed to follow a probability distribution. Various properties of the equilibrium such as existence, uniqueness and presence of a mathematical programming formulation are investigated. Apart from demand uncertainty, operating capacity in real world networks can also vary from day to day depending on various factors like weather conditions and incidents. With increasing deployment of Intelligent Transportation Systems, users get information about the impact of capacity or the state of the roads through various dissemination devices like dynamic message signs. This dissertation presents a new equilibrium formulation termed user equilibrium with recourse to model information provision and capacity uncertainty, where users learn the state or capacity of the link when they arrive at the upstream node of that link. Depending on the information received about the state of the upstream links, users make different route choice decisions. In this work, the capacity of the links in the network is assumed to follow a discrete probability distribution. A mathematical programming formulation of the user equilibrium with recourse model is presented along with solution algorithm. This model can be extended to analytically model network flows under information provision where the arcs have different cost functional form depending on the state of the arc. The corresponding system optimal with recourse model is also presented where the objective is minimize the total system cost. The network design problem where users are routed according to the user equilibrium with recourse principle is studied. The focus of this study is to show that planning decisions for networks users have access to information is significantly different from the no-information scenario.text
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Mai, Anh Tien. "Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models." Thèse, 2015. http://hdl.handle.net/1866/15871.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications.
We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices.
The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms.
Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models.
The second theme is related to the estimation of static discrete choice models with large choice sets.
We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm.
Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process.
The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important.
Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.Les gens consacrent une importante part de leur existence à prendre diverses décisions, pouvant affecter leur demande en transport, par exemple les choix de lieux d'habitation et de travail, les modes de transport, les heures de départ, le nombre et type de voitures dans le ménage, les itinéraires ... Les choix liés au transport sont généralement fonction du temps et caractérisés par un grand nombre de solutions alternatives qui peuvent être spatialement corrélées. Cette thèse traite de modèles pouvant être utilisés pour analyser et prédire les choix discrets dans les applications liées aux réseaux de grandes tailles. Les modèles et méthodes proposées sont particulièrement pertinents pour les applications en transport, sans toutefois s'y limiter. Nous modélisons les décisions comme des séquences de choix, dans le cadre des choix discrets dynamiques, aussi connus comme processus de décision de Markov paramétriques. Ces modèles sont réputés difficiles à estimer et à appliquer en prédiction, puisque le calcul des probabilités de choix requiert la résolution de problèmes de programmation dynamique. Nous montrons dans cette thèse qu'il est possible d'exploiter la structure du réseau et la flexibilité de la programmation dynamique afin de rendre l'approche de modélisation dynamique en choix discrets non seulement utile pour représenter les choix dépendant du temps, mais également pour modéliser plus facilement des choix statiques au sein d'ensembles de choix de très grande taille. La thèse se compose de sept articles, présentant divers modèles et méthodes d'estimation, leur application ainsi que des expériences numériques sur des modèles de choix discrets de grande taille. Nous regroupons les contributions en trois principales thématiques: modélisation du choix de route, estimation de modèles en valeur extrême multivariée (MEV) de grande taille et algorithmes d'optimisation non-linéaire. Cinq articles sont associés à la modélisation de choix de route. Nous proposons différents modèles de choix discrets dynamiques permettant aux utilités des chemins d'être corrélées, sur base de formulations MEV et logit mixte. Les modèles résultants devenant coûteux à estimer, nous présentons de nouvelles approches permettant de diminuer les efforts de calcul. Nous proposons par exemple une méthode de décomposition qui non seulement ouvre la possibilité d'estimer efficacement des modèles logit mixte, mais également d'accélérer l'estimation de modèles simples comme les modèles logit multinomiaux, ce qui a également des implications en simulation de trafic. De plus, nous comparons les règles de décision basées sur le principe de maximisation d'utilité de celles sur la minimisation du regret pour ce type de modèles. Nous proposons finalement un test statistique sur les erreurs de spécification pour les modèles de choix de route basés sur le logit multinomial. Le second thème porte sur l'estimation de modèles de choix discrets statiques avec de grands ensembles de choix. Nous établissons que certains types de modèles MEV peuvent être reformulés comme des modèles de choix discrets dynamiques, construits sur des réseaux de structure de corrélation. Ces modèles peuvent alors être estimées rapidement en utilisant des techniques de programmation dynamique en combinaison avec un algorithme efficace d'optimisation non-linéaire. La troisième et dernière thématique concerne les algorithmes d'optimisation non-linéaires dans le cadre de l'estimation de modèles complexes de choix discrets par maximum de vraisemblance. Nous examinons et adaptons des méthodes quasi-Newton structurées qui peuvent être facilement intégrées dans des algorithmes d'optimisation usuels (recherche linéaire et région de confiance) afin d'accélérer le processus d'estimation. Les modèles de choix discrets dynamiques et les méthodes d'optimisation proposés peuvent être employés dans diverses applications de choix discrets. Dans le domaine des sciences de données, des modèles qui peuvent traiter de grands ensembles de choix et des ensembles de choix séquentiels sont importants. Nos recherches peuvent dès lors être d'intérêt dans diverses applications d'analyse de la demande (analyse prédictive) ou peuvent être intégrées à des modèles d'optimisation (analyse prescriptive). De plus, nos études mettent en évidence le potentiel des techniques de programmation dynamique dans ce contexte, y compris pour des modèles statiques, ouvrant la voie à de multiples directions de recherche future.
