Rozprawy doktorskie na temat „Time travel”

Given the complexity of transportation systems, generating optimal routing decisions is a critical issue. This thesis focuses on how routing decisions can be computed by considering the distribution of travel time and associated risks. More specifically, the routing decision process is modeled in a way that explicitly considers the dependence between the travel times of different links and the risks associated with the volatility of travel time. Furthermore, the computation of this volatility allows for the development of the travel time derivative, which is a financial derivative based on travel time. It serves as a value or congestion pricing scheme based not only on the level of congestion but also its uncertainties. In addition to the introduction (Chapter 1), the literature review (Chapter 2), and the conclusion (Chapter 6), the thesis consists of two major parts:

In part one (Chapters 3 and 4), the travel time distribution for transportation links and paths, conditioned on the latest observations, is estimated to enable routing decisions based on risk. Chapter 3 sets up the basic decision framework by modeling the dependent structure between the travel time distributions for nearby links using the copula method. In Chapter 4, the framework is generalized to estimate the travel time distribution for a given path using Gaussian copula mixture models (GCMM). To explore the data from fundamental traffic conditions, a scenario-based GCMM is studied. A distribution of the path scenario representing path traffic status is first defined; then, the dependent structure between constructing links in the path is modeled as a Gaussian copula for each path scenario and the scenario-wise path travel time distribution is obtained based on this copula. The final estimates are calculated by integrating the scenario-wise path travel time distributions over the distribution of the path scenario. In a discrete setting, it is a weighted sum of these conditional travel time distributions. Different estimation methods are employed based on whether or not the path scenarios are observable: An explicit two-step maximum likelihood method is used for the GCMM based on observable path scenarios; for GCMM based on unobservable path scenarios, extended Expectation Maximum algorithms are designed to estimate the model parameters, which introduces innovative copula-based machine learning methods.

In part two (Chapter 5), travel time derivatives are introduced as financial derivatives based on road travel times—a non-tradable underlying asset. This is proposed as a more fundamental approach to value pricing. The chapter addresses (a) the motivation for introducing such derivatives (that is, the demand for hedging), (b) the potential market, and (c) the product design and pricing schemes. Pricing schemes are designed based on the travel time data captured by real time sensors, which are modeled as Ornstein-Uhlenbeck processes and more generally, continuous time auto regression moving average (CARMA) models. The risk neutral pricing principle is used to generate the derivative price, with reasonably designed procedures to identify the market value of risk.

Three Attempts at Time Travel is a piece for wind ensemble that is approximately ten minutes in length. It consists of a brief introduction and three continuous movements based on the same starting material. It is semi-programmatic, but it is not an attempt to depict a specific narrative. Rather, it portrays a scenario involving time travel. The concept of the piece begins with a person who uses a time machine to travel back to a certain point in time to change the result of an event in the their own life. During the piece, the person goes back to the same starting point three times with each “restart” resulting in a different outcome. On the final restart, a positive resolution is reached, but it is ultimately a conflicted ending because it is not the ending that the time traveler was aiming for. At the end of the introduction and each of the first two movements, a “time machine” motive consisting of: a Mahler hammer, a concert bass drum, a drum set, a thunder sheet, a suspended cymbal and a triangle occurs to signal the return to the original point in time.

Being able to accurately forecast the time of arrival of a vehicle in traffic appeals both to private drivers aiming to keep up with their schedules, and to businesses that need to organize transport logistics. THis thesis is assigned by the Swedish truck manufacturer Scania CV AB, and sets out to use GPS data from Scania's vehicle fleet to train Machine LEarning models to predict the travel times of vehicles between stops. The predictive models implemented train on features engineered from quite simple information from the vehicles, yet reach high predictive accuracy in certain scenarios. Two approaches to predicting travel time are tested, one referred to as the Local Models approach, and the other as the Global Model approach. In the Local Models approach, many separate regressors are trained on geographical subsets of the datra and then comnbined to give global predictions. In the Global Model approach, a single regressor trains on the entire data set. The Global Model approch gives better performance than that of the Local Models in the experiment, but the Local Models approach shows some promising tendencies. It is found that a regressor predicts significantly more accurately when the geographical spread of the data is limited.
Att ge noggranna förutsager om restider för fordon i trafik är av intresse både för privata förare som försöker hinna med sina scheman, och företag som behöver organiska logistik för transporter. Denna rapport görs på uppdrag av svenska lastbilstillverkaren Scania CV AB, och har som mål att använda GPS-data från Scanias fordon till att träna maskininlärningsmodeller för att förutsäga hur lång tid det tar för fordon att resa mellan stopp. De prediktiva modellerna som implementeras använder variabler som konstrueras från relativt enkel information från fordonen, men lyckas ändå nå hög prediktiv prestanda i vissa scenarion. Två olika ansatser prövas för att förutsäga restider, en ansats med lokala modeller, och en ansats med global modell. I ansatsen med lokala modeller tränas flera separata regressorer på geografiska delmängder av datan, vilka sedan kombineras och ger globala förutsägor. I ansatsen med global modell tränas en enda regressor på hela datamängden. Ansatsen med global modell visar sig ha högre prestanda i experimenten, men ansatsen med lokala modeller förevisar ändå vissa lovande tendenser. Resultaten antyder att en regressor ger mycket noggrannare prediktioner när den geografiska spridningen i datan begränsas.

In the modern industrialized society, a long commuting time is becoming more and more common. However, commuting results in a number of different costs, for example, external costs such as congestion and pollution as well as internal costs such as individual time consumption. On the other hand, increased commuting opportunities offer welfare gains, for example via larger local labor markets. The length of the commute that is acceptable to the workers is determined by the workers' preferences and the compensation opportunities in the labor market. In this thesis the value of travel time or commuting time changes, has been empirically analyzed in four self-contained essays. First, a large set of register data on the Swedish labor market is used to analyze the commuting time changes that follow residential relocations and job relocations. The average commuting time is longer after relocation than before, regardless of the type of relocation. The commuting time change after relocation is found to differ substantially with socio-economic characteristics and these effects also depend on where the distribution of commuting time changes is evaluated. The same data set is used in the second essay to estimate the value of commuting time (VOCT). Here, VOCT is estimated as the trade-off between wage and commuting time, based on the effects wage and commuting time have on the probability of changing jobs. The estimated VOCT is found to be relatively large, in fact about 1.8 times the net wage rate. In the third essay, the VOCT is estimated on a different type of data, namely data from a stated preference survey. Spouses of two-earner households are asked to individually make trade-offs between commuting time and wage. The subjects are making choices both with regard to their own commuting time and wage only, as well as when both their own commuting time and wage and their spouse's commuting time and wage are simultaneously changed. The results show relatively high VOCT compared to other studies. Also, there is a tendency for both spouses to value the commuting time of the wife highest. Finally, the presence of hypothetical bias in a value of time experiment without scheduling constraints is tested. The results show a positive but not significant hypothetical bias. By taking preference certainty into account, positive hypothetical bias is found for the non-certain subjects.

