Dynamic Model of Transit Signal Priority on Colored Time Petri Net

Abstract

A dynamic coordination strategy model of the transit signal priority and traffic signal control cooperative system is created by using Colored Time Petri Nets (CTPNs). To extend the coordination from isolated intersections to the arterial network of intersections, a multi-level and multi-group computer supported cooperative system is described based on CTPNs. Then inter-intersection and cross-intersection coordination strategy for busses and vehicles was proposed to model transit signal priority in urban networks. INTRODUCTION Traffic management systems address the problem of reducing congestion, vehicle delay time, fuel consumption, and pollution. The most common technique to regulate and manage urban traffic areas and surface street networks is traffic signal control (Dotoli and Fanti 2006). Traffic signal control plays a central role in modern urban traffic management (Dotoli et al. 2003). Public transit, with the advantages of large capacity, reduced road occupancy, low fuel consumption and so forth, is considered to be one of the most effective ways to solve urban transportation problems (Han and Liu 2008). Transit signal priority (TSP) is a direct way to improve public transit service levels and attract residents to use public transit. In traffic control systems, general vehicle signal control and transit signal priority control share resources, resource conflicts, a tendency to deadlock and overflow, and require well-planned synchronization and scheduling. They are controlled to achieve satisfactory performance which includes reduced travel time for transit customers, improved schedule adherence and side-street traffic, and the smooth flow of traffic. (Dotoli et al. 2006). Therefore, it is of practical importance to develop, verify and, validate simple, yet powerful models that help to design and improve the safety and efficiency of traffic signal control systems. Petri nets have been proven to be a powerful modeling tool for various kinds of discrete event systems (Chung and Huang 2007). Compared with other analytical and simulation methods, Petri nets have the following advantages (Dos Santos Soares and Vrancken 2007; Wang et al. 1999): 1) Petri nets can easily express concurrency, competition, and synchronization activities among traffic, TSP and traffic control 2) Petri net modeling allows easy changes to be made to the network configuration, the traffic signal control logic, timing and coordination, and the assumptions on intersection physical layout, vehicle flow rate, turning movement, ICCTP 2009: Critical Issues in Transportation Systems Planning, Development, and Management ©2009 ASCE 1590