Bhargava Rama Chilukuri

Among the different strategies adopted to improve the efficiency and reliability of the bus services, bus signal priority is a low cost and less infrastructure- demanding solution that has the potential to reduce bus travel times in urban arterials. This paper develops analytical models for finding the thresholds for Green Extension (GE) and Red Truncation (RT) for a four-phase signal system with buses on conflicting phases. The thresholds are developed based on reducing the total person delay after considering buses from the current cycle and unserved buses from the previous cycle for priority decisions. The proposed models aim for zero-delay service for the buses from the current cycle and reducing delay for the unserved buses from the previous cycle. The models reveal that at multi-phase signals, several bus priority alternatives are possible to reduce total person delay and agencies can choose alternatives based on their requirements and constraints. These models are evaluated in VISSIM microscopic simulation environment. The evaluation results indicate a 16.7 to 42.8% reduction in total person intersection delay due to the implemented bus priority.

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).