Trade-Offs Between Bus and Private Vehicle Delays at Signalized Intersections: Case Study of a Multiobjective Model

Mixed road users on most urban arterials are controlled by the same set of signals and must compete for shared road space. Transit signal priority (TSP) systems have been established to improve transit service operations in mixed traffic. To balance the benefits of priority control with the negative effects, most existing adaptive TSP strategies normally use an integrated performance index, a weighted sum of all types of delays, for evaluation and optimization. In a previous study, the authors formulated the TSP optimization into a quadratic programming problem with an enhanced delay-based performance index to obtain global optimization. In this study, the problem was formulated into a multiobjective optimization model, which was solved with a nondominated sorting genetic algorithm. Pareto-optimal front results were presented to evaluate the trade-offs between two objectives: minimization of private vehicle delay and of bus delay. Then the most appropriate solution was chosen with high-level information. A simulation study was conducted along 7.4 km of a bus corridor, with an adaptive TSP simulation platform, by using a full-scale signal simulator, ASC/3, in Vissim. The results show that the Pareto-optimal solutions provided more interesting practical options for decision makers.