Готові списки джерел за темами / Passenger modelling

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Добірка наукової літератури з теми "Passenger modelling"

Автор: Grafiati
Опубліковано: 10 березня 2023

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Статті в журналах з теми "Passenger modelling"

1

Das, Amsori M. "Persamaan Struktur Loyalty Modelling Pengguna Public Transport Railway MRT- SBK Greaters Kuala Lumpur Malaysia." Jurnal Ilmiah Universitas Batanghari Jambi 20, no. 3 (October 1, 2020): 895. http://dx.doi.org/10.33087/jiubj.v20i3.1078.

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Анотація:
In the context of transportation, the passenger loyalty is a measurement of the level of passenger’s willingness to use a similar public transport. The goal of this study is to examines and identifies factors that influencing passenger loyalty. Three factors such as satisfaction, service value, services quality was predicted as an influential factor towards passengers’ loyalty. The Mass Rapid Transit (MRT) for Sungai Buloh to Kajang (SBK) line in Kuala Lumpur conurbation was used as a case study and 555 respondents have contributed to this study. Structural equation modelling (SEM) was used to investigate the relationship between service quality, service value, passenger satisfaction and passenger loyalty. Satisfaction has the most significant influence on passenger loyalty. Service value has direct and positive effects on passenger loyalty. This study also found the service quality has significant indirect effect on the passenger loyalty via service value and passenger satisfaction.The structural model for investigating the loyalty of MRT-SBK users to this service has been analysed and tested using the service quality, satisfaction and quality value showed 75% positive change for all variables. These models recorded average errors and absolute index evaluation in accepted criteria of ≤ 0.09 and ≥ 0.94 respectively. The study reveals that MRT-SBK passengers’ loyalty is significantly influenced by service attributes, such as vehicle safety, convenience, punctuality, comfort, cleanliness of the facility provided. This study helps MRT service provider to optimize resource to enhance user’s satisfaction and therefore, increase the passenger loyalty
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2

Zhu, Wei, Wei Wang, and Zhaodong Huang. "Estimating Train Choices of Rail Transit Passengers with Real Timetable and Automatic Fare Collection Data." Journal of Advanced Transportation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/5824051.

Повний текст джерела
Анотація:
An urban rail transit (URT) system is operated according to relatively punctual schedule, which is one of the most important constraints for a URT passenger’s travel. Thus, it is the key to estimate passengers’ train choices based on which passenger route choices as well as flow distribution on the URT network can be deduced. In this paper we propose a methodology that can estimate individual passenger’s train choices with real timetable and automatic fare collection (AFC) data. First, we formulate the addressed problem using Manski’s paradigm on modelling choice. Then, an integrated framework for estimating individual passenger’s train choices is developed through a data-driven approach. The approach links each passenger trip to the most feasible train itinerary. Initial case study on Shanghai metro shows that the proposed approach works well and can be further used for deducing other important operational indicators like route choices, passenger flows on section, load factor of train, and so forth.
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3

YAN, Zhenying, Meiying JIAN, Xiaojuan LI, and Jinxin CAO. "Modelling the Passenger Choice Behaviour of Buying High-Speed Railway Tickets." Promet - Traffic&Transportation 34, no. 3 (June 1, 2022): 455–65. http://dx.doi.org/10.7307/ptt.v34i3.3942.

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Анотація:
Passenger choice behaviour of buying tickets has a great impact on the high-speed rail (HSR) revenue management. It is very critical to find out the sensitive factors that prevent passengers with high willingness to pay for a ticket from buying low-price tickets. The literature on passenger choice behaviour mainly focuses on travel mode choice, choice between a conventional train and a high-speed train and choice among high-speed trains. To extend the literature and serve revenue management, this paper investigates passenger choice behaviour of buying high-speed railway tickets. The data were collected by the stated preference (SP) survey based on Beijing-Hohhot high-speed railway. The conditional logit model was established to analyse influencing factors for business travel and non-business travel. The results show that: business passengers have the higher inherent preference for full-price tickets, while non-business passengers have the higher inherent preference for discount tickets; the number of days booked in advance and frequent passenger points have a significant impact on the ticket choice of business travellers, but not on non-business travellers; passengers are unwilling to buy tickets that depart after 16:00 for non-business travel; factors have different effects on the passengers' choice in business travel and non-business travel. The results can provide parameters for revenue management models and references for the ticket-product design.
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4

Yang, Bo, Xuedong Yan, and Dahai Guo. "Level of Service Analysis Based on Maximum Number of Passengers in Waiting Room of Railway Passenger Station Using Arena Simulation." Discrete Dynamics in Nature and Society 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/452035.