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"Data organization for routing on the multi-modal public transportation system: a GIS-T prototype of Hong Kong Island." 2001. http://library.cuhk.edu.hk/record=b5890808.
Full textAbstract:
Yu Hongbo.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 130-138).
Abstracts in English and Chinese.
ABSTRACT IN ENGLISH --- p.i-ii
ABSTRACT IN CHINESE --- p.iii
ACKNOWLEDGEMENTS --- p.iv-v
TABLE OF CONTENTS --- p.vi-viii
LIST OF TABLES --- p.ix
LIST OF FIGURES --- p.x-xi
Chapter CHAPTER I --- INTRODUCTION
Chapter 1.1 --- Problem Statement --- p.1
Chapter 1.2 --- Research Purpose --- p.5
Chapter 1.3 --- Significance --- p.7
Chapter 1.4 --- Methodology --- p.8
Chapter 1.5 --- Outline of the Thesis --- p.9
Chapter CHAPTER II --- LITERATURE REVIEW
Chapter 2.1 --- Introduction --- p.12
Chapter 2.2 --- Origin of GIS --- p.12
Chapter 2.3 --- Development of GIS-T --- p.15
Chapter 2.4 --- Capabilities of GIS-T --- p.18
Chapter 2.5 --- Structure of a GIS-T --- p.19
Chapter 2.5.1 --- Data Models for GIS-T --- p.19
Chapter 2.5.2 --- Relational DBMS and Dueker-Butler's Data Model for Transportation --- p.22
Chapter 2.5.3 --- Objected-oriented Approach --- p.25
Chapter 2.6 --- Main Techniques of GIS-T --- p.26
Chapter 2.6.1 --- Linear Location Reference System --- p.26
Chapter 2.6.2 --- Dynamic Segmentation --- p.27
Chapter 2.6.3 --- Planar and Non-planar Networks --- p.28
Chapter 2.6.4 --- Turn-table --- p.28
Chapter 2.7 --- Algorithms for Finding Shortest Paths on a Network --- p.29
Chapter 2.7.1 --- Overview of Routing Algorithms --- p.29
Chapter 2.7.2 --- Dijkstra's Algorithm --- p.31
Chapter 2.7.3 --- Routing Models for the Multi-modal Network --- p.32
Chapter 2.8 --- Recent Researches on GIS Data Models for the Multi-modal Transportation System --- p.33
Chapter 2.9 --- Main Software Packages for GIS-T --- p.36
Chapter 2.10 --- Summary --- p.37
Chapter CHAPTER III --- MODELING THE MULTI-MODAL PUBLIC TRANSPORTATION SYSTEM
Chapter 3.1 --- Introduction --- p.40
Chapter 3.2 --- Elaborated Stages and Methods for GIS Modeling --- p.40
Chapter 3.3 --- Application Domain: The Multi-modal Public Transportation System --- p.43
Chapter 3.3.1 --- Definition of a Multi-modal Public Transportation System --- p.43
Chapter 3.3.2 --- Descriptions of the Multi-modal Public transportation System --- p.44
Chapter 3.3.3 --- Objective of the Modeling Work --- p.46
Chapter 3.4 --- A Layer-cake Based Application Domain Model for the Multi- modal Public Transportation System --- p.46
Chapter 3.5 --- A Conceptual Model for the Multi-modal Public Transportation System --- p.49
Chapter 3.6 --- Logical and Physical Implementation of the Data Model for the Multi-modal Public Transportation System --- p.54
Chapter 3.7 --- Criteria for Routing on the Multi-modal Public Transportation System --- p.57
Chapter 3.7.1 --- Least-time Routing --- p.58
Chapter 3.7.2 --- Least-fare Routing --- p.60
Chapter 3.7.3 --- Least-transfer Routing --- p.60
Chapter 3.8 --- Summary --- p.61
Chapter CHAPTER IV --- DATA PREPARATION FOR THE STUDY AREA
Chapter 4.1 --- Introduction --- p.53
Chapter 4.2 --- The Study Area: Hong Kong Island --- p.63
Chapter 4.2.1 --- General Information of the Transportation System on Hong Kong Island --- p.63
Chapter 4.2.2 --- Reasons for Choosing Hong Kong Island as the Study Area --- p.66
Chapter 4.2.3 --- Mass Transit Routes Selected for the Prototype --- p.67
Chapter 4.3 --- Data Source and Data Collection --- p.67
Chapter 4.4 --- Geographical Data Preparation --- p.71
Chapter 4.4.1 --- Data Conversion --- p.73
Chapter 4.4.2 --- Geographical Data Input --- p.79
Chapter 4.5 --- Attribute Data Input --- p.86
Chapter 4.6 --- Summary --- p.88
Chapter CHAPTER V --- IMPLEMENTATION OF THE PROTOTYPE
Chapter 5.1 --- Introduction --- p.89
Chapter 5.2 --- Construction of the Route Service Network --- p.89
Chapter 5.2.1 --- Generation of the Geographical Network --- p.90
Chapter 5.2.2 --- Setting Attribute Data for the Route Service Network --- p.95
Chapter 5.3 --- A GIS-T Prototype for the Study Area --- p.102
Chapter 5.4 --- General GIS Functions of the Prototype --- p.104
Chapter 5.4.1 --- Information Retrieve --- p.104