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Road freight transport travel time estimation is an important task in fleet management and traffic planning. Goods often must be delivered in a predefined time window and any deviation may lead to serious consequences. It is possible to improve travel time estimation by considering more factors that may affect it. In this thesis work we identify factors that may affect travel time, find possible sources of information about them, propose a model for estimating travel time of heavy goods vehicles, and verify this model on real data. As results, the experiments showed that considering time related and weather related factors, it is possible to improve accuracy of travel time estimation. Also, it was shown that the influence of a particular factor on travel time depended on the considered road segment. Furthermore, it was shown that different data mining algorithms should be applied for different road segments in order to get the best estimation.

Restider är alltid intressanta, för de som använder vägen och de som är ansvariga för vägen. Det finns olika tekniker för att samla in information om restider, till exempel traditionella videobaserade system och nyare system som använder Bluetooth. Bluetooth är en kostnadseffektiv metod som använder väganvändarnas olika elektroniska enheter, till exempel smartphones eller trådlösa headsets, för att samla in information om restider. Den infrastruktur som behövs för att mäta restid är två stycken Bluetooth-mottagare varav en placeras i början och en i slutet av vägsträckan samt en server som tar emot och analyserar insamlad data. Bluetooth fungerar bra för att samla in information om restider, men är tekniken möjlig att använda för att identifiera restider för specifika transportslag? I det här projektet undersöks möjligheterna att identifiera restider som hör till cyklister i Bluetooth-data från stadstrafik. För att de restider som samlas in ska vara intressanta måste de rensas på så kallade outliers, det vill säga observationer som inte representerar den faktiska restiden på vägsträckan. Projektet undersöker därför ett antal olika filtreringsalgoritmer för att kunna rensa insamlad data från outliers. Filtreringsalgoritmerna jämförs först med varandra för att se vilken eller vilka som fungerar bäst i olika trafikmiljöer. Därefter jämförs filtreringsalgoritmerna med de interna filtreringsalgoritmerna som leverantören av Bluetooth-mottagarna, BLIP Systems, använder i sitt analysverktyg för att erbjuda en helhetslösning. Projektets slutsatser är att Bluetooth fungerar bra som insamlingsteknik för restidsinformation och att de restider som ges inte är signifikant skilda från restider som samlas in med andra, mer traditionella, insamlingstekniker. Det går dock inte att dra några konkreta slutsatser vad gäller möjligheterna att identifiera cyklister i blandad stadstrafik på den vägsträcka som testas i projektet. Detta på grund av att bilar och cyklister har för lika restid på vägsträckan. Metoden som används bör dock testas på ytterligare vägsträckor innan det är möjligt att fastslå om den fungerar eller inte. Av de olika filtreringsalgoritmerna som testas är det en Box och Whisker-algoritm, som använder IQR-teknik för filtreringen, som presterar bäst på indata från stadstrafik och indata från motorväg. Indata från mellanstora vägar tas inte med i resultatet. När Box och Whisker-algoritmen jämförs med Bluetooth-mottagarnas interna filtreringsalgoritmer är resultatet att Bluetooth-mottagarnas filtreringsalgoritmer ger ett något bättre resultat än Box och Whisker-algoritmen, men att den ändå ger ett fullgott resultat.

The implications of travel time uncertainty on the operational efficiency of airport terminals have until now not been examined. With the forecast growth in congestion levels predicted for all modes of transport, not only will travel time uncertainty increase but its impact may increase also. The first part of this thesis covers the analysis of two passenger surveys conducted at Manchester Airport and Birmingham Airport. These surveys had the objective of providing evidence to support or dispute the belief that air travellers react to travel time uncertainty. The research identifies that passengers do react by allowing margins of safety for their access journeys, and that this change in behaviour will modify the arrival distribution patterns at airports. The second part of this thesis examines how airport passenger flows could be altered by a change in the arrival distribution of originating passengers at airport terminals. Three airports - Manchester, Birmingham and East Midlands International - are modelled using a simulation tool and tested to assess how a shift in arrival distribution affects queuing and peak passenger volumes within the airport terminal. The findings of this thesis show that airport passenger terminal operational efficiency is affected by access journey time uncertainty. It also identifies that passenger decision making can only be explained by various combinations of factors. Possible methods of minimising the effects of travel time uncertainty are considered. The advantages and disadvantages of access journey time uncertainty for airports and airlines are discussed. It concludes that, to be successful in overcoming negative aspects, both parties must provide a service that results in customer satisfaction. This is the only sure way to maintain their respective revenue levels and secure their future in what is becoming an increasingly competitive industry.

Estimation of real-time travel times on arterial streets has been a challenging task due to the intersection control delay as well as bottleneck delay from the downstream link. Therefore, few transportation professionals have conducted research at utilizing the dynamic flow methods to estimate travel times on arterial street networks. This thesis is to develop dynamic flow algorithms that estimates the real-time travel time on an arterial street network by utilizing the traffic information obtained from detectors. A modified method to the one adopted in HCM2000 in computing the intersection control delay is developed and utilized to estimate the real-time travel time for a short-time interval update under non-incident and incident situations. Simulation model is developed in CORSIM to validate developed algorithms under different traffic situations.
Master of Science

Emergency services has a vital function in society, and except saving lifes a functioning emergency service system provides the inhabitants of any give society with a sence of feeling secure. Because of the delicate nature of the services provided there is always an interest in improvement with regards to the performance of the system. In order to have a good system there are a variety of models that can be used as decision making support. An important component in many of these models are the travel time of an emergency vehicle. In In this study the focus lies in travel time estimation for the emergency services and how it could be estimated by using a neural network, called a deep learning process in this report. The data used in the report is map matched GPS points that have been collected by the emergency services in two counties in Sweden, Östergötland and Västergötland. The map matched data has then been matched with NVDB, which is the the national road database, adding an extra layer of information, such as roadlink geometry, number of roundabouts etc. To find the most important features to use as input in the developed model a Pearson and Spearman correlation test was performed. Even if these two tests do not capture all possible relations between features they still give an indication of what features that can be included. The deep learning process developed within this study uses route length, average weighted speed limit, resource category, and road width. It is trained with 75% of the data leaving the remaining 25% for testing of the model. The DLP gives a mean absolute error of 51.39 when trained and 59.21 seconds when presented with new data. This in comparison a simpler model which calculates the travel time by dividing the route length with the weighted averag speed limt, which gives a mean absolute error of 227.48 seconds. According to the error metrics used in order to evaluate the models the DLP performs better than the current model. However there is a dimension of complexity with the DLP which makes it sort of a black box where something goes in and out comes an estimated travel time. If the aim is to have a more comprehensive model, then the current model has its benefits over a DLP. However the potential that lies in using a DLP is entruiging, and with a more in depth analysis of features and how to classify these in combination with more data there may be room for developing more complex DLPs.

