Evaluation of connected vehicle impact on mobility and mode choice

Minelli, Simon; Izadpanah, Pedram; Razavi, Saiedeh

doi:10.1016/j.jtte.2015.08.002

Cited by 21 publications

(13 citation statements)

References 21 publications

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“…Minelli et al [8] evaluated the effectiveness of the connected vehicles among the mode choice and transportation network mobility. The evaluation step consisted of mode choice and traffic assignment.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

Han¹,

Lee

Park

et al. 2019

Journal of Advanced Transportation

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This study aims to develop an optimal signal control algorithm for signalized intersections using individual vehicle’s trajectory data under the vehicle-to-infrastructure (V2I) communication environment. The optimal signal control algorithm developed in this study consists of three modules, namely, a phase group length computation module, a split distribution module, and a phase sequence assignment module. A set of analyses using a microscopic simulation model, VISSIM, was conducted for evaluating the effectiveness of the V2I-based optimal signal control algorithm proposed in this study. The analysis results show that the performance of the V2I-based optimal signal control algorithm is superior to the actuated as well as the fixed signal control methods in an isolated intersection and a 2X3 signalized intersection network. In addition, this study investigated the minimum market penetration rate of V2I equipped vehicles for which the V2I-based optimal signal control algorithm is applicable.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

Han¹,

Lee

Park

et al. 2019

Journal of Advanced Transportation

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“…This work emphasizes driver behaviour modelling issues, which have not been considered in related papers in the literature [12,18,19,22,23,28,29].…”

Section: Modelling Issuesmentioning

confidence: 99%

Impact on Network Performance of Probe Vehicle Data Usage: An Experimental Design for Simulation Assessment

Mercadé

Linares

Garcia

et al. 2018

Journal of Advanced Transportation

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Probe-based technologies are proliferating as a means of inferring traffic states. Technological companies are interested in traffic data for computing the best routes in a traffic-aware manner and they also provide real-time traffic information with certain temporal accuracy. This paper analyses and evaluates how data provided by a fleet of probe cars can be used to develop a navigation service and how the penetration rate of this service affects a set of city-scale KPIs (Key Performance Indicators) and driver KPIs. The case study adopts a model-driven approach in which microscopic simulation emulates real-size fleets of probe vehicles that provide positions and speed data. What is noteworthy about the modelling behaviour is that drivers are segmented according to their knowledge of network conditions for selected trips: experts, regular drivers, and tourists. The paper presents and discusses the modelling approach and the results obtained from an experimental Barcelona CBD model designed to evaluate the penetration rates of probe vehicles and route guidance. An analysis of the simulation experiments reveals remarkable links among city-scale KPIs, which-from a multivariate point of view-is a novelty. A simulation-based framework for results analysis and visualization is also introduced in order to simplify the simulation results analysis and easily visualize OD paths for driver segments.

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“…This paper highlights driver behavior modeling, which has not been considered in any related papers in the literature (Lee and Park 2008;Wang et al 2017;Paikari et al 2013;Olia et al 2016;Deflorio 2003;Pan et al 2012;Minelli et al 2015). Drivers are split into six groups according to their knowledge of network and traffic conditions and according to guidance availability:…”

Section: Driver Behavior Modelingmentioning

confidence: 99%

Simulation Assessment of New Generation Navigation Strategies

Mercadé¹,

Linares²,

Garcia³

et al. 2018

2018 Winter Simulation Conference (WSC)

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Probe vehicle (or connected car) data is becoming an important source of real-time travel information for a variety of intelligent transportation system applications. Since traditional sensors have significant installation and maintenance costs, technological companies are interested in traffic data from these alternative detection techniques for computing traffic aware shortest routes. This paper analyzes and evaluates the use of data provided by probe vehicles in two reactive navigation strategies and how this affects a set of city and driver key performance indicators. The case study adopts a microscopic simulation approach to emulate real-size fleets of probe cars providing positions and speed data. The paper presents and discusses the modeling approach and the obtained results after conducting an experimental design for a Barcelona district scenario. Moreover, a simulation-based framework is introduced for simplifying simulation results analysis and easily visualizing origin-destination paths for the proposed driver segments (experts, regular and tourists).

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Evaluation of connected vehicle impact on mobility and mode choice

Cited by 21 publications

References 21 publications

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

Impact on Network Performance of Probe Vehicle Data Usage: An Experimental Design for Simulation Assessment

Simulation Assessment of New Generation Navigation Strategies

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