In this paper, Chula-Sathorn SUMO Simulator (Chula-SSS) has been proposed as an educational tool for traffic police and traffic engineers. The tool supports our framework to develop actuated traffic signal control logics in order to resolve urban traffic congestion. The framework design aims to incorporate the tacit traffic control expertise of human operators by trying to extract and extend the human-level intelligence in actuating logically traffic signal controls. In this regard, a new software package has been developed for the microscopic-mobility computer simulation capability of the SUMO (Simulation of Urban MObility) platform. Using the SUMO TraCI, our package implements the graphical user interface (GUI) of actual traffic light signal control panel, recently introduced in Bangkok (Thailand) for traffic police deployment in the Chulalongkorn University’s Sathorn Model project under the umbrella of Sustainable Mobility Project 2.0 of the World Business Council for Sustainable Development (WBCSD). The traffic light signal control panel GUI modules can communicate via TraCI in real-time to SUMO in order both to retrieve the raw traffic sensor data emulated within SUMO and to send the desired traffic light signal phase manually entered via GUI by the module users. Each of the users could play a role of traffic police in charge of actuating the traffic light signal at each of the controllable intersections. To demonstrate this framework, Chula-SSS has been implemented with the calibrated SUMO dataset of Sathorn Road network area. This area is one of the most critical areas in Bangkok due to the immense traffic volume with daily recurring traffic bottlenecks and network deadlocks. The simulation comprises of 2375 intersection nodes, 4517 edges, 10 main signalised intersections. The provided datasets with Chula-SSS cover both the morning and evening rush-hour periods each with over 55,000 simulated vehicles based on the comprehensive traffic data collection and SUMO mobility model calibration. It is hoped that the herein developed framework and software package can be not only useful for our Thailand case, but also readily extensible to those developing and least- developed countries where traffic signal controls rely on human operations, not yet fully automated by an area traffic controller. In those cases, the framework proposed herein is expectedly an enabling technology for the human operators to practice, learn, and evolve their traffic signal control strategies systematically.
A Traffic Light Signal Control System with Truck Priority1*This work has been supported in part by the National Science Foundation under the CPS program and in part by the University Transportation Center METRANS at University of Southern California.