This dissertation attempts to develop simple and direct approaches to estimate the vehicle queue length and travel time along signalized arterial links for real-time traffic operations. This dissertation is the first to demonstrate a process using vehicle trajectory data to generate detector volume, speed and time occupancy data, along with the generalized flow rate, density and space mean speed data. This approach minimizes detector over-counting and miss-counting issues. The detection zone can be of any shape or size and at any location along the trajectory. The relationships among detector volume, speed and time occupancy along signalized arterials are analyzed theoretically and experientially. If the generalized definitions of flow rate, density and space mean speed are used, the fundamental relationship, v = ds, holds valid in a signalized arterial environment. The fundamental relationship diagram plotted using field signalized arterial data has not been seen in any of the literatures reviewed.

Within the defined time-space region, the scatter diagram of the generalized density and the detector time occupancy presents a strong linear correlation. Simply converting detector volume counts within one data collection time period to use as the generalized flow rate introduces estimation errors. There are two major reasons. The first is that vehicles don’t completely cross the detector during the data collection time period. The second is that it assumes vehicles would evenly spread across the data collection time period when crossing the detection zone. Traffic flow intensity is introduced and defined within the time-space regions to provide much more accurate description of the traffic flow arrival and departure conditions.

This dissertation attempts to make improvements to the input-output technique for queue estimation along signalized links. Based on analyses of the theoretical and experiential cumulative input-output diagrams, also known as the Newell Curves, two major improvements are proposed to improve the performance of the input-output technique. The improvements take into account vehicles stop on top of detectors in the estimation, make necessary adjustments to detector vehicle counts, and introduce a reset mechanism to remove the accumulated estimation errors during a long time period. The improvements are tested using two sets of field data. One set of data are 10-second queue and virtual detector data generated using the Federal Highway Administration Next Generation Simulation Peachtree Street dataset. The other set of data are field manually collected 20-second queue, and loop detector vehicle count and time occupancy data at metered on-ramps. It is concluded that both improvements help to produce estimation results far better than the original input-output technique. With adjusted detector vehicle counts, the performance of the Kalman Filter queue estimation model is also improved.

A simple conservation law approach is developed to estimate travel time along signalized arterial links. Inputs used include the traffic flow intensity at input and out detectors, plus the initial vehicle queue. The estimated travel time is tested with the field travel time data to evaluate the performance of the estimation. The developed model is also compared with the NCHRP Project 3-79 model and the Little’s Law queueing theory model. The developed model performs much better for per short interval travel time estimation.

The proposed travel time estimation approach only uses the detector volume and time occupancy data. It does not rely on signal timing data to estimate the control delay or a delay model to estimate the queueing delay. In addition, neither roadway geometry nor vehicle length data are used.

This focuses on hydrological transport in shallow catchments with topography-driven flow paths. The thesis gives new insight to kinematic pathway models for estimation of tracer discharge at the catchment outlet. A semi-analytical methodology is presented for transient travel time and age distributions referred to as "kinematic pathway approach“(KPA) that accounts for dispersion at two levels of morphological and macro-dispersion. Macro-dispersion and morphological dispersion components are reflected in KPA by assuming an effective Péclet number and topographically driven pathway length distributions, respectively. The kinematic measure of the transport, defined as a characteristic velocity of water flow through the catchment is obtained from the overall water balance in the catchment. To include transformation process in its simplest form of linear decay/degradation a framework is presented that solves one-dimensional reactive transport with numerically simulated travel times as the independent variable. The proposed KPA and coupled transport framework for quantifying tracer discharge at the shallow catchment outlet are applied to two selected catchments in Sweden. KPA is applied to modeling of a 23-year long chloride data series for the Kringlan catchment whereas the implantation of the framework for quantifying natural attenuation is illustrated for the Forsmark catchment. Numerical simulations of Forsmark catchment advective travel times are obtained by means of particle tracking using the fully-integrated flow model MIKE SHE. The KPA is found to provide reasonable estimates of tracer discharge distribution when considering the transport controlled by hillslope processes associated with short topographically driven flow paths to adjacent discharge zones, e.g. rivers and lakes. Simulated natural attenuation for Forsmark is also estimated well provided that the pathway length distribution is skewed toward short pathway lengths. This fact is indicative of the controlling impact of topography on flow path length and travel time distributions in shallow catchments. Our work has shown that the pathway (Lagrangian) methodologies are promising as predictive tools for hydrological transport.

QC 20170928

La informació sobre el temps de viatge és l'indicador clau en el funcionament operatiu d’una autopista i un dels inputs més apreciats pels seus usuaris. Tot i això, no ha estat fins molt darrerament que els operadors d'autopistes han començat a analitzar el trànsit de la carretera amb l’objectiu de proporcionar informació acurada sobre el temps de viatge. També recentment, les administracions titulars de les autopistes han començat a demanar que es proporcioni tal informació com a mesura del servei d'accessibilitat proporcionat per la carretera, en termes de qualitat i fiabilitat. Durant el segle passat, els detectors d’espira magnètica jugaven un paper primordial en la monitorització del trànsit al proporcionar informació sobre el volum de trànsit i també sobre la velocitat i longitud mitjanes dels vehicles, encara que generalment amb menys precisió en aquests dos darrers casos. En les darreres dècades han aparegut noves tecnologies de control de trànsit (càmeres intel•ligents, seguiment mitjançant GPS o telèfon mòbil, identificació de dispositius bluetooth, nous detectors MeMS, etc.) que permeten millorar considerablement la recollida de dades sobre el temps de viatge. Algunes d’aquestes tecnologies són barates (bluetooth), d’altres no ho són (càmeres); però en qualsevol cas la major part de la xarxa d’autopistes encara està controlada per detectors d’espira magnètica. Té sentit doncs, emprar la seva informació bàsica i enriquir-la, quan calgui, amb noves fonts de dades. Aquesta tesi presenta una metodologia nova i simple per a la previsió a curt termini del temps de viatge en autopistes de peatge basada en la fusió de dades provinents de detectors d’espira magnètica i de tiquets de peatge. La metodologia és genèrica i no és tecnològicament captiva: es podria generalitzar fàcilment a uns altres tipus de dades. L'anàlisi Bayesià permet obtenir dades fusionades que són més fiables que les dades d’entrada originals, superant alguns problemes habituals en l’estimació del temps de viatge a partir de fonts úniques d’informació. La metodologia desenvolupada aporta valor afegit a les dades actuals (detectors d’espira i tiquets de peatge) en autopistes de peatge tancat, i aprofita al màxim (en termes d'estimació del temps de viatge) les dades disponibles, sense caure en la demanda recurrent i costosa d’una major necessitat de dades. L'aplicació dels algoritmes a l’autopista de peatge AP-7 als voltants de Barcelona demostra empíricament la tesi: és possible desenvolupar un sistema acurat d'informació de temps de viatge, en temps real, en autopistes de peatge tancat amb la monitorització existent. Per això, d'ara en endavant els operadors d'autopistes podran oferir aquest valor afegit als seus clients sense gairebé cap inversió extra.
Travel time information is the key indicator of highway management performance and one of the most appreciated inputs for highway users. Despite this relevance, the interest of highway operators in providing approximate travel time information is quite recent. Besides, highway administrations have also recently begun to request such information as a means to measure the accessibility service provided by the road, in terms of quality and reliability. In the last century, magnetic loop detectors played a role in providing traffic volume information and also, with less accuracy, information on average speed and vehicle length. New traffic monitoring technologies (intelligent cameras, GPS or cell phone tracking, Bluetooth identification, new MeMS detectors, etc.) have appeared in recent decades which permit considerable improvement in travel time data gathering. Some of the new technologies are cheap (Bluetooth), others are not (cameras); but in any case most of the main highways are still monitored by magnetic loop detectors. It makes sense to use their basic information and enrich it, when needed, with new data sources. This thesis presents a new and simple approach for the short term prediction of toll highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and it is not technologically captive: it could be easily generalized to other equivalent types of data. Bayesian analysis makes it possible to obtain fused estimates that are more reliable than the original inputs, overcoming some drawbacks of travel time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) of the available data, without falling in the recurrent and costly request of additional data needs. The application of the algorithms to empirical testing in AP-7 toll highway in Barcelona proves our thesis that it is possible to develop an accurate real-time travel time information system on closed toll highways with the existing surveillance equipment. Therefore, from now on highway operators can give this added value to their customers at almost no extra investment. Finally, research extensions are suggested, and some of the proposed lines are currently under development.