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Анотація:
The level of service is an important aspect of the operation and management at a railway passenger station. Particularly, the level of service in waiting room (LOSWR) is one of the most important influential factors in deciding passengers’ satisfaction. This paper proposes a model for finding the LOSWR based on the maximum number of passengers, and an Arena simulation model that simulates passengers’ aggregation behaviors in the waiting room is presented for analyzing the LOSWR. Through the simulation, we demonstrate how the passenger advanced arrival time and the accompany rate influence the maximum number of passengers and the LOSWR. In addition, the simulation also illustrates the effect utilities and the priority of different measures that can be used to improve the LOSWR. In detail, the simulation results demonstrate that the passenger advanced arrival time and advanced check-out time have much stronger effect utilities on the maximum number of passengers and the LOSWR than other discussed factors. The simulation suggests that the Arena is an effective simulation platform for analyzing complex passengers-related behaviors at railway passenger station.
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5

Zheng, Jinzi. "Research on Passenger Flow Assignment of High-Speed Trains Based on Personalized Itinerary Choice." Discrete Dynamics in Nature and Society 2020 (May 1, 2020): 1–8. http://dx.doi.org/10.1155/2020/6543571.

Повний текст джерела
Анотація:
Under the condition that ticket fare for high-speed train could fluctuate around a benchmark price in China, aimed at predicting how the passengers will distribute among different trains given a ticket fare, the passenger flow assignment method for high-speed trains is studied. Different from the classical researches on the passenger flow assignment, by introducing a variable that represents the value of time, this research allows passengers to make their personalized choice between the principles of time minimization and expense minimization, so as to demonstrate how the passengers holding different time values respond to each ticket fare scheme. An equilibrium passenger flow assignment model based on personalized choice is built and an improved Monte-Carlo random simulation algorithm is designed for solving the model. The actual ticket sale data for Beijing-Shanghai high-speed railway are used to verify the feasibility of the proposed model and algorithm. The passenger flow assignment results under various fare schemes show how the distribution of passenger flow changes with the adjustment of ticket fare.
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6

Gao, Jianghua, Limin Jia, and Jianyuan Guo. "Applying System Dynamics to Simulate the Passenger Flow in Subway Stations." Discrete Dynamics in Nature and Society 2019 (December 19, 2019): 1–14. http://dx.doi.org/10.1155/2019/7540549.

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Анотація:
A macroscopic passenger flow simulation model based on system dynamics is proposed in this paper. It considers the key factors influencing the dynamics of passenger flow from a holistic perspective of the stations and then models the dynamic change in the number of passengers. Firstly, the transmission of passenger flow for a general many-to-many relation between nodes are presented. When the sum of sending capacities heading for a downstream node is less than the receiving capacity of this node, the aggregation of stranded passengers will form the queuing part of the node. The results coming from a passenger flow simulation of a subway station in Beijing show that the proposed model performs well by comparing it with the real data. It can be applied to describe the dynamic change in the number of passengers and the level of service for the facilities.
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7

Palmowska, Agnieszka, and Izabela Sarna. "CFD Modelling of Thermal Comfort in the Passenger Coach." Architecture, Civil Engineering, Environment 15, no. 4 (December 1, 2022): 133–46. http://dx.doi.org/10.2478/acee-2022-0044.

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Анотація:
Abstract This paper presents the results of numerical simulations of thermal comfort in a passenger coach. The numerical model with people's presence was developed and appropriate boundary conditions were prepared. The ANSYS CFX program was used for the simulations. The calculations were carried out for summer and winter conditions. The predicted mean vote (PMV), predicted percentage dissatisfied (PPD) and draft rate (DR) were calculated to assess the thermal comfort of passengers. The requirements of railway standards in terms of passenger comfort assessment were also verified. Based on the simulation results, it was found that the thermal comfort conditions of the passengers in the coach were not fully satisfactory, especially in summer.
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8

Setiawan, Rudy. "The Effect of Service Quality and Service Value on Suroboyo Bus Passenger Satisfaction." IOP Conference Series: Earth and Environmental Science 830, no. 1 (September 1, 2021): 012005. http://dx.doi.org/10.1088/1755-1315/830/1/012005.

