Urban traffic congestion is often concentrated at urban intersections. An urban road traffic signal control system is needed to prevent problems such as driving delays caused by frequent traffic congestions on trunk lines, exhaust emissions owing to frequent start and stop of vehicles, and fuel wastage due to long idling times. Maximizing the traffic capacity of an intersection and reducing the delay rate of vehicles has always been a problem for traffic control research. The coordinated control of urban traffic signals is regarded as a multi-objective optimization problem. A mathematical model for urban trunk traffic is studied herein. An average delay model, average queue length model, total delay calculation model for vehicles at intersections, and vehicle exhaust emission model are established to obtain an optimization model for a new traffic trunk coordinated control system. In addition, our study combines the fuzzy control theory with the adaptive sequencing mutation multi-objective differential evolution algorithm (FASM-MDEA). This new optimization method for traffic signal control at urban intersections is proposed as a solution for the traffic flow optimization model to solve the problem of traffic signal coordination and control of urban trunk lines. The simulation results demonstrate the effectiveness of the model optimization algorithm proposed in this study.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Traffic Signal Optimization Based on Fuzzy Control and Differential Evolution Algorithm


    Contributors:
    Lin, Haifeng (author) / Han, Yehong (author) / Cai, Weiwei (author) / Jin, Bo (author)


    Publication date :

    2023-08-01


    Size :

    2751381 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Type-2 fuzzy multi-intersection traffic signal control with differential evolution optimization

    Bi, Yunrui / Srinivasan, Dipti / Lu, Xiaobo et al. | Tema Archive | 2014



    Fuzzy Traffic Signal Control

    Niittymaki, J. P. | British Library Conference Proceedings | 2002


    Adaptive Fuzzy Logic Traffic Signal Control Based on Cuckoo Search Algorithm

    Wu, Suhua / Bi, Yunrui / Wang, Gang et al. | TIBKAT | 2019


    Adaptive Fuzzy Logic Traffic Signal Control Based on Cuckoo Search Algorithm

    Wu, Suhua / Bi, Yunrui / Wang, Gang et al. | Springer Verlag | 2019