In the research area of travel time prediction, the existing studies mainly focus on aggregated travel time prediction (without distinguishing vehicle types) or travel time prediction for passenger vehicles. The travel time prediction for freight transportation has not received enough attention from researchers. Only a few relevant studies can be found in the literature, and the proposed methods are usually very simple and lack comparisons with more advanced methods. Although many believed that a better prediction model can be developed using more advanced techniques such as artificial neural networks or autoregressive conditional heteroscedastic models, it is usually difficult and costly to train these models and the model interpretability is poor. There is a demand for `off-the-shelf' methods with good performance, ease of implementation and good model interpretability. Thus, the aims of this thesis are: (1) developing some `off-the-shelf' data-driven methods to predict travel time for freight transportation; (2) creating a comprehensive understanding of how the developed methods can be more effectively applied for general travel time prediction problems. Its two main contributions are: (1) it develops data-driven travel time prediction methods for freight transportation by utilising freight vehicles' trajectory data; (2) it investigates the relation between features and performance and discovers the combinatorial effects of features under the effects of different noise processes and different model fitting strategies. The experimental results show that useful features can be mined from the trajectory data to enhance the travel time prediction for freight transportation. The developed methods outperform some of the state-of-the-art data-driven methods.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 147-154).
Uncertainty in travel time is one of the key factors that could allow us to understand and manage congestion in transportation networks. Models that incorporate uncertainty in travel time need to specify two mechanisms: the mechanism through which travel time uncertainty is generated and the mechanism through which travel time uncertainty influences users' behavior. Existing traffic equilibrium models are not sufficient in capturing these two mechanisms in an integrated way. This thesis proposes a new stochastic traffic equilibrium model that incorporates travel time uncertainty in an integrated manner. We focus on how uncertainty in travel time induces uncertainty in the traffic flow and vice versa. Travelers independently make probabilistic path choice decisions, inducing stochastic traffic flows in the network, which in turn result in uncertain travel times. Our model, based on the distribution of the travel time, uses the mean-variance approach in order to evaluate travelers' travel times and subsequently induce a stochastic traffic equilibrium flow pattern. In this thesis, we also examine when the new model we present has a solution as well as when the solution is unique. We discuss algorithms for solving this new model, and compare the model with existing traffic equilibrium models in the literature. We find that existing models tend to overestimate traffic flows on links with high travel time variance-to-mean ratios. To benchmark the various traffic network equilibrium models in the literature relative to the model we introduce, we investigate the total system cost, namely the total travel time in the network, for all these models. We prove three bounds that allow us to compare the system cost for the new model relative to existing models. We discuss the tightness of these bounds but also test them through numerical experimentation on test networks.
by Daizhuo Chen.
S.M.

The sprawl of U.S. cities has attracted criticism from many sources in recent years. Among the greatest of the cited harms of sprawl is the alleged travel time burden that it imposes on its residents. Previous research has tested the relationship between the sprawl of business activity and travel times by examining only its effects on commuting times and has concluded that people do not choosing housing and work locations to minimize commutes. This research takes a more comprehensive approach by analyzing the relationship between household travel times and sprawl by testing the relationship between access to economic centers and daily household travel time. The relatively minor increase in household travel times with decrease in access to economic centers found by the analysis shows that people logically reduce trips to centers when choosing housing locations with less access to centers. The ability of people to make these reductions in travel is clearly increased by the dispersal of activity from the central business district and other centers. Comparison of predicted household travel times with an estimated rent gradient show that the increase in housing prices with improved access to subcenters is far less than would be expected given the predicted household travel times, contradicting the relationship between household travel time and housing prices embodied in central place theory and its limited polycentric extensions. An analysis of joined trips suggests that households with less access to economic centers used joined trips, in which multiple destinations are visited on a single trip from the home, to reduce household travel. All of the results suggest that auto use enables households throughout the metropolitan area to reduce travel time. The car has greater flexibility and speed than other modes, particularly in areas of lower density. The travel time savings and flexibility that are provided by the dispersal of economic activity have allowed people to choosing housing that they prefer at lower prices with little added transportation cost. Given these benefits we should carefully consider the manner and method we choose to reduce any negative externalities of sprawl and auto use.
Ph. D.

This research aims to explore the cause of stability in travel-time expenditures for an individual, which is seen to be invariant within the context of geographic location and time, and which is commonly known as the ‘travel-time budget’. The concept of biological energy expenditure on travelling is introduced in this research as a possible means to explain why travel-time expenditures have shown stability for a long time. The stochastic frontier modelling framework is used to estimate the ‘travel-energy budget’, which is seen as a controlling mechanism for travel-time expenditure. This research thus uncovers a very fundamental aspect from human physical considerations that has considerable implications in transport policy and practice. Even though understanding the similarity and variability of individual travel behaviour, particularly time use in travelling, has been considered one of the key issues in travel behaviour research for over four decades, limited availability of longitudinal data has restricted the analysis from deeper insights. Most of the past data in transport research come from self-reporting mechanisms. These self-report methods are fraught with error along with other problems. In contrast, GPS travel data has been regarded as more accurate, comprehensive, and complete in nature. This study aims to undertake a highly disaggregate analysis of travel-energy expenditures using multi-day and multi-year GPS data, which has never been studied in this way in the past. The greatest strength of this thesis clearly lies in its empirical contribution to address and explore new insights on travel behaviour and travel-time and travel-energy expenditures through the use of a novel multi-day, multi-period panel GPS data set. It contributes to the transport literature in theoretical and empirical aspects and the existence of stable travel-energy budgets. It also opens a new window of rethinking and making major changes in policy directions for transport.