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Анотація:
Abstract It is important for the public transit operator to understand the effect of service quality and service value on passenger satisfaction, to maintain passengers loyalty and to attract more passengers. This study analyzed the effect of service quality and service value on Suroboyo Bus passengers satisfaction. Data were collected from a random sample of 300 Suroboyo Bus passenger and was analyzed using Structural Equation Modelling. Results show that service quality has significant positive effects on the service value, and both the service quality and the service value have significant positive effects on the passenger satisfaction. The results as well indicate that service quality only explains up to 4.5% variance of service value, while service quality and service value explains up to 48.8% variance of passenger satisfaction. Additionally, Suroboyo Bus passenger satisfaction more affected by service value, than by service quality.
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9

Setiawan, Rudy. "The Effect of Service Quality and Service Value on Suroboyo Bus Passenger Satisfaction." IOP Conference Series: Earth and Environmental Science 830, no. 1 (September 1, 2021): 012005. http://dx.doi.org/10.1088/1755-1315/830/1/012005.

Повний текст джерела
Анотація:
Abstract It is important for the public transit operator to understand the effect of service quality and service value on passenger satisfaction, to maintain passengers loyalty and to attract more passengers. This study analyzed the effect of service quality and service value on Suroboyo Bus passengers satisfaction. Data were collected from a random sample of 300 Suroboyo Bus passenger and was analyzed using Structural Equation Modelling. Results show that service quality has significant positive effects on the service value, and both the service quality and the service value have significant positive effects on the passenger satisfaction. The results as well indicate that service quality only explains up to 4.5% variance of service value, while service quality and service value explains up to 48.8% variance of passenger satisfaction. Additionally, Suroboyo Bus passenger satisfaction more affected by service value, than by service quality.
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10

Vukelić, Goran, Goran Vizentin, and Vlado Frančić. "Prospects for use of extended reality technology for ship passenger evacuation simulation." Pomorstvo 35, no. 1 (June 30, 2021): 49–56. http://dx.doi.org/10.31217/p.35.1.6.

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Анотація:
Safety of passengers on ships is usually investigated based on data available from post-accident reports, experimental research and/or numerical modelling of emergencies. As for the numerical modelling, ship passenger evacuation falls within a greater set of pedestrian evacuation research in which extended reality (XR) technology is playing important role lately. However, XR still strives to find its place in the modelling of ship passenger evacuation. This paper brings review of literature published on the topic of XR in pedestrian evacuation with special focus on the use of these technologies (e.g. virtual reality, augmented reality) in shipping industry. Findings are put in the context of IMO’s guidelines for evacuation analysis and prospect for use of XR for ship passenger evacuation simulation are presented.
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Дисертації з теми "Passenger modelling"

1

Chandakas, Ektoras. "Modelling congestion in passenger transit networks." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1011/document.