Chapter 5.4.2 --- Display --- p.105
Chapter 5.4.3 --- Data Query --- p.105
Chapter 5.5 --- Routing in the Prototype --- p.105
Chapter 5.5.1 --- Routing Procedure --- p.108
Chapter 5.5.2 --- Examples and Results --- p.110
Chapter 5.5.3 --- Comparison and Analysis --- p.113
Chapter 5.6 --- Summary --- p.118
Chapter CHAPTER VI --- CONCLUSION
Chapter 6.1 --- Research Findings --- p.123
Chapter 6.2 --- Research Limitations --- p.126
Chapter 6.3 --- Direction of Further Studies --- p.128
BIBLIOGRAPHY --- p.130
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Tian, Hengliang. "Travelers' route choice behavior in risky networks." 2013. https://scholarworks.umass.edu/dissertations/AAI3603163.
Full textAbstract:
The accurate modeling of travelers' route choice decision making when faced with unreliable (risky) travel times is necessary for the assessment of policies aimed at improving travel time reliability. Two major objectives are studied in this thesis. The first objective is to evaluate the applicability of a process model to route choice under risk where the actual process of decision making is captured. Traditionally, we adopt "as-if" econometric models to predict people's route choice decisions. The second objective is to investigate travelers' capability to incorporate future real-time traffic information into their current route choice decision making. Two separate stated preference (SP) surveys were conducted for each objective. The first SP survey used an interactive map in a computer based test. The second SP survey used a full-scale high-fidelity driving simulator. Compared with econometric models, process models have been rarely investigated in travel decision making under risk. A process model aims to describe the actual de cision making procedure and could potentially provide a better explanation to route choice behavior. A process model, Priority Heuristic (PH), developed by Brand statter et al. (2006) is introduced to the travel choice context and its probabilistic version, Probabilistic Priority Heuristic (PPH), is developed and estimated in this study. With data collected from a stated preference (SP) survey which is based on an animated computer interface, one econometric model, Rank-Dependent Expected Utility (RDEU) model, and two other alternative models were compared with the PPH model in a cross validation test to investigate their data-fitting and predictive performance. Our results show that the PPH model outperforms the RDEU model in both data-fitting and predictive performance. This suggests that the process modeling paradigm could be a promising new area in travel behavior research. With the advance of information and telecommunication technology, real-time traffic information is increasingly more available to help travelers make informed route choice decisions when faced with unreliable travel times. A strategic route choice refers to a decision taking into account future diversion possibilities at downstream nodes based on real-time information not yet available at the time of decision-making. Based on the data collected from a driving simulator experiment and a matching PC based experiment, a mixed Logit model with two latent classes, strategic and non strategic route choice, is specified and estimated. The estimates of the latent class probabilities show that a significant portion of route choice decisions are strategic and subjects can learn to make more strategic route choice as they have more experience with the decision scenarios. Non-parametric tests additionally show that network complexity adversely affects travelers' strategic thinking ability in a driving simulator environment but not in a PC environment and a parallel driving task only affects strategic thinking ability in a difficult scenario but not a simple one. In addition, we find that people's strategic thinking ability are influenced by their gender and driving experience (mileage) in the non-parametric analysis, but not in the modeling work. These findings suggest that a realistic route choice model with real-time traffic information should consider both strategic and non-strategic behavior, which vary with the characteristics of both the network and the driver.