The reliability of bus systems is a vital issue on the transport agenda, since urban areas are yearning for high quality alternatives for the private car. A key indicator of reliability is a low level of day-to-day travel time variability (TTV). To obtain funds for reducing TTV, it is necessary to give evidence for the benefits from such improvement, but current tools for estimating the cost of TTV are insufficient. This thesis covers issues that arise when analysts need to show that improved bus infrastructure brings benefits from reduced TTV. The first part of the thesis aims at understanding how the attitudes of travellers to TTV can be converted into monetary terms. The design of a survey is described, where respondents trade-off between TTV and other attributes. A modelling experiment, based on the survey responses, finds that the effect of TTV is best explained using variables that represent trip scheduling considerations. Following is a series of experiments that seek to estimate the willingness-to-pay for reduced TTV in a way that is sensitive to taste variation between travellers. Several Mixed Logit models are estimated, but some doubts about their credibility are raised, and hence the same willingness-to-pay estimates are also computed using nonparametric techniques. Some conclusions are drawn regarding the process of estimating heterogeneous willingness-to-pay and the ability to recognise the willingness-to-pay from survey data. The starting point for the second part of the thesis is the lack of tools for estimating the level of TTV in hypothetical scenarios. We, consider the case for using traffic microsimulation to estimate TTV by running a microsimulation model multiple times, and looking at the variation between runs as an estimate of the variation between different days. Such concept of estimation requires a special calibration methodology, which sets the level of simulated inter-run variability at a similar level to inter-day variability in the real network. A full calibration methodology is developed, tackling methodological, computational and statistical issues. Finally, the demand and supply methodologies are combined, and it is illustrated how the savings from improved bus infrastructure can be examined. The contribution of the entire study includes methodological and technical insights into modelling the attitudes to TTV, estimating the distribution of the willingness-to-pay and calibrating traffic microsimulation models; but it also brings up policy issues concerning the role of TTV in transport appraisal.

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 89-94).
The benefits of bus automatic vehicle location (AVL) data are well documented (see e.g., Furth et al. (2006)), ranging from passenger-facing applications that predict bus arrival times to service-provider-facing applications that monitor network performance and diagnose performance failures. However, most other researchers' analyses tend to use data that they acquired through negotiations with transit agencies, adding a variable cost of time both to the transit agencies and to researchers. Further, conventional wisdom is that simple vehicle location trajectories are not suitable for evaluating bus performance (Furth et al. 2006). In this research, I use data that are free and open to the public. This access enables researchers and the general public to explore bus position traces. The research objective of this Master's Thesis is to build a computational system that can robustly evaluate bus performance across a wide range of bus systems under the hypothesis that a comparative approach could be fruitful for both retrospective and real-time analysis. This research is possible because a large number of bus providers have made their bus position, or AVL, data openly available. This research thus demonstrates the value of open AVL data, brings understanding to the limits of AVL data, evaluates bus performance using open data, and presents novel techniques for understanding variations in bus travel time. Specifically, this thesis demonstrates research to make the system architecture robust and fruitful: " This thesis explores the exceptions in the various datasets to which the system must be robust. As academics and general public look to exploit these data, this research seeks to elucidate important considerations for and limitations of the data. " Bus data are high-dimensional; this research strives to make them dually digestible and informative when drawing conclusions across a long timescale. Thus, this research both lays the foundation for a broader research program and finds more visually striking and fundamentally valuable statistics for understanding variability in bus travel times.
by David G. Gerstle.
S.M.in Transportation

This thesis presents an investigation of arterial travel time and reliability. Specifically an examination of the proposed arterial travel time reliability performance measures detailed in Federal Highway Administration’s Notice of Proposed Rulemaking on national performance management measures are performed. These measures, including level of travel time reliability and peak hour travel time ratio, are computed and compared to those currently used to quantify congestion and travel time reliability. Within this process several commonly used data sources are evaluated to determine the effects of data quality and data source on performance measure evaluation. The newly created Urban Streets Reliability tool is also evaluated for its ability to estimate the effect of several proposed projects on the travel time reliability of a transportation network. In conclusion, this thesis found that the proposed travel time reliability performance measures show definite differences in estimates of facility reliability as compared with currently used performance measures such as travel time index and planning time index. A variation in the magnitude of this difference was also observed based on a rural vs. urban roadway setting. Finally, further areas of research involving the use of the Urban Streets Reliability tool to estimate the impact of reliability improvements on side streets and the transportation network as a whole are discussed.

The empty railcars repositioning strategy generates no income but is crucial for a good service quality, it should then satisfy two main objectives: fullling the customer demand and generating as little expense as possible. Moreover, because of breakdown or heavy traffic, variation on travel times happens to be the main cause of uncertainty in railroad scheduling and must be taken into account to suggest a robust planning.

This thesis presents the linear program used in a prototype tool for the optimization of empty railcar repositioning strategy designed for the SNCF1. The resulting schedule is computed with CPLEX and minimizes moving cost, delay and unfulllment penalties. Substitutions of railcar categories are also permitted and eventually penalized. In addition, uncertainty on travel times is handled by considering the expected cost of a move (regarding delay probability and possible penalties) and by adding slack periods at the end of moves. The robustness can be modulated through the use of a cursor. Finally, the model enforces a decision making process previously dened by the SNCF to ensure that the suggested planning can be easily grasped and trusted by users.

Schedules have then been generated based on randomly generated data and simulated. Results show a potential saves of 10% on considered costs and a good range of use of the robustness cursor is suggested.

Finally, paths for improvement of this prototype are proposed to meet the eventual schedulers' further needs in order to move forward the production of this tool at the company scale.
Master of Science

The purpose of this research is to solve several important problems of the AVI system, including the AVI site location problem, travel time forecasting, the study of reliability and accuracy of the forecasted travel time. This thesis serves as a further research toward the modeling of AVI systems in which the effects of AVI site location, AVI site density, travel time forecasting are analyzed. The model based on the genetic algorithms was applied to AVI site location problem to solve it as a multi-objective optimization problem, thus the best locations was determined on the basis of several criteria. The model developed was tested in an assumed transportation network. The achieved CPU time in this stage of the research are promising. MATLAB and its accompanying Neural Network Toolbox, has been applied to data obtained from San Antonio real time AVI Tag database to forecast travel time. The approach to the neural network is detailed in this paper. Two ANN models were tested in this research. The accuracy of AVI travel time forecasting was then assessed and the better model for travel time forecasting was found. Lastly, a comparison of forecasted travel time with different travel time prediction technologies was performed to serve as a reference parameter for the travel time forecasting study.
Master of Science

