In this paper, we introduce a mathematical model for traffic signal scheduling problem with consideration of a platoon dispersion model. The traffic signal scheduling problem (TSSP) is formulated as a discrete-time optimization problem while the objectives are to reduce the average delay time for each link and the stop delay time in the queue for each intersection with regard to the traffic dynamics and platoon dispersion model. A non-linear programming (NLP) problem is proposed for this TSSP and a mixed integer linear programming (MILP) problem is converted from the obtained NLP formulation to simplify the development of the optimizer. The proposed traffic signal scheduling scheme is compared to an optimized fixed-time traffic control scheme with regard to the throughput and the maximal queue length. Simulation results show that our proposed method could outperform the optimized fixed-time scheme by capturing more elaborate short term traffic flow variations.
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This research is supported by A*STAR under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund Pre Positioning (IAF-PP) (Award A19D6a0053).