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Анотація:
Un modèle structurel est fourni afin d'appréhender les phénomènes de capacité dans un modèle d'affectation de flux de voyageurs sur un réseau de transport collectifs. Cela a été fondé sur une représentation du réseau de transports collectifs en deux couches : sur la couche inférieure, le modèle traite séparément chaque sous système du réseau (ligne, station et rabattement) en fonction des effets de capacité spécifiques ; sur la couche supérieure, le choix d'itinéraire d'un voyageur individuel est adressée par une représentation du réseau en leg (ou segment de ligne) en utilisant le coût et les caractéristiques opérationnelles des sous-systèmes respectifs. On établit une cadre novateur pour modéliser les effets de capacité et on développe le modèle CapTA (pour Capacitated Transit Assignment). Il s'agit d'un modèle d'affectation de flux systémique et modulaire. Il adresse les phénomènes de capacité ci dessous : La qualité du service en véhicule est liée au confort de voyageurs à bord. L'occupation d'états de confort hétérogènes (places assises, strapontins et debout à de densités de voyageurs variables) influence la pénibilité perçu du voyage ; La capacité du véhicule à la montée impacte le temps d'attente de voyageurs et leur distribution aux missions disponibles ; La capacité de l'infrastructure de la ligne établit une relation entre le temps de stationnement des véhicules (and par extension les flux de voyageurs en montée et en descente) et la performance des missions et leur fréquence de service. Ces phénomènes sont traités par ligne d'exploitation sur la base d'un ensemble des modèles locaux qui rendent de flux et de coût spécifiques. Par conséquent, ils modifient les conditions locales d'un trajet en transports collectifs pour chaque voyageur individuel. Cependant, ils doivent être adressés dans le cadre d'un réseau de transports collectifs afin de recueillir leur effet sur les choix d'itinéraire sur le réseau ; essentiellement sur les arbitrages économiques qui impactent le choix entre itinéraires alternatifs. Leur traitement sur la couche réseau garantir la cohérence du choix d'itinéraire. Le modèle de station traite de contraintes de capacité spécifiques et évalue les conditions locales de marche, qui est sensible aux interactions des voyageurs à l'intérieur de la station : le goulot instantané à l'entrée d'un élément de circulation retard l'évacuation de la plateforme ; la densité de voyageurs et l'hétérogénéité des leur flux ralenti les voyageurs qui circulent dans une station ; la présence de l'information en temps réel influence le processus de décision des voyageurs. Ces effets n'ont pas seulement un impact sur le choix d'itinéraire à l'intérieure de la station, mais notamment ils modifient les choix de service sur le niveau du réseau. La Région Ile-de-France fournit un champ d'application idéal pour un modèle d'affectation de flux de voyageurs en transport collectifs sous contraintes de congestion. Plus précisément, il est utilisé dans le cadre du modèle CapTA pour illustrer les capacités de simulation et la finesse de l'approche de modélisation adoptée. Le réseau de transports collectifs contient 1 500 missions de cars et autocars, tout comme 260 missions ferroviaires et inclut 14 lignes de métro et 4 lignes de tramway. L'affectation de trafic à l'heure de pointe du matin est caractérisée d'une charge importante en voyageurs sur les sections centrales de lignes ferroviaires qui traversent la ville. Un temps de stationnement élevé, en raison de flux de montée et descente, et la réduction de la fréquence de service impactent la capacité des missions et des lignes. Le temps généralisé d'un trajet est impacté notamment de sa composante de confort à bord. De résultats détaillés sont présentés sur le RER A, la ligne la plus chargée du réseau ferroviaire régional
A structural model is provided to capture capacity phenomena in passenger traffic assignment to a transit network. That has been founded on a bi-layer representation of the transit network : on the lower layer the model addresses each network sub-system (line, station and access-egress) separately, on the basis of specific capacity effects ; on the upper layer a leg-based representation is used with respect to the sub-systems' costs and operating characteristics to address the trip maker's path choices. We establish a novel framework for modelling capacity effects and develop the CapTA network model (for Capacitated Transit Assignment). It is systemic and modular and addresses in particular the following capacity phenomena, the in-vehicle quality of service is linked to the comfort of the passengers on-board. The occupation of heterogeneous comfort states (seats, folding seats and standing at different passenger densities) influences the perceived arduousness of the travel ; the vehicle capacity at boarding influences the waiting time of the passengers and their distribution to the transit services ; the track infrastructure capacity relates the dwelling time of the vehicles (and by extent the alighting and boarding flows) with the performance of the transit services and their service frequency. These phenomena are dealt with by line of operations on the basis of a set of local models yielding specific flows and costs. Accordingly, they modify the local conditions of a transit trip for each individual passenger. However, these should be addressed within the transit network in order to capture their effect on the network path choices; essentially the economic trade-offs that influence the choice between different network itineraries. Their treatment in a network level assures the coherence of the path choice. Equivalently, a station sub-model addresses specific capacity constraints and yields the local walking conditions, sensible to the interaction of the passengers in the interior of a station : the instant bottleneck created at the entry of the circulation elements delays the evacuation of the station platforms; the passenger density and presence of heterogeneous passenger flows slows down the passengers who circulate in the station; and the presence of real-time information influences the decision making process of the transit users exposed to. These effects do not only impact locally the in-station path choice, but most notably they modify the choices of transit routes and itineraries on a network level. The Paris Metropolitan Region provides an ideal application field of the capacity constrained transit assignment model. It is mainly used as a showcase of the simulation capabilities and of the finesse of the modelling approach. The transit network involves 1 500 bus routes together with 260 trains routes that include 14 metro lines and 4 light rail lines. Traffic assignment at the morning peak hour is characterized by heavy passenger loads along the central parts of the railway lines. Increased train dwelling, due to boarding and alighting flows, and reduction in the service frequency impact the route and the line capacity. The generalized time of a transit trip is impacted mainly though its in-vehicle comfort component. Detailed results have been provided for the RER A, the busiest commuter rail line in the transit network
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2

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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Анотація:
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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3

Glass, Anthony. "Modelling competition in the British passenger rail industry." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432382.

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4

Kinene, Alan. "Modelling the Passenger Demand for Buses in Örebro City." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-51426.

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5

Macey, P. "Probabilistic risk assessment modelling for passenger aircraft fire safety." Thesis, Cranfield University, 1997. http://hdl.handle.net/1826/4260.