Travel time reliability is deemed as one of the most important factors affecting travelers’ route choice decisions. However, existing practices mostly consider average travel time only. This dissertation establishes a methodology framework to overcome such limitation. Semi-standard deviation is first proposed as the measure of reliability to quantify the risk under uncertain conditions on the network. This measure only accounts for travel times that exceed certain pre-specified benchmark, which offers a better behavioral interpretation and theoretical foundation than some currently used measures such as standard deviation and the probability of on-time arrival. Two path finding models are then developed by integrating both average travel time and semi-standard deviation. The single objective model tries to minimize the weighted sum of average travel time and semi-standard deviation, while the multi-objective model treats them as separate objectives and seeks to minimize them simultaneously. The multi-objective formulation is preferred to the single objective model, because it eliminates the need for prior knowledge of reliability ratios. It offers an additional benefit of providing multiple attractive paths for traveler’s further decision making. The sampling based approach using archived travel time data is applied to derive the path semi-standard deviation. The approach provides a nice workaround to the problem that there is no exact solution to analytically derive the measure. Through this process, the correlation structure can be implicitly accounted for while simultaneously avoiding the complicated link travel time distribution fitting and convolution process. Furthermore, the metaheuristic algorithm and stochastic dominance based approach are adapted to solve the proposed models. Both approaches address the issue where classical shortest path algorithms are not applicable due to non-additive semi-standard deviation. However, the stochastic dominance based approach is preferred because it is more computationally efficient and can always find the true optimal paths. In addition to semi-standard deviation, on-time arrival probability and scheduling delay measures are also investigated. Although these three measures share similar mathematical structures, they exhibit different behaviors in response to large deviations from the pre-specified travel time benchmark. Theoretical connections between these measures and the first three stochastic dominance rules are also established. This enables us to incorporate on-time arrival probability and scheduling delay measures into the methodology framework as well.

The importance of travel time estimation has increased due to the central role it plays in a number of emerging intelligent transport systems and services including Advanced Traveller Information Systems (ATIS), Urban Traffic Control (UTC), Dynamic Route Guidance (DRG), Active Traffic Management (ATM), and network performance monitoring. Along with the emerging of new sensor technologies, the much greater volumes of near real time data provided by these new sensor systems create opportunities for significant improvement in travel time estimation. Data fusion as a recent technique leads to a promising solution to this problem. This thesis presents the development and testing of new methods of multi-sensor data fusion for the accurate, reliable and robust estimation of travel time. This thesis reviews the state-of-art data fusion approaches and its application in transport domain, and discusses both of opportunities and challenging of applying data fusion into travel time estimation in a heterogeneous real time data environment. For a particular England highway scenario where ILDs and ANPR data are largely available, a simple but practical fusion method is proposed to estimate the travel time based on a novel relationship between space-mean-speed and time-mean-speed. In developing a general fusion framework which is able to fuse ILDs, GPS and ANPR data, the Kalman filter is identified as the most appropriate fundamental fusion technique upon which to construct the required framework. This is based both on the ability of the Kalman filter to flexibly accommodate well-established traffic flow models which describe the internal physical relation between the observed variables and objective estimates and on its ability to integrate and propagate in a consistent fashion the uncertainty associated with different data sources. Although the standard linear Kalman filter has been used for multi-sensor travel time estimation in the previous research, the novelty of this research is to develop a nonlinear Kalman filter (EKF and UKF) fusion framework which improves the estimation performance over those methods based on the linear Kalman filter. This proposed framework is validated by both of simulation and real-world scenarios, and is demonstrated the effectiveness of estimating travel time by fusing multi-sensor sources.

