, Former Professor, Civil, Environmental and Geo-Engineering
Due to budget constraints, most of the traffic signals in the U.S. are retimed once every 2-5 years. Despite that, traffic delay increases 3-5% per year with outdated timing plans. It would be desirable to reduce the signal retiming costs by automating all or a portion of the manual process. This research takes one step forward in this direction. In this project, we developed a performance visualization and fine-tuning tool for arterial traffic signal systems, aimed at reducing the labor costs for signal retiming. Using high-resolution, event-based data from the SMART-Signal system, a set of easy-to-use algorithms were developed to refine traffic signal systems. Specifically, a framework was developed to diagnose operational problems regarding cycle lengths, green splits and offsets. Then, algorithms for offsets and green splits fine-tuning was proposed. To fine-tune offsets, a practical procedure to construct time space diagram (TS-Diagram) to visualize the progression quality on arterials was proposed and validated. For green splits, an adjusted measure of effectiveness (MOE), the utilized green time (UGT), was proposed for performance evaluation. Moreover, a practical procedure for time of day (TOD) transitions was also developed to generate optimal timing plan schedules. Field case studies and simulation experiments were carried out to illustrate and validate the proposed algorithms. The algorithms could be used during the retiming process to help agencies reduce labor costs or to periodically refine traffic signal systems for coordinated arterials.