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Chaudhary, Ankita. "Impact of range anxiety on driver route choices using a panel-integrated choice latent variable model." Thesis, 2014. http://hdl.handle.net/2152/28254.
Full textAbstract:
There has been a significant increase in private vehicle ownership in the last decade leading to substantial increase in air pollution, depleting fuel reserves, etc. One of the alternatives known as battery operated electric vehicles (BEVs) has the potential to reduce carbon footprints due to lesser or no emissions and thus the focus on shifting people from gasoline operated vehicles (GVs) to BEVs has increased considerably recently. However, BEVs have a limited ‘range’ and takes considerable time to completely recharge its battery. In addition, charging stations are not as pervasive as gasoline stations. As a result a new fear of getting stranded is observed in BEV drivers, known as range anxiety. Range anxiety has the potential to substantially affect the route choice of a BEV user. It has also been a major cause of lower market shares of BEVs. Range anxiety is a latent feeling which cannot be measured directly. It is not homogenous either and varies among different socio-economic groups. Thus, a better understanding of BEV users’ behavior may shed light on some potential solutions that can then be used to improve their market shares and help in developing new network models which can realistically capture effects of varying EV adoptions. Thus, in this study, we analyze the factors that may impact BEV users’ range anxiety in addition to their route choice behavior using the integrated choice latent variable model (ICLV) proposed by Bhat and Dubey (2014). Our results indicate that an individual’s range anxiety is significantly affected by their age, gender, income, awareness of charging stations, BEV ownership and other category vehicle ownership. Further, it also highlights the importance of including disutility caused by distance while considering network flow models with combined GV and BEV assignment. Finally, a more concentrated effort can be directed towards increasing the awareness of charging station locations in the neighborhood to help reduce the psychological barrier associated with range anxiety. Overcoming this barrier may help increase consumer confidence, resulting in increased BEV adoption and ultimately will lead towards a potentially pollution-free environment.text
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Morin, Léonard Ryo. "A dynamic sequential route choice model for micro-simulation." Thèse, 2012. http://hdl.handle.net/1866/9829.
Full textAbstract:
Dans les études sur le transport, les modèles de choix de route décrivent la sélection par un utilisateur d’un chemin, depuis son origine jusqu’à sa destination. Plus précisément, il s’agit de trouver dans un réseau composé d’arcs et de sommets la suite d’arcs reliant deux sommets, suivant des critères donnés. Nous considérons dans le présent travail l’application de la programmation dynamique pour représenter le processus de choix, en considérant le choix d’un chemin comme une séquence de choix d’arcs. De plus, nous mettons en œuvre les techniques d’approximation en programmation dynamique afin de représenter la connaissance imparfaite de l’état réseau, en particulier pour les arcs éloignés du point actuel. Plus précisément, à chaque fois qu’un utilisateur atteint une intersection, il considère l’utilité d’un certain nombre d’arcs futurs, puis une estimation est faite pour le restant du chemin jusqu’à la destination. Le modèle de choix de route est implanté dans le cadre d’un modèle de simulation de trafic par événements discrets. Le modèle ainsi construit est testé sur un modèle de réseau routier réel afin d’étudier sa performance.In transportation modeling, a route choice is a model describing the selection of a route between a given origin and a given destination. More specifically, it consists of determining the sequence of arcs leading to the destination in a network composed of vertices and arcs, according to some selection criteria. We propose a novel route choice model, based on approximate dynamic programming. The technique is applied sequentially, as every time a user reaches an intersection, he/she is supposed to consider the utility of a certain number of future arcs, followed by an approximation for the rest of the path leading up to the destination. The route choice model is implemented as a component of a traffic simulation model, in a discrete event framework. We conduct a numerical experiment on a real traffic network model in order to analyze its performance.
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Tu, Ming-Lin, and 杜明臨. "A Study on Stochastic Dynamic Route Choice Model." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/69465642675399515924.
Full text
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Xiao, Yi-Chun, and 蕭伊君. "A Study on Multi-objective Shortest Route Choice Optimization Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/84536072060480929041.
