Abstract

The article discusses a strategy, referred to as Categorized Arrivals-based Phase Reoptimization at Intersections (CAPRI), which integrates transit signal priority and rail/emergency preemption within a dynamic programming-based real-time traffic adaptive signal control system. The system takes as input sensor data, from detectors, automatic vehicle locators, transponders, etc., for realtime predictions of traffic flow, and “optimally ” controls the flow through the network using signal phasing. The system utilizes a traffic adaptive signal control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in a hierarchical fashion, (2) predicts traffic flows, at appropriate resolution levels (individual vehicles, platoons of vehicles, transit vehicles, emergency response units, and trains) to enable proactive control, (3) supports various optimization modules for solving the hierarchical subproblems, and (4) utilizes data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be implemented in the field within an appropriate rolling time horizon of the corresponding subproblem. Simulation-based analyses illustrate the effectiveness of the CAPRI system.

Citations