4.7 Article

Pedestrian-Safety-Aware Traffic Light Control Strategy for Urban Traffic Congestion Alleviation

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2019.2955752

Keywords

Safety; Mathematical model; Accidents; Optimization; Real-time systems; Data models; Intelligent transportation systems; Urban traffic light control; macroscopic pedestrian flow model; macroscopic vehicle flow model; mixed logical constraints; pedestrian violation; evolutionary algorithms

Funding

  1. Agency for Science, Technology and Research (A*STAR) through its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund-Pre Positing (IAF-PP) [A19D6a0053]

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This paper presents a traffic signal control strategy for urban traffic networks to reduce vehicle traveling delay and increase pedestrian crossing safety. An additional Dynamic All RED (DAR) phase is introduced to address pedestrian non-compliance, and an evolutionary algorithm is proposed to solve the computational complexity of the model. Case studies demonstrate the impact of pedestrian movement on vehicle traffic networks and the effectiveness of the traffic light control strategy in reducing risks for pedestrians and vehicles.
Conflicts between pedestrians and vehicles are one of the common safety issues at signalized intersections. Pedestrian Flashing GREEN (FG), a time interval for pedestrians on crosswalks to safely finish crossing before the next phase occurs, may fail to clear the crosswalk in the allotted time, due to significant pedestrian non-compliant behavior. In this manner, probability of pedestrian-vehicle exposures increases when non-compatible vehicle flows are released at the next immediate phase. This paper seeks to address this issue by presenting a traffic signal control strategy for urban traffic networks that aims to minimize vehicle traveling delay (increase efficiency) as well as pedestrian crossing risk (increase safety). First, a macroscopic model for pedestrian-vehicle mixed-flow networks is proposed. Considering the high-incidence rate of pedestrian violations during FG, an additional Dynamic All RED (DAR) phase is introduced at the end of each FG period, whose duration is adaptively adjusted according to the number of non-compliant pedestrians. With computational complexity being a concern for our model, an evolutionary algorithm with repairing mechanism (EARM), is proposed to solve our problem. Case studies are provided to illustrate the potential impact of the pedestrian movement to the vehicle traffic networks when pedestrian safety is considered in the system, as well as the efficacy of our traffic light control strategy for pedestrians and vehicles on risk reduction.

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