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Анотація:
This thesis describes the development of a computer simulation model for the investigation of airliner fire accident safety. The aim of the work has been to create a computer-based analysis tool that generates representative aircraft accident scenarios and then simulates their outcome in terms of passenger injuries and fatalities. The details of the accident scenarios are formulated to closely match the type of events that are known to have occurred in aircraft accidents over the last 40 years. This information has been obtained by compiling a database and undertaking detailed analysis of approximately 200 airliner fire accidents. In addition to utilising historical data, the modelling work has incorporated many of the key findings obtained from experimental research undertaken by the world's air safety community. An unusual feature of the simulation process is that all critical aspects of the accident scenario have been analysed and catered for in the formative stages of the programme development. This has enabled complex effects, such as cabin crash disruption, impact trauma injuries, fire spread, smoke incapacitation and passenger evacuation to be simulated in a balanced and integrated manner. The study is intended to further the general appreciation and understanding of the complex events that lead to fatalities in aircraft fire accidents. This is achieved by analysing all contributory factors that are likely to arise in real fire accident scenarios and undertaking quantitative risk assessment through the use of novel simulation methods. Future development of the research could potentially enable the undertaking of a systematic exploration and appraisal of the effectiveness of both current and future aircraft fire safety policies.
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6

Zhao, Dong. "Bus Bunching Modelling and Control: A Passenger-oriented Approach." Thesis, The University of Sydney, 2018. https://hdl.handle.net/2123/23899.

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Анотація:
Bus bunching indicated the situation when two originally equally spaced bus services running close to each other as the earlier service runs increasingly late or the later service runs ahead. This phenomenon corresponds to bus services unreliability due to the extra passenger boarding, improper dispatching or travelling irregularity resulting in traffic congestions, for example. Bunched buses deteriorate passengers travel experience on public transport services that share the infrastructure with other travel modes. This has become a growing concern in big cities where traffic problems are common. It is challenging to improve the bus service reliability as a variety of chaotic sources, such as traffic congestion or unpredictable travel demand, can affect it. In order to understand the main influence factors of bus bunching in Sydney, this thesis first investigates in detail the bus service operations in Sydney and develops three passenger-oriented bus bunching mitigation approaches to improve the bus service reliability. The real picture of bus bunching in Sydney is scrutinised based on the Sydney bus system automatic vehicle location (AVL) field data. By developing the bus bunching distributions based on different criteria, such as stop location, the bus running direction, month, weekday, time and route number, bus bunching is observed to have a higher possibility in occurring during afternoon peak hours on weekdays in March and July. Additionally, buses with an outbound direction are more likely to be bunched. The ten most heavily-used bus routes with the highest number of bus bunching have also been identified using Sydney AVL data. It is observed that the overlapping routes and shared stops result in more bunches due to the interaction between buses. All the above findings have been used as the input for the simulation modelling. Second, we develop a discrete-event micro-simulation model of a bus service system with overlapping routes. The model tracks the number of passenger waiting at each bus stop as well as the amount of rider inside the vehicle of each running bus. The arrival of riders to stops are modelled as a random process while origin and destination of riders are then stored. With the input, as mentioned above, including the bus service schedule, bus stop locations, and the arrival information of riders, we have modelled Sydney's top 10 routes that have the highest number of bunches, assuming that the bus running speed follows the lognormal distribution. The lognormal distribution is determined by a historical bus running speed data fitting and each link's lognormal distribution parameter for running speed generating can be designated by a MATLAB program based on historical field data for each link. The proposed model offers waiting and in-vehicle time of each rider and can replicate the bus bunching situation in Sydney. To mitigate the number of bus bunching and reduce the unreliability of passengers travel time, we propose three control approaches in this study: (i) bus running speed management (ii) pre-planned limited-stop services (stop-skipping) and (iii) real-time boarding restrict approach. The first two approaches are associated with the planning-level control while the third is related to the operation-level bunching control. Bus running speed management method aims at identifying the links with a large number of bunching and equipping the links with the dedicated bus lane to increase the mean bus running speed and to reduce the variability of the bus running speed. This leads to a reduced likelihood of delays, and hence, mitigate the number of bus bunching. This control has considered minimizing the influence of other traffic modes on speed by selecting the least number of critical links in the network. Pre-planned limited-stop (stop-skipping) service applies as an express service in order to reduce the bus total travel time. The limited-stop pattern is rationalized by skipping the low-demand bus stops determined by historical data. This reduces total dwell time and total travel time, and then, the number of bus bunching. As a pre-planned control, passengers are assumed to be informed with all limited-stop services information, thus, none of the passengers would board on the limited-stop service at the low demand stops. Real-time boarding restrict control is a real-time control level method to reduce bus total dwell time by controlling the number of boarding. This approach is triggered when the headway between two buses is less than a pre-defined scheduled headway, in which the delayed bus will subsequently restrict passenger boarding while allow alighting only. Without passenger boarding, a decreasing number of in-vehicle passengers will alight at the following stop, which reduces the bus total running time and corrects the bus trajectory. Extensive numerical experiments have been carried out to analyse the control strategies using the developed model. The analysis results indicate that all of the control approaches achieve a high performance in reducing the number of bunching; bus running speed management and pre-planned stop-skipping methods also perform superior in reducing passenger travelling time; while real-time boarding restrict control, as a remedy method, have a better potential in steadying the passenger mean waiting time.
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Willerström, Jakob. "Modelling CO2 emissions from passenger cars for Swedish municipalities." Thesis, Uppsala universitet, Naturresurser och hållbar utveckling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385843.