Full textAbstract:
碩士逢甲大學
都市計畫所
99
With the development of car navigation systems, more drivers experienced to its convenience. The current commercial car navigation system is based on providing the shortest distance possible. However, there are other factors that concern the driver when it comes to selection of path. The choices can generally be divided into macro and micro view factors. As for macro, cost, safety, comfort and so on is taken into consideration; and as for micro, such as distance, number of intersection and etc is considered. Since the macroscopically measurable factors have a high degree of difficulty, it is not conducive to apply to car navigation systems. Therefore, this study will also consider the spatial distance, the number of traffic lights to intersections, the level of road and the number of turns, to achieve the shortest spatial distance, the least number of intersection be through, the least number of turns and the maximum level of road, in order to build the multi-objective decision model to select the best path. Many studies have pointed out that the shortest path (SP) problem is NP-complete. It is hard to find the best-compromise solution for the SP problem without spending much effort. It is also impossible to identify the problem by utilizing mathematical programming approach in a finite time. A heuristic or macro algorithm is usually applied to solve the SP problem. The genetic and Dijkstra algorithm is used in this study to solve the problems. At the first, convert the multi-objective problem into a single objective problem and then apply the Dijkstra method to identify the best-compromise solution. On the other hand, utilize the genetic algorithm to search for the best-compromise solution by converting into genes and chromosomes and the design of suitable copy, crossover and mutation functions principles. Use genetic algorithm for random searches and able to do a database search in the solution space in order to solve the multi-target path established to select the best of the problem. Compare the two algorithms and the model constructed in this study for solving approach and results analysis provide randomly and broadly searching capabilities for solving multi-objective path selection optimization problem. Empirical studies will select two types of road network structure to carry out. The empirical results show that study proposed a multi-objective optimization model to solve the path is feasible through the Dijkstra algorithm and genetic algorithm. And, proposed a multi-objective path optimization model to make a more precise simulation of the decision-making behavior of drivers’ path selection. The experimental results demonstrate the advantage of the multi-objective path optimization model provides automobile drivers more diverse and richer information than the conventional SDP. With the aids of the GIS and MOPOAT, the optimal paths of the MOPO and SOPO problems can be easily identified by the PGA in just a matter of seconds, despite the fact that these problems are highly complex and difficult to solve manually.
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Usyukov, Vladimir. "Development of a Cyclists' Route-Choice Model: An Ontario Case Study." Thesis, 2013. http://hdl.handle.net/10012/8088.
Full textAbstract:
This research presents the first North American route-choice model for cyclists developed from a large sample of GPS data. These findings should encourage all interested municipalities to implement cycling as part of their transportation planning by determining key designing and planning factors to encourage cycling. The analysis is based on processing revealed preference data obtained from 415 self-selected cyclists in Waterloo, Ontario, which corresponded to 2000 routes. Cyclists' route decisions were modeled using multinomial logit framework of discrete choice theory. The main finding involved in capturing two different behaviour groups, namely experienced and inexperienced cyclists. This was subsequently reflected in the two developed models. The key factors impacting route-choice were found to be trip length, speed, volume, bicycle lane presence and percent of uphill gradient that cyclists face. The predictive power of the best model was 65%. The outlier analysis found that the relative significance of uphill gradient coefficient in one circumstances and perhaps the exclusion of unobserved variables, in other circumstances could be the cause why probability of actual choice was not predicted by both models all the time.
In addition, this research involved in the development of a transferability study involving route-choice modeling for cyclists. The analysis is based on the revealed preference data obtained from 255 self-selected cyclists in Peel Region, Ontario, which corresponded to 425 unique routes. The choice set contained actual routes and a combination of alternatives obtained by labeling and impedance rules. The transferability of Waterloo's model to Peel Region was 37%. This means that cyclists behaviour in the Peel Region can be predicted correctly by travel length, bicycle lane presence and percent of uphill gradient for every third cyclist.
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Liao, YuanLing, and 廖苑伶. "A Study of Dynamic Route Choice Behavior with Fuzzy Utility Model." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/54647153372096210827.
