Schedule-driven intersection control.

Xie Xiao-Feng, Smith Stephen F., Liang Lu, Barlow Gregory J.

    Research output: Contribution to journalArticlepeer-review

    83 Citations (Scopus)


    Model-based intersection optimization strategies have been widely investigated for distributed traffic signal control in road networks. Due to the form of “black-box” optimization that is typically assumed, a basic challenge faced by these strategies is the combinatorial nature of the problem that must be solved. The underlying state space is exponential in the number of time steps in the look-ahead optimization horizon at a given time resolution. In this paper, we present a schedule-driven intersection control strategy, called SchIC, which addresses this challenge by exploiting the structural information in non-uniformly distributed traffic flow. Central to our method is an alternative formulation of intersection control optimization as a scheduling problem, which effectively reduces the state space through use of an aggregate representation on traffic flow data in the prediction horizon. A forward recursive algorithm is proposed for solving the scheduling problem, which makes use of
    Original languageEnglish
    Pages (from-to)168 - 189
    JournalTransportation Research Part C: Emerging Technologies
    Issue numbern/a
    Publication statusPublished - 2012


    • Adaptive traffic signal control, Model-based intersection optimization, Real-time systems, Urban traffic control, Intelligent transportation systems


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