An analytical approach to real-time bus signal priority system for isolated intersections
mode - bus, infrastructure - bus/tram priority, infrastructure - traffic signals, operations - traffic, operations - reliability, planning - travel demand management, planning - methods, planning - service improvement, technology - intelligent transport systems
Green extension, person delay minimization, real-time bus signal priority, red truncation
Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using an analytical approach. The core of the proposed priority system involves two signal controller actions – red truncation (RT) and green extension (GE), which determine the priority timings based on the objective of minimizing total person delay incurring at the subject intersection. We demonstrate the analytical approach by deriving closed-form expressions for optimal RT and GE for a two-phase signal using cumulative count curves. The inputs required for these priority models are based on average traffic and bus conditions limited to the current signal cycle alone. Solutions for the RT and GE models indicate that three dimensionless variables – ratio of bus-arrival time to traffic queuing time, ratio of bus passenger occupancy to other vehicles’ average passenger occupancy, and ratio of traffic demand to saturation flow ratio – govern the priority decisions. Simulation results showed significant delay reduction for buses (≈22%) with a negligible impact on other traffic users during low to medium traffic conditions and high bus frequencies (3 min headway).
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Thodi, B.T., Chilukuri, B.R., & Vanajakshi, L. (2022). An analytical approach to real-time bus signal priority system for isolated intersections. Journal of Intelligent Transportation Systems, Vol. 26(2), pp. 145-167.