Full textAbstract:
碩士淡江大學
運輸管理學系
88
The focus of this thesis is on the auto-driving commuters’ day-to-day dynamic departure time and route choice behavior. Such behavior is by its own nature a complex issue, involving each individual''''s perception of the decision attributes and impact of time. Probabilistic model such as random utility theory has been widely applied to address the uncertainty of travel''''s decision behavior. On the other hand, Fuzzy set theory can handle the phenomenon of ambiguous events rather than random nature, which may well be suitable for addressing human decision behavior such as travel decisions. Previous studies under the direction of Dr. Chee Chung Tong at Tamkang University such as Chao''''s thesis( 1998 ), Chang''''s thesis( 1998 ) and the most recent Wu''''s(1999 ) have demonstrated promising results. With Chao''''s pioneering work to explore the feasibility and to establish the general framework of fuzzy inference models, Chang extended this framework to include extra travel time prediction and membership function shift components for the issues of day-to-day dynamics. Wu then adopted another approach to tackle the dynamic issue by taking the advantage of dynamic feedback feature of Neuro-network into the original framework to form a Neuro-Fuzzy network model. What in common in the above three studies is that each of the various decision attributes was treated separately (in-tandem) in an approximate reasoning phase and later combined in the internal presentation phase and generate decision outcome in the final defuzzification phase. In this thesis, a Fuzzy Utility Model was proposed. The major difference lies in the alternative treatment of decision attributes and the consequent process while using similar FNN model framework of Wu. It is performed firstly by integrating individual attributes into a single index which can be viewed as a (weighted) combined attractiveness of a certain travel decision as defined as "Score" or "Utility" in decision theory or probabilistic behavior models followed by similar process in fuzzy reasoning with Neuro-network. Three different approaches were employed to calibrate the weight of associated attributes respectively. One is from the Multi-attribute Utility Function theory, another from multi-criteria decision context, and the other from the famous random utility behavior models. Observations of this study came from the same controlled experiment approach of previous serial studies where the experiment subject’ departure time and route choices were recorded along with their individual statement regarding their own perception to the decision related attributes. Through a series of consecutive verification process the Fuzzy Utility decision model formulated in this study has generally demonstrated improvement over previous models in terms of percentage of correct matches.
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Cheng, Hung-Ming, and 鄭鴻明. "A Study on the Route Choice Behavior Model of Car Drivers." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/06441104403640511260.
Full textAbstract:
碩士國立交通大學
交通運輸研究所
85
The purpose of this study is to observe the important variables that will effect the route choice behavior of car drivers in Taipei Urban Area. We collected the related data of route choice behavior and then classify them by trip origin and destination, to construct proper route choice behavior models of car drivers in Urban Area Taipei. In this study we used two-step survey. First we collected the important variables that will effect the route choice behavior of car drivers in Taipei Urban Area. Then we used previously results to design next survey. In this survey, we collected the revealed preference data and stated preference data. The revealed preference data includes real route and substitute route; The stated preference data means the route which car drivers select when face an especially transportation situation. We also collected some personal basic data of answers just as age, sex, income and so on; some data of using car situation and trip characters. This study used Logit model to construct route-choice behavior models according to different route choice set and personal basic data and trip characters data. Finally, we construct a positive study. It used the ID3 algorithm that is one kind of knowledge acquisition of expert analysis system to construct a really case study in Taipei Urban Area. According to this study, we can find the following results: 1. After cross analysis and testing of statistical hypothesis the personal basic data and trip characters data totally 17 items, we find that ''occupation'' is most related with other items, and that ''fully insurance'' and ''sex'' are least related with other items. 2. Generally speaking, running speed and really running distance are most important variables in deciding car drivers'' route choice behavior, then are traffic information provided and left-turn numbers. In the personal basic data, sex, age, traffic expense and income are more important variables. In the trip characters data, trip time, car age, fully insurance, displacement (c.c.), owner of car, and changes route situations are more important variables. The Rho-squre value (ρ2) appears good in every model,they show that these models are proper in Taipei Urban Area. 3. In the positive case study, if we control the attributes to 3 or 4, the forecast successful rates of inductive decision tree are more than 50%, they show that ID3 algorithm is a utility method in forecasting route-choice behavior of car drivers.
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Morin, Léonard Ryo. "Traffic prediction and bilevel network design." Thesis, 2020. http://hdl.handle.net/1866/24801.
Full textAbstract:
Cette thèse porte sur la modélisation du trafic dans les réseaux routiers et comment celle-ci est intégrée dans des modèles d'optimisation. Ces deux sujets ont évolué de manière plutôt disjointe: le trafic est prédit par des modèles mathématiques de plus en plus complexes, mais ce progrès n'a pas été incorporé dans les modèles de design de réseau dans lesquels les usagers de la route jouent un rôle crucial. Le but de cet ouvrage est d'intégrer des modèles d'utilités aléatoires calibrés avec de vraies données dans certains modèles biniveaux d'optimisation et ce, par une décomposition de Benders efficace. Cette décomposition particulière s'avère être généralisable par rapport à une grande classe de problèmes communs dans la litérature et permet d'en résoudre des exemples de grande taille.
Le premier article présente une méthodologie générale pour utiliser des données GPS d'une flotte de véhicules afin d'estimer les paramètres d'un modèle de demande dit recursive logit. Les traces GPS sont d'abord associées aux liens d'un réseau à l'aide d'un algorithme tenant compte de plusieurs facteurs. Les chemins formés par ces suites de liens et leurs caractéristiques sont utilisés afin d'estimer les paramètres d'un modèle de choix. Ces paramètres représentent la perception qu'ont les usagers de chacune de ces caractéristiques par rapport au choix de leur chemin. Les données utilisées dans cet article proviennent des véhicules appartenant à plusieurs compagnies de transport opérant principalement dans la région de Montréal.