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Анотація:
The ratification of the Paris agreement has motivated nations to investigate howsubstantial greenhouse gas emission reductions can be accomplished for limiting globalwarming under two degrees Celsius. In Sweden, the magnitude of CO2 emissionsfrom domestic transportation is approximately one third of all other emission sectorscombined. It is therefore crucial for Sweden to stimulate substantial reductions in thissector. Local actors' possibilities to contribute to climate change mitigation arecentral to succeed albeit constrained in the transportation sector due to data andresource limitations. With the intention to benefit local climate change mitigationwork, a model capable of estimating the tailpipe CO2 emissions from passenger carswas created. The modelling exploited traffic work data from mandatory vehiclechecks conducted in Sweden for calculating CO2 emissions per car and year for theperiod of 1999-2017, to thereafter be aggregated for a municipality, i.e. a bottom-upapproach. The model and model results have been validated with official data andemission factors from HBEFA, whereas model configurations have also beencontrolled with sensitivity analyses. The model was applied for a case-study, Järfälla, amunicipality who recently had a carbon budget developed. Model results illustrated anincreasing trend in CO2 emissions for the period of 1999-2017 and were alsopresented over fuel technology, mass and car age. Moreover, the model was appliedto produce CO2 estimates per postal codes in the municipality for 2017 and toquantify the effect of explorative scenarios, i.e. policy goals, on CO2 emissions.
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Cheng, Lin. "Modelling airport passenger group dynamics using an agent-based method." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/72999/1/Lin_Cheng_Thesis.pdf.

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This thesis investigates the influence of passenger group dynamics on passengers' behaviour in an international airport. A simulation model is built to analyse passengers' behaviour during airport departure processes and during an emergency event. Results from the model showed that passengers' group dynamics have significant influences on the performance and utilisation of airport services. The agent-based model also provides a convenient way to investigate the effectiveness of space design and service allocations, which may contribute to the enhancement of passenger airport experiences.
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9

Neto, I. U. "The development and testing of a non-recursive aggregate passenger travel demand modelling approach." Thesis, University of Bristol, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235179.

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Khan, Omer Ahmed. "Modelling passenger mode choice behaviour using computer aided stated preference data." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16500/1/Omer_Khan_Thesis.pdf.

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Redland Shire Council (RSC) has recently completed the preparation of Integrated Local Transport Plan (ILTP) and started its implementation and monitoring program. One of the major thrusts of the ILTP is to reduce the car dependency in the Shire and increase the shares of sustainable environmental-friendly travelling modes, such as walking, cycling and public transport. To achieve these objectives, a mathematical model is needed that is capable of modelling and forecasting the travelling mode choice behaviour in the multi modal environment of Redland Shire. Further, the model can be employed in testing the elasticity of various level-of-service attributes, under a virtual travel environment, as proposed in the ILTP, and estimating the demand for the new travelling alternatives to private car, namely the bus on busway, walking on walkway and cycling on cycleway. The research estimated various nested logit models for different trip lengths and trip purposes, using the data from a stated preference (SP) survey conducted in the Shire. A unique computer assisted personal interviewing (CAPI) instrument was designed, using both the motorised (bus on busway) and non-motorised travelling modes (walking on walkway and cycling on cycleway) in the SP choice set. Additionally, a unique set of access modes for bus on busway was also generated, containing hypothetical modes, such as secure park and ride facilities and kiss and ride drop-off zones at the busway stations, walkway and cycleway facilities to access the busway stations and a frequent and integrated feeder bus network within the Shire. Hence, this study created a totally new virtual travel environment for the population of Redland Shire, in order to record their perceived observations under these scenarios and develop the mode choice models. From the final model estimation results, it was found that the travel behaviour forecasted for regional trip-makers is considerably different from that of local trip-makers. The regional travellers for work, for instance, were found not to perceive the non-motorised modes as valid alternatives to car, possibly due to longer trip lengths. The value of time (VoT) determined for local work trip-makers (16.50 A$/hr) was also found to be higher than that of regional work trip-makers (11.70 A$/hr). From the survey analysis, a big part of the targeted population was found to be car captives, who are not likely to switch from cars to public transport; even if a more efficient transit infrastructure is implemented. In the past, the models have been generally calibrated using the mode choice survey data only, while that of the captive users were ignored. This yields a knowledge gap in capturing the complete travel behaviour of a region, since the question of what particular biases can be involved with each model estimation parameter by the captives remain unresolved. In this research, various statistical analyses were performed on the car captive users' data by categorising them into various trip characteristics and household parameters, in order to infer the relative influence of the car captive population on the travel behaviour of the study area. The outcomes of the research can assist the policy makers in solving the strategic issues of transit planning, including the future development of a busway corridor, with an efficient transit access mode network. The research findings can also be utilised in evaluating the feasibility of developing walkways and cycleways in the Shire, along with appraising the relative influence of car captive users on the travel behaviour forecasts for the study area.
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Книги з теми "Passenger modelling"

