Predictive car-following scheme for improving traffic flows on urban road networks

A. S.M. Bakibillah, Mahmudul Hasan, Md Mustafijur Rahman, Md Abdus Samad Kamal

    Research output: Contribution to journalArticleResearchpeer-review

    6 Citations (Scopus)

    Abstract

    Driving behavior is one of the main reasons that causes bottleneck on the freeway or restricts the capacity of signalized intersections. This paper proposes a car-following scheme in a model predictive control (MPC) framework to improve the traffic flow behavior, particularly in stopping and speeding up of individual vehicles in dense urban traffic under a connected vehicle (CV) environment. Using information received through vehicle-to-vehicle (V2V) communication, the scheme predicts the future states of the preceding vehicle and computes the control input by solving a constrained optimization problem considering a finite future horizon. The objective function is to minimize the weighted costs due to speed deviation, control input, and unsafe gaps. The scheme shares the planned driving information with the following vehicles so that they can make better cooperative driving decision. The proposed car-following scheme is simulated in a typical driving scenario with multiple vehicles in dense traffic that has to stop at red signals in multiple intersections. The speeding up or queue clearing and stopping characteristics of the traffic using the proposed scheme is compared with the existing car-following scheme through numerical simulation.

    Original languageEnglish
    Pages (from-to)325-334
    Number of pages10
    JournalControl Theory and Technology
    Volume17
    Issue number4
    DOIs
    Publication statusPublished - Nov 2019

    Keywords

    • Car-following scheme
    • connected vehicle environment
    • distributed control
    • model predictive control
    • vehicle string

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