Le deuxième article aborde l'intégration d'un modèle de choix de chemin avec utilités aléatoires dans une nouvelle formulation biniveau pour le problème de capture de flot de trafic. Le modèle proposé permet de représenter différents comportements des usagers par rapport à leur choix de chemin en définissant les utilités d'arcs appropriées. Ces utilités sont stochastiques ce qui contribue d'autant plus à capturer un comportement réaliste des usagers. Le modèle biniveau est rendu linéaire à travers l'ajout d'un terme lagrangien basé sur la dualité forte et ceci mène à une décomposition de Benders particulièrement efficace. Les expériences numériques sont principalement menés sur un réseau représentant la ville de Winnipeg ce qui démontre la possibilité de résoudre des problèmes de taille relativement grande.
Le troisième article démontre que l'approche du second article peut s'appliquer à une forme particulière de modèles biniveaux qui comprennent plusieurs problèmes différents. La décomposition est d'abord présentée dans un cadre général, puis dans un contexte où le second niveau du modèle biniveau est un problème de plus courts chemins. Afin d'établir que ce contexte inclut plusieurs applications, deux applications distinctes sont adaptées à la forme requise: le transport de matières dangeureuses et la capture de flot de trafic déterministe. Une troisième application, la conception et l'établissement de prix de réseau simultanés, est aussi présentée de manière similaire à l'Annexe B de cette thèse.The subject of this thesis is the modeling of traffic in road networks and its integration in optimization models. In the literature, these two topics have to a large extent evolved independently: traffic is predicted more accurately by increasingly complex mathematical models, but this progress has not been incorporated in network design models where road users play a crucial role. The goal of this work is to integrate random utility models calibrated with real data into bilevel optimization models through an efficient Benders decomposition. This particular decomposition generalizes to a wide class of problems commonly found in the literature and can be used to solved large-scale instances. The first article presents a general methodology to use GPS data gathered from a fleet of vehicles to estimate the parameters of a recursive logit demand model. The GPS traces are first matched to the arcs of a network through an algorithm taking into account various factors. The paths resulting from these sequences of arcs, along with their characteristics, are used to estimate parameters of a choice model. The parameters represent users' perception of each of these characteristics in regards to their path choice behaviour. The data used in this article comes from trucks used by a number of transportation companies operating mainly in the Montreal region. The second article addresses the integration of a random utility maximization model in a new bilevel formulation for the general flow capture problem. The proposed model allows for a representation of different user behaviors in regards to their path choice by defining appropriate arc utilities. These arc utilities are stochastic which further contributes in capturing real user behavior. This bilevel model is linearized through the inclusion of a Lagrangian term based on strong duality which paves the way for a particularly efficient Benders decomposition. The numerical experiments are mostly conducted on a network representing the city of Winnipeg which demonstrates the ability to solve problems of a relatively large size. The third article illustrates how the approach used in the second article can be generalized to a particular form of bilevel models which encompasses many different problems. The decomposition is first presented in a general setting and subsequently in a context where the lower level of the bilevel model is a shortest path problem. In order to demonstrate that this form is general, two distinct applications are adapted to fit the required form: hazmat transportation network design and general flow capture. A third application, joint network design and pricing, is also similarly explored in Appendix B of this thesis.
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Fan, Hui-Chi, and 范惠琪. "Traveler's Route Choice Behavioral Model Considering Perceptions of Highway Level of Service." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/90787735370751520100.
Full textAbstract:
碩士國立暨南國際大學
土木工程學系
95
The highway’s level of service is an important index for assessing the efficiency of the highway. Conventional assessment of the highway’s level of service was based on traffic flow conditions (such as density and average speed) without considering the effects of users’ perception. This study addresses on investigating the highway’s level of service by incorporating users’ perception on highway environment. Two questionnaires were designed to collect the drivers’ preferences on different scenarios. The ordered probit model was used to model the perception of drivers on highway’s level of service. The mixed logit model was further used to investigate drivers’ route choice behavior while simultaneously considering drivers’ perception of highway’s level of service. The estimation results indicate that several factors significantly affect users’ perception of highway’s level of service and route choice behavior, which include gender, trip purpose, average speed, quality of pavement, number of traffic signals and truck percentage of highway. Moreover, sensitivity analysis shows that raising the toll fee will switch a large portion of drivers to toll-free highways. The result of this study can provide guidelines for transportation planners and drivers in decision making, and further mitigate traffic congestions.
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Chen, Hui-Yu, and 陳薈予. "A Route-Carrier Choice Model: The Impacts of Airline Mergers on Passengers’ Welfare." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/r5gt6t.