1

Johnstone, Nick. Modelling passenger demand, energy consumption and pollution emissions in thetransport sector. Cambridge: Department of Applied Economics, University of Cambridge, 1995.

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Gentile, Guido, and Klaus Noekel, eds. Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25082-3.

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Webb, Jonathan. Mathematical modelling of the stability of passenger-carrying tandem seat all terrain vehicle (ATV). Sudbury: HSE Books, 2004.

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Garrow, Laurie A. Discrete choice modelling and air travel demand: Theory and applications. Farnham, Surrey: Ashgate, 2009.

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Discrete choice modelling and air travel demand: Theory and applications. Farnham, Surrey: Ashgate, 2010.

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Cherry, Ann Susan. An investigation of multibody system modelling and control analysis techniques for the development of advanced suspension systems in passenger cars. [s.l.]: typescript, 1992.

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Daamen, Winnie. Modelling Passenger Flows In Public Transport Facilities (Trail Thesis Series). Delft Univ Pr, 2004.

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8

STEMM: Strategic European multi-modal modelling. Luxembourg: Office for Official Publications of the European Communities, 1999.

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Gentile, Guido, and Klaus Nökel. Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems: COST Action TU1004. Springer, 2016.

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10

Gentile, Guido, and Klaus Nökel. Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems: COST Action TU1004. Springer London, Limited, 2016.

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Частини книг з теми "Passenger modelling"

1

Bouzaïene-Ayari, Belgacem, Michel Gendreau, and Sang Nguyen. "Passenger Assignment in Congested Transit Networks: A Historical Perspective." In Equilibrium and Advanced Transportation Modelling, 47–71. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5757-9_3.

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2

Capote, Jorge, Daniel Alvear, Orlando Abreu, Mariano Lázaro, and Arturo Cuesta. "Evacuation Modelling of Fire Scenarios in Passenger Trains." In Pedestrian and Evacuation Dynamics 2008, 705–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_68.

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3

Horn, Mark E. T. "Modelling and Assessment of Demand-Responsive Passenger Transport Services." In Applied GIS and Spatial Analysis, 169–94. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470871334.ch10.

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4

Kolluru, Soma Sekhara Rao, and Aditya Kumar Patra. "Estimation of Passenger Exposure to PM2.5 on a Highway." In Urban Air Quality Monitoring, Modelling and Human Exposure Assessment, 355–66. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5511-4_25.

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5

Friedrich, Markus, Fabien Leurent, Irina Jackiva, Valentina Fini, and Sebastián Raveau. "From Transit Systems to Models: Purpose of Modelling." In Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems, 131–234. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25082-3_4.

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6

Gentile, Guido, Michael Florian, Younes Hamdouch, Oded Cats, and Agostino Nuzzolo. "The Theory of Transit Assignment: Basic Modelling Frameworks." In Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems, 287–386. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25082-3_6.

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Mohata, Abhishek, Nimai Mukhopadhyay, and Vidyapati Kumar. "CRITIC-COPRAS-Based Selection of Commercially Viable Alternative Fuel Passenger Vehicle." In Advances in Modelling and Optimization of Manufacturing and Industrial Systems, 51–69. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6107-6_5.

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Zhao, Zheng, Pei Liu, and Zheng Li. "Modelling and Analysis of China’s Passenger Car Fuel Consumption up to 2030." In Advances in Energy Systems Engineering, 273–309. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42803-1_10.

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9

Subbarao, Saladi S. V., A. Deepti, H. Amit, A. Akshay, and S. K. Charan. "Emission Modelling of Passenger Cars in India: A Case of Hyderabad City." In Lecture Notes in Civil Engineering, 343–51. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9925-2_24.

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10

Andreasson, Ingmar, Fabien Leurent, Francesco Corman, and Luigi dell’Olio. "Applications and Future Developments: Modelling the Diversity and Integration of Transit Modes." In Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems, 485–519. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25082-3_8.

