An Agent-Based Approach to Assess Drivers' Interaction with Pre-Trip Information Systems

Rossetti, Rosaldo J. F.; Liu, Ronghui

doi:10.1080/15472450590912529

Cited by 19 publications

(6 citation statements)

References 22 publications

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“…Most studies with this approach have focused on investigating the impact of information on route choice behavior. As could be expected, such studies (Nakayama et al, 1999;Horowitz 1984;Iida et al, 1992;Cantarella and Cascetta, 1995;Jha et al, 1998;Oh et al, 2003;Rossetti and Liu, 2005) found that the drivers' route choice could be affected by their earlier experiences. Recently, Srinivasan (2003) considered the disutility from changing paths to describe route choice behavior, and Nakayama et al (1999Nakayama et al ( , 2000Nakayama et al ( , 2001 developed a rule-based model to study drivers' route choice behavior.…”

Section: Traveler Behavior and Day-to-day Evolution Approachmentioning

confidence: 54%

Effects of user equilibrium assumptions on network traffic pattern

Kim

Jayakrishnan

2009

KSCE J Civ Eng

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The user equilibrium concept in traffic assignment is based on fundamental assumptions: perfect information, rationality, and homogeneity. This study examines changes in the traffic pattern and the network behavior when these assumptions are relaxed. In order to relax these assumptions, we employ a day-to-day evolution approach and develop agent-based simulation models that include drivers' learning model, preference model and preference sensitivity. Using the developed models, we investigate how each assumption affects network traffic patterns. The test results show that the assumption of perfect information is most influencing on the traffic assignment results. In addition, the prior information greatly affects on the route choice when drivers do not have perfect knowledge on network travel time.

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Section: Traveler Behavior and Day-to-day Evolution Approachmentioning

confidence: 54%

Effects of user equilibrium assumptions on network traffic pattern

Kim

Jayakrishnan

2009

KSCE J Civ Eng

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“…Fujiwara et al indicated that the informed level of travel service given by pre-trip information significantly affects the departure time choice [18]. Rossetti and Lui revealed that the overall performance of the pre-trip information was very likely affected by exogenous information, as ascribed to demand formation and network topology [19]. Shiftan et al confirmed that pre-trip travel time information has an impact on route-choice behavior and underscored that when experience seeking increases, individuals tend to prefer a route characterized by lower average but greater variance of travel time [20].…”

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confidence: 99%

Who Will Use Pre-Trip Traveler Information and How Will They Respond? Insights from Zhongshan Metropolitan Area, China

et al. 2015

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Abstract:The Intelligent Transportation System (ITS) is able to make the transportation system safer, smoother, and more sustainable. The research and practice of pre-trip traveler information (PTI), an indispensable component of ITS, is very limited in China. With data collected from Zhongshan Metropolitan Area, China, this empirical study revealed the socio-demographics of potential PTI users and feasible travel responses in daily trips under PTI. Young-and-middle-aged, influential, and motorized males were the most potential PTI users, while unemployed young females the least. Among the motorized potential users who habitually traveled by car, the high-income sub-group was least likely to shift travel modes under PTI. The younger white-collar or blue-collar had a lower propensity to shift to bicycle, but the younger blue-collar workers were more likely to shift to walking. The low income preferred to shift to bus rather than elevated light rail due to the difference of travel cost. The findings will facilitate our understanding of the market segments and effects of PTI, improve the system design and implementation strategy, and help address urban traffic and environmental issues throughout China. OPEN ACCESSSustainability 2015, 7 5858

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“…As it stands, it is also possible to use the tool to perform altitude queries for single points (as opposed to annotating an entire network file). The tool should be open-sourced and made publicly available soon, integrated in the MAS-Ter Lab specification (Rossetti et al, 2002(Rossetti et al, , 2005(Rossetti et al, , 2007. As main contributions from the developed work, the general comparison between altitude information retrieval techniques and the developed tool can be considered.…”

Section: Discussionmentioning

confidence: 99%

Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

Santos

Pinto

Rossetti

et al. 2016

Journal of Information Systems Engineering & Management

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Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO -Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models -particularly for the case of the Porto urban network, in Portugal. With this goal in mind, a comparison between different altitude information retrieval approaches is made and a simple tool to annotate network models with altitude data is proposed. The work starts by describing the methodological approach followed during research and development, then describing and analysing its main findings. This description includes an in-depth explanation of the proposed tool. Lastly, this work reviews some related work to the subject.

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An Agent-Based Approach to Assess Drivers' Interaction with Pre-Trip Information Systems

Cited by 19 publications

References 22 publications

Effects of user equilibrium assumptions on network traffic pattern

Effects of user equilibrium assumptions on network traffic pattern

Who Will Use Pre-Trip Traveler Information and How Will They Respond? Insights from Zhongshan Metropolitan Area, China

Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

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