This licentiate thesis consists of an introduction (‘kappa’) and three papers discussing various aspects of time as a commodity and the practice of valuing travel time. The first paper is an analysis of the properties of time as an economic resource taking into account literature on behavior with regard to time. The intent is to provide better understanding of the underlying assumption of transferability between time and money in the context of transportation. The second paper builds on the analysis in the first paper combined with the findings of a study of commuters travel experiences during disruptions in the train traffic on the Øresund strait between Sweden and Denmark. It contrasts the theoretical account of value of travel time with the experiences reported by commuters and argues that the view of travel time as strictly a disutility can be limiting from a planning perspective. Instead, it is argued that an alternative approach can be to make travel time ‘plannable’, meaning viewing travel time as time travellers can plan to spend in a certain way at a certain time. The third paper argues that the diversity of possible mobility solutions based on self-driving vehicles has been somewhat overlooked in the current literature on value of travel time. Thus, the complexity of valuing travel time for self-driving vehicles has not been fully addressed. The paper consists of a morphological analysis of the parameters that might impact value of travel time for self-driving vehicles and a deeper analysis of five plausible self-driving vehicle mobility concepts. It is claimed that not all such concepts can be easily mapped into transport modes and that it might be more appropriate to differentiate value of travel based on travel characteristics.
Denna licentiatavhandling består av en introduktion och treartiklar som på olika sätt berör värdering av restid. Vare sigvi vill det eller inte är vår vardag driven av och bunden av tid.Vi planerar vår tid, spenderar vår tid och stressar när tideninte räcker till. Det vi önskar, vill och måste göra tar tid; tidenvillkorar helt enkelt mycket i våra liv. Om det är så att vi villförflytta oss från en fysisk plats till en annan, kanske mellanhem och jobb eller skola, tar det tid. Den här specifika tiden,restiden, antas behövas på grund av behovet av att jobba, fikaeller handla, inte genom en önskan om att resa i sig (även omdet självklart finns resor vi gör för nöjes skull, där nöjet är självaresan). I och med att resan (och restiden) är nödvändig men intei sig önskvärd är det ett grundläggande antagande inom fältetför transportekonomi att människor vill minimera sin restid i såstor utsträckning som möjligt. Det är det här antagandet sommycket av planeringen och investeringarna i transporter grundarsig på. Genom att undersöka betalningsvilja hos resenärer kanman sätta ett monetärt värde på potentiellt insparad restid: tidblir pengar. Men är det verkligen så enkelt? Till att börja medär tid och pengar de facto inte samma sak. Vi kan inte sparatid på samma sätt som pengar utan sparad tid måste användasomedelbart. Det blir därmed rimligt att anta att vad man gör medden insparade tiden spelar roll eftersom tiden känns mer värd omden kan spenderas på något meningsfullt. Vad man har möjlighetatt göra beror ofta på sammanhanget och upplevs därför mindreflexibelt än när det gäller insparade pengar.Denna avhandling resonerar vidare kring frågor om förhållandetmellan tid och pengar, i synnerhet den vanligt förekommandeoch generellt accepterade monetära värderingen av restid. Tillviss del problematiserar avhandlingen antagandet att tid är pengar och frågar sig om inte för mycket fokus läggs på tidskvantitetframför tidskvalitet och att kan det vara värdefullt att reflekterakring vilka transportinvesteringar som detta gynnar. Syftet äratt undersöka om de vedertagna transportekonomiska modellersom tillämpas idag speglar sådant vi som samhälle värdesätteroch lyfta aspekter som möjligen förbises.Introduktionen till avhandlingen består av en metodologiskdiskussion kring filosofins roll i tvärvetenskapliga projekt, enöversiktlig teoretisk bakgrund till begrepp såsom rationalitetoch välfärdsekonomi och en genomgång av teman som på etteller annat sätt berör värdering av tid. Därefter sammanfattasartiklarna och introduktionen avslutas med slutsatser och ettavsnitt om möjliga framtida forskningsämnen.Den första artikeln i den här avhandlingen handlar om hurförhållandet mellan tid och pengar kan bättre förstås genom attutgå från tiden som det primära att värdesätta. Denna analysoch de insikter som analysen leder till kan därefter förklara ochbättre underbygga antaganden som görs vid modellering av beslutrörande tid. I artikeln analyseras egenskaper av tid i relation tillpengar som framkommit i beteendevetenskaplig och psykologiskforskning. I transportekonomi, likt traditionell mikroekonomi,utgår man från ett antagande om stabila rationella preferenser hosindivider. Givet skillnader mellan hur individer verkar resonerakring tid jämfört med pengar kan man dock ställa sig frågan omdet skulle kunna vara annorlunda att vara rationell med avseendepå tid jämfört med att vara rationell med avseende på pengar. Isynnerhet då det finns egenskaper hos tid som är så pass specifikaatt motsvarande egenskaper inte finns hos andra typer av objekteller varor. Sammantaget hävdar vi att det enkla förhållandetmellan tid och pengar inte är tillräckligt rättfärdigat i ljuset av defaktiska skillnaderna mellan tid och pengar som verkar föreligga.Den andra artikeln i avhandlingen rör upplevelser av restid ochförhållandet mellan upplevelsen och de teoretiska antagandenasom görs i transportekonomi. I artikeln analyserar vi upplevelser av restid hos resenärer som påverkades av det plötsliga införandetav identitetskontroller vid resor mellan Sverige och Danmark 2015.Mot bakgrund av en studie där upplevelserna dokumenteradesvisar vi på aspekter av restid som upplevs men inte speglas i vedertagnatransportekonomiska modeller. Artikeln delar upp dessaaspekter i tre kategorier: (i) aspekter rörande den faktiska restatiden och upplevelser av själva resan, (ii) kortsiktiga anpassningartill rådande omständigheter och (iii) långsiktiga anpassningar tillrådande omständigheter. Vi menar att restiden behöver sättasi ett vidare perspektiv genom att se resan och restiden i ettsammanhang där planering av vardagen är en förutsättning föratt få livet att gå ihop. Ett möjligt sådant perspektiv är att urplaneringssynpunkt sträva efter att göra tiden så ‘planerbar’ sommöjligt, alltså att underlätta individers långsiktiga och kortsiktigaplanering av både restid och resor, istället för att enkom serestid som onytta.I tredje artikeln tillämpas till viss del insikter om vad som skiljertid från pengar och dessa appliceras på värdering av restid försjälvkörande fordon. Värdet av restid beror traditionellt (blandannat) på transportmedel, det vill säga om resan görs med bil,buss eller tåg. Självkörande bilar har i litteraturen setts som ytterligareresslag, ofta en ny sorts bil. Vi menar dock att självkörandefordon kan mynna ut i många olika typer av transportmedel därvissa kommer att likna de vi har idag medan andra kommer attvara nya sett till resegenskaper. Givet att dessa egenskaper är relateradetill aspekter som påverkar resenärers värdering av restidkommer tiden alltså vara olika mycket värd. Värdering av restidför självkörande fordon bli därför mer komplext än att lägga tillett eller ens några ytterligare transportmedel. För att belysa dettagör vi i artikeln en så kallad morfologisk analys där vi spännerupp ett lösningsfält vi menar täcker in aspekter som påverkarvärderingen av restid för självkörande fordon. Sedan analyserarvi möjliga (och troliga) lösningar, där varje lösning motsvararett möjligt transportmedel, och menar att restidsvärdet för dessa lösningar rimligen bör skilja sig åt. Det leder oss till att föreslåatt ett alternativt sätt att segmentera restidsvärde skulle kunnavara att utgå från resegenskaper, snarare än transportmedel somsådana. Sådana resegenskaper skulle kunna vara privat/deladresa eller om resan sker efter tidtabell eller är “on-demand“.Sammanfattningsvis menar jag att monetär värdering av tidkan ses från tre perspektiv: (i) det linjära förhållandet mellan tidoch pengar som sådant, (ii) aggregeringen av individers insparaderestid till faktisk samhällsnytta och (iii) restidsförkortningarsplats i kostnadsnyttoanalys och transportplanering i allmänhet.Transportinvesteringar görs på lång sikt och de samhällsekonomiskakalkyler som ligger till grund för dessa investeringar behöverdärmed spegla både vårt förhållande till tid idag men även hur vikommer att förhålla oss till tiden i framtiden. Rimligen kommervi då ha lika mycket tid som idag, men kommer vårt förhållandetill tid vara detsamma?Slutligen föreslår jag i avhandlingen möjliga framtida temanatt undersöka vidare, såsom transporträttvisa, aggregering avväldigt små restidsvinster och förhållandet mellan risker ochtidsvinster.

QC 20200819

This project recognized lack of data analysis and travel time prediction on arterials as the main gap in the current literature. For this purpose it first investigated reliability of data gathered by Bluetooth technology as a new cost effective method for data collection on arterial roads. Then by considering the similarity among varieties of daily travel time on different arterial routes, created a SARIMA model to predict future travel time values. Based on this research outcome, the created model can be applied for online short term travel time prediction in future.

This thesis seeks to provide guidance on the deployment of Bluetooth sensors for travel time measurement in work zone corridors. The investigation focuses on the detection characteristics of Class 1 and Class 2 Bluetooth devices, and how cultivating an understanding of these characteristics together with the effect of the sensor inquiry cycle length can suggest a more precise method of travel time measurement. This thesis also explores the range of detection location around a Bluetooth sensor in order to recommend a minimum corridor separation of Bluetooth sensors, and to ascertain the best method of Bluetooth travel time derivation. Finally, this thesis investigates these principles further through multiple side-fire deployments on the I-285 corridor in Atlanta, Georgia; as well as two deployments capturing several hours of active work zone travel time.

Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Hunter, Michael; Committee Member: Guensler, Randall; Committee Member: Leonard, John; Committee Member: Rodgers, Michael; Committee Member: Roshan J. Vengazhiyil. Part of the SMARTech Electronic Thesis and Dissertation Collection.

This thesis focuses on interactive and computational semantics for manipulating the time-based medium of an evolving information space. The interactive semantics enable the user to engage in linear timeline traversal and non-linear history manipulation. Extended tape recorder metaphor controls, including jog-shuttle based navigation, provide the user with flexible means for operating the software's generative functionalities, and linearly traversing session history. The user can see previews of information space states while traversing the history using the jog-shuttle. We also introduce a door-latch metaphor that enables one of several considered forms of nonlinear history manipulation. Users can change history by retroactively latching an information sample in its position across time. For representing the information space history, we have developed MPEG-like computational keyframe semantics. This representation is in the form of XML, which is generated automatically and converted back to Java by a framework named ecologylab.xml, which was developed as a part of this thesis. These computational keyframe semantics serve as the basis for interaction semantics. A user study was conducted in the form of a design competition, to evaluate these new features. The results indicated that the users do find the time travel features useful and they feel more in-control of the information space with access to time travel features compared to the case when time travel features are not present.

This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.