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Тези доповідей конференцій з теми "Passenger modelling"

1

Strachan, Jonathan, David Cormie, and Keith Clutter. "Explosion Hazard Modelling Applied To Passenger Vessels." In Passenger Ship Safety. RINA, 2003. http://dx.doi.org/10.3940/rina.pass.2003.11.

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Ramsdale, Susan, and R. Nigel Mawhinney. "Fire Consequence Modelling For The Safety First Project." In Passenger Ship Safety. RINA, 2003. http://dx.doi.org/10.3940/rina.pass.2003.19.

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James, E. H. "Further Aspects of Combustion Modelling in Spark Ignition Engines." In Passenger Car Meeting & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1989. http://dx.doi.org/10.4271/892012.

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<div class="htmlview paragraph">An existing “phenomenological” computer model of the spark ignition engine combustion process has been used to reveal further information on flame development in such engines. A detailed flame map and pressure-time diagram (from <a href="#R6" class="xrefAnchor" title="Jump to reference Ref (6)">Ref (6)</a>) has been analysed to determine more precisely the 3-dimensional nature of the flame development across the CFR engine cylindrical disc combustion chamber. The conventional spherical flame assumption (centred at the spark plug) is found to be inaccurate with the extent of the deviation from sphericity varying with flame radius and compression ratio in both the vertical and horizontal (plan view) planes. The flame map provides input data in the form of enflamed volumes, heat transfer surface areas etc for the subsequent evaluation of turbulent burning velocities, mass burn rates, pressure-time diagrams etc. This is achieved by an iterative technique involving the mass burnt during any crank angle interval so that the burnt volume is correctly predicted (i.e. coincides with the known, measured, enflamed volume). A “thin flame” assumption appears valid across the major part of the chamber but, during the final “termination period”, combustion calculations involving finite burn-up rates in “thick” turbulent flames need to be incorporated. The transitional point coincides with a rapid escalation in the surface:volume ratio of the “end gas” and, possibly also, with the appearance of enhanced low frequency flow velocity fluctuations induced by piston motion on the expansion stroke. An exponential expression is used to portray mass burn rates within the entrained charge during flame propagation at this time. Pressure-time diagrams using the ‘thick’ flame model are compared with ‘thin’ flame predictions and measured values.</div>
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Do, Ngoc-Hien, Quynh-Lam Le Ngoc, and Ki-Chan Nam. "An Estimation Of Passenger Car Equivalent Of Motorbikes." In 24th European Conference on Modelling and Simulation. ECMS, 2009. http://dx.doi.org/10.7148/2001-0098-0103.

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Do, Ngoc-Hien, Quynh-Lam Le Ngoc, and Ki-Chan Nam. "An Estimation Of Passenger Car Equivalent Of Motorbikes." In 24th European Conference on Modelling and Simulation. ECMS, 2010. http://dx.doi.org/10.7148/2010-0098-0103.

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6

"Modelling Passengers Flow at Airport Terminals - Individual Agent Decision Model for Stochastic Passenger Behaviour." In 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0004055701090113.

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7

Ghosh, Robin, and Ivan Terekhov. "Future Passenger Air Traffic Modelling: Trend Analysis of the Passenger Air Travel Demand Network." In 53rd AIAA Aerospace Sciences Meeting. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-1642.

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Eberle, Reinhard, and Harald A. Franze. "Modelling the Use Phase of Passenger Cars in LCI." In Total Life Cycle Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1998. http://dx.doi.org/10.4271/982179.

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Haug, Jürgen, Udo Piram, Werner Schiehlen, and Thomas Schirle. "Modelling of a Passenger Coach As Elastic Multibody System." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-4225.

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Abstract In this paper the multibody model of a railroad passenger coach consisting of two rigid bogies and an elastic car body is presented. The elastic body is introduced by a floating reference frame and superimposed elastic deformations linearized with respect to the reference frame. The governing equations of motion are presented in symbolical form, where the time-invariant matrices describing the elastodynamical behavior are computed numerically in a preprocessor. To increase the computational efficiency, condensation techniques are applied and ten modes are chosen to describe the elastic behavior. Simulations of high speed travelling have been carried out with excitation from measured data of a real track. As a measure of ride comfort the acceleration at characteristic points on the coach are computed. Comparison with results obtained using a less sophisticated rigid body model show significant higher accelerations, depending on the position on the coach, too.
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Kellermann, Norman. "Agent-Based Simulation As A Support For Price-Setting In Passenger Transport." In 27th Conference on Modelling and Simulation. ECMS, 2013. http://dx.doi.org/10.7148/2013-0333.

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