Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151283
Title: Traffic light scheduling for pedestrian-vehicle mixed-flow networks
Authors: Zhang, Yi
Gao, Kaizhou
Zhang, Yicheng
Su, Rong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Zhang, Y., Gao, K., Zhang, Y. & Su, R. (2018). Traffic light scheduling for pedestrian-vehicle mixed-flow networks. IEEE Transactions On Intelligent Transportation Systems, 20(4), 1468-1483. https://dx.doi.org/10.1109/TITS.2018.2852646
Project: S15-1105-RF-LLF URBAN
Journal: IEEE Transactions on Intelligent Transportation Systems
Abstract: This paper presents a macroscopic model for pedestrian-vehicle mixed-flow network and a traffic signal scheduling strategy for both pedestrians and vehicles. We first propose a novel mathematical model of pedestrians crossing a junction. By combining a link-based vehicle network model, a traffic light scheduling problem is formulated with the aim to strike a good balance between pedestrians' needs and vehicle drivers' needs. The problem is first converted into a mixed-integer linear programming (MILP) problem via a novel transformation procedure, which is solvable by several existing solvers, e.g., GUROBI. Then a meta-heuristic method called discrete harmony search (DHS) algorithm is also adopted to reduce the computational complexity in MILP. Numerical simulation results are provided to illustrate the effectiveness of our real-time traffic light scheduling strategy for pedestrians and vehicles, and the potential impact of the pedestrian movement to the vehicle traffic flows.
URI: https://hdl.handle.net/10356/151283
ISSN: 1524-9050
DOI: 10.1109/TITS.2018.2852646
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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