This thesis concerns the prediction of travel times between two points on a map, based on a combination of link-scale road network data and historical trip-scale data. The main idea is that the predictions using the road network data can be improved by a correction factor estimated from historical trip data. The correction factor is estimated both using a Machine Learning approach, more specifically Gaussian Progress Regression, and a simple baseline method inspired by an approach in the literature. The Gaussian Progress Regression is performed using a string kernel and a squared exponential kernel. The Gaussian Process Regression using the string kernel outperforms both the baseline and the squared exponential kernel, and is hence the most promising approach on the considered problem.
Denna rapport behandlar uppskattningar av restider mellan två punkter på en karta, utifrån en kombination data från vägnät (på en skala av vägsegment) och historisk data från utförda resor (på en större skala, som resorna). Huvudidén är att uppskattningarna kan förbättras genom att införa en korrigeringsfaktor som uppskattas utifrån den historiska resdatan. Korrigeringsfaktorn uppskattas både genom maskininlägningsmetoder, mer specifikt med regression baserad på Gaussianska processer, och med en enkel referensmetod inspirerad av en metod i litteraturen. Två olika kärnfunktioner används vid den Gaussinaska regressionen: en kvadratiskt exponentiellt kärna och en strängkärna. Den metod som använder strängkärnan är den mest lovande metoden i denna studie, då den presterar bättre än de båda andra.

This thesis consists of two main chapters along with an introduction andconclusion. In the introduction, we address the inspiration for the thesis, whichoriginates in a common calculus problem wherein travel time is minimized across two media separated by a single, straight boundary line. We then discuss the correlation of this problem with physics via Snells Law. The first core chapter takes this idea and develops it to include the concept of two media with a circular border. To make the problem easier to discuss, we talk about it in terms of running and swimming speeds. We first address the case where the starting and ending points for the passage are both on the boundary. We find the possible optimal paths, and also determine the conditions under which we travel along each path. Next we move the starting point to a location outside the boundary. While we are not able to determine the exact optimal path, we do arrive at some conclusions about what does not constitute the optimal path. In the second chapter, we alter this problem to address a rectangular enclosed boundary, which we refer to as a swimming pool. The variations in this scenario prove complex enough that we focus on the case where both starting and ending points are on the boundary. We start by considering starting and ending points on adjacent sides of the rectangle. We identify three possibilities for the fastest path, and are able to identify the conditions that will make each path optimal. We then address the case where the points are on opposite sides of the pool. We identify the possible paths for a minimum time and once again ascertain the conditions that make each path optimal. We conclude by briefly designating some other scenarios that we began to investigate, but were not able to explore in depth. They promise insightful results, and we hope to be able to address them in the future.

Value of Travel Time Savings (VTTS) is probably the most important benefit in transportation investment projects. Nevertheless, knowledge about VTTS for cyclists is sparse. In a time of change to a more climate-friendly, urban transport system more knowledge of the topic is highly demanded. By utilizing a mixed logit model, this study estimate that the average VTTS for a Norwegian cyclist is higher than previously measured. Applying the average VTTS-value in national cost benefit analysis would make time-saving infrastructure and facilities for cyclists more profitable. By parameterizing the coefficients for time and cost, the study also find that income and variables related to reasons to cycle have large impacts on individual VTTS for cyclists.

There is lack of knowledge on how well the transport projects work once implemented. This research project seeks to investigate how the forecasted benefits claimed during the economic appraisal of the projects compare with the actual benefits realised. This study carried out a literature review on how the travel time benefits are forecasted for transport investment projects and comments on general to specific issues like value of travel time, international and local experiences of forecasting travel time savings to use of traffic modelling in forecasting travel time savings. The study also carried out a post-construction evaluation of projects on a diverse range of transport projects from realignments, grade separated interchange to the installation of HOV lanes and urban bypass project. Post-construction analysis was carried out and then compared against those assumed for the pre-construction evaluation and possible reasons for the differences were discussed.

The current traffic situation in Stockholm with heavy traffic and congested roads makes accurate travel time estimation both difficult and important for several different types of businesses. In this thesis a method of estimating travel time based on historical GPS data from taxi vehicles is presented. One of the major problems faced is to match the reported GPS location to a position in the actual road network. The proposed probabilistic method for finding the most likely position includes two features, the travel time of the vehicle and distance of the GPS error. The historical GPS data is analyzed in order to create a database with historical traffic patterns; average velocities for different roads at different times are logged. To create and estimation the route is estimated using the path finding algorithm A* and the expected traffic patterns are found from the historical data. When comparing the travel time estimation to known travel times, the method display promising results with a mean average percentage error of 16.8%.

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTITUIÇÕES COMUNITÁRIAS DE ENSINO PARTICULARES
A presente tese analisa as representações de viagens no tempo em um conjunto de produções da indústria cinematográfica dos Estados Unidos. O objetivo do estudo é compreender as concepções sobre o tempo elaboradas nos filmes selecionados e como estas se relacionam com o pensamento e as práticas do Ocidente moderno-contemporâneo. Especificamente, a investigação foca em filmes nos quais personagens rompem com a cronologia de uma sequência de eventos ou vivenciam determinados momentos repetidas vezes. A expressão viagem no tempo envolve significados diversos. Portanto, o esforço de pesquisa começa por entender suas possíveis definições. O primeiro capítulo faz uma revisão de algumas das vertentes teóricas sobre o tempo na tradição filosófica-científica ocidental. Já o segundo capítulo explora interpretações sobre o fenômeno do mito e, além disso, examina o histórico da ficção científica. Após delimitar e detalhar o material selecionado no terceiro capítulo, a tese se volta para a análise textual dos filmes. O exame do conjunto indica três grandes questões atreladas às viagens no tempo: as cosmologias e imagens do fim do mundo; a demarcação e conexão de diferentes tempos por meio de objetos; e a problematização das relações sociais, sobretudo, o parentesco. Cada uma dessas questões é analisada no quarto capítulo. A tese demonstra como os filmes traduzem o tempo em termos concretos através das trajetórias dos personagens e seus artefatos, que, ao desconhecerem a ordem histórica, geram paradoxos, encontros e desencontros na vida social.
This thesis analyzes representations of time travel in an ensemble of productions from the United States film industry. The purpose of this study is to understand the notions of time portrayed in the selected films and how these are related to modern-contemporary Western thought and practices. Specifically, the investigation focuses on movie pictures in which characters break from the chronology of a sequence of events or experience the same moment repeatedly. The term time travel involves diverse meanings. Therefore, the research effort begins by understanding its possible definitions. The first chapter reviews some of the theoretical strands about time in Western philosophical and scientific traditions. The second chapter explores interpretations about the phenomenon of myth and the history of science fiction. After delimiting and describing the selected material in the third chapter, the thesis proceeds to the textual analysis of films. The examination of the ensemble indicates three main issues related to time travel: cosmologies and images of the end of the world; objects as markers of and connections between different temporalities, and the questioning of social relations, above all, kinship. Each one of these issues is analyzed in the fourth chapter. The thesis demonstrates how films translate time in concrete terms through the trajectories of characters and their artifacts that, unbounded by the historical order, engender paradoxes, meetings, and mismatches in social life.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1985.
Microfiche copy available in Archives and Science.
Bibliography: p. 125-126.
by Carl B. Godkin.
M.S.