Full textAbstract:
碩士國立交通大學
運輸與物流管理學系
107
The fierce competition in the market has caused many airlines to go bankrupt or to merge with others, and the market structure has thus been changing, too. In view of the fact that the wave of mergers will continue to affect society and industry, a clearer understanding of its impact is an important research topic. From the literature review, it is known that airline mergers will affect the network structure, the state of competition, fares, service quality, and thus passenger welfare. However, most of the literature only partially analyzes the factors listed above, and the empirical study on the actual merger is very limited. Therefore, this study considers relevant factors more completely, establishes the travel demand model that provides sufficient details, and analyzes passenger welfare changes caused by the mergers rationally. This study first uses the aggregate data to construct a route-carrier choice model for metropolitan cities to analyze the market. The metropolitan area may contain multiple airports. Each route-carrier is a discrete choice, and passengers are free to choose between airports and flight types (connecting or direct). Also, not selecting any route-carrier (not generating any air trip) is permitted, so that the total demand can remain elastic. In addition, treatment groups and control groups are first defined, and difference-in-differences method is then used to measure the passenger welfare changes (including the analysis of various factors and the differences between traditional and low-cost airline merger). The results show that the substitutability from high to low are: routes within a carrier > OD airport > non-air alternatives. As for price endogeneity, route distance *oil price and route distance are effective instrument variables. In terms of welfare analysis, as a whole, airline mergers resulted in welfare increase (AA-US merger > US-HP merger > WN-FL merger). And if the markets are further divided into different categories, it can be found that the mergers caused welfare increase in most of the categories, while they also caused welfare decrease in the rest of the categories. To sum up, the study establishes a choice model that quantifies the impact of mergers on passenger welfare. This model keeps the demand elastic and incorporates route-carrier level variables; the nested structure is designed to take the substitutability and competitive of choices into account (e.g. travelers may choose different OD airports and routes in multiple airports metropolitan areas). In addition, time value and price elasticity become more reasonable after using IVs to deal with endogeneity. The preliminary welfare analysis showed that the impact of the mergers on welfare is positive (as a whole), but differ among markets (city-pair) and airline types (FSC and LCC). Propensity score matching may be used to do further analysis.
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Hsiao-Chi, Peng, and 彭曉琪. "Dynamic User Equilibrium Doubly Constrained Origin-Destination /Departure Time/ Route Choice Bi-level Programming Model." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/27838548984279748782.
Full textAbstract:
碩士國立中央大學
土木工程研究所
89
Abstract This thesis, as follow-up study of Ying-Chun CHEN(1999), Tsung-Yi LEE(2000), attempts to further some important issues based on the dynamic user-equilibrium doubly constrained origin-destination /departure time/route choice model formulated using variational inequality approach and the solution algorithm of my model is using streamlined diagonalization lagrangian(GP) method to solves super network problem. As a result of road has link capacity constraint in the actual network, in order to my model conform to practicality condition, attempt to incorporate inflow link capacity constrained into it, and formulated the dynamic capacitated user-equilibrium doubly constrained origin-destination/departure time/route choice model. And numerical examples are provided for test and analysis. That uses bi-level programming method to formulate the dynamic signal timings control (DSTC) model. The upper level is dynamic signal timings optimal model, it tries to minimum the total travel cost by allocating the green times and determining link capacities, and the lower level is dynamic user-equilibrium doubly constrained origin-destination /departure time/route choice model, based on the fixed link capacities , searches the shortest travel time time-route for use. In accordance with variational inequality sensitivity analysis theory attain sensitivity analysis information by generalized inverse approach and developing solution algorithm. Finally, making several numerical examples to verify this research is correctly.
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Chang, Chai-Wei, and 張佳偉. "Computational Efficiency of Path-based Algorithm in Solving the Dynamic User-optimal Route Choice Model." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/39471853624537800763.
Full textAbstract:
碩士國立中央大學
土木工程學系
85
In the last three decades, the link-based algorithm of Frank- and-Wolfe has seen widely used in traffic assignment due to the advantage of using less computer memory. However, this advantage becomes less and less important as the computer technology advances on. In the meantime, the path-based solution algorithms have attracted much of researchers'' interest due to their potential applications in the area of disaster evacuation and/or route guidance for travelers. In this thesis, two path-based solution algorithms, i.e., disaggregated simplicial decomposition method of Hohenbalken and gradient projection method, are revisited and demonstrated with dynamic user-optimal route choice problems. It is observed that the path-based algorithms generally perform much better than the link-based algorithm in terms of computational time and degree of precision but slight inferior in memory requirement.