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Studies of vehicle lane-changing to avoid pedestrians with cellular automata

Xiang Li and Jian-Qiao Sun

Physica A: Statistical Mechanics and its Applications, 2015, vol. 438, issue C, 251-271

Abstract: This paper presents studies of interactions between vehicles and crossing pedestrians. A cellular automata system model of the traffic is developed, which includes a number of subsystem models such as the single-lane vehicle model, pedestrian model, interaction model and lane-changing model. The random street crossings of pedestrians are modeled as a Poisson process. The drivers of the passing vehicles are assumed to follow a safety-rule in order not to hit the pedestrians. The results of both single and multiple car simulations are presented. We have found that in general, the traffic can benefit from vehicle lane-changing to avoid road-crossing pedestrians. The traffic flow and average vehicle speed can be increased, which leads to higher traffic efficiency. The interactions between vehicles and pedestrians are reduced, which results in shorter vehicle decelerating time due to pedestrians and less switches of the driving mode, thus leads to the better energy economy. The traffic safety can be improved in the perspective of both vehicles and pedestrians. Finally, pedestrians can cross road faster. The negative effect of lane-changing is that pedestrians have to stay longer between the lanes in the crossing.

Keywords: Traffic system; Vehicle lane-changing; Vehicle–pedestrian interaction; Traffic fuel efficiency; Vehicle emissions; Cellular automata (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:438:y:2015:i:c:p:251-271

DOI: 10.1016/j.physa.2015.06.028

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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