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A Real-Time Transit Signal Priority Control Model Considering Stochastic Bus Arrival Time

Transit signal priority (TSP) strategy gives transit vehicles preferential treatments to move through an intersection with minimum delay. To produce a good TSP timing, advance planning with enough look-ahead time is the key. This,however, means added uncertainty about bus arrival time at stop bar. In this paper, we proposed a stochastic mixed-integer nonlinear program (SMINP) model as the core component of a real-time TSP control system. The model adopts a novel approach to capture the impacts of the priority operation to other traffic by using the deviations of the phase split times from the optimal background split times. In addition, the model explicitly accounts for the randomness of the bus' arrival time by considering the bus stop dwell time and the delay caused by standing vehicle queues. The SMINP is implemented in a simulation evaluation platform developed using a combination of a microscopic traffic simulator and a commercial optimization solver. Comparison analyses were performed to compare the proposed control model with the state-of-the-practice TSP system [i.e., ring-barrier controller (RBC)-TSP]. The results showed the SMINP has yielded asmuch as 30% improvement of bus delay compared with RBC-TSP in a single-bus case. In a multiple-bus case, SMINP handles the bus priority request much more effectively under congested traffic conditions.