Large scale planned special events (PSE), such as sporting games, concerts, and parades, attracting high volume of pedestrians, buses and passenger vehicles, result in significant non-recurrent traffic congestion.
Properly managing traffic for PSEs is crucial for travel safety, mobility and energy consumption. In this research project titled "Traffic Control Agency Behavior Modeling and Deployment Optimization for Large Scale Planned Special Events," the investigators proposed a network wide intersection control model to harness non-recurrent congestion caused by PSEs, utilizing manned intersection control from traffic control agency (TCA), including police and traffic law enforcement officers, who overrides traffic lights to direct traffic movements.
Different with pre-timed traffic signal control, TCAs can effectively balance queues and increase throughput, and prevent pedestrian-vehicle crashes. This project aims to model TCA behavior and investigate the optimization plan to deploy TCA spatially and temporally. The research outcomes can be applied to both campus events and non-campuses events. Therefore, all the SUNY campus as well as other communities can benefit from this work. This project will obtain practice support from Parking and Transportation Service at the University at Buffalo. The improvement for their current deployment on campus constitutes the success for this project. Energy consumption of event traffic, to be accurately quantified by microscopic traffic simulation software, will be greatly reduced by correct TCA planning.
An experiment was designed based on a standalone version of manual intersection control simulator. The participants are existing traffic police from the Police Department at the University at Buffalo. Due to time constraints, four experiments are conducted for police with different number of traffic control experiences. The results of manual traffic control are compared with the results from SYNCHRO (commercial traffic signal optimization software) offline optimized signal plan with hourly average event traffic. According to the comparisons, we can observe that:
The above findings conclude that TCAs are able to successfully tackle issues of large uncertainty and multi-modal volume from the event traffic. However, their performances are not consistent with their work experiences. Therefore, there is a pressing need to standardize manual intersection control and develop training courses for both new and existing TCAs.
ISE and CSEE faculty member Qing He, along with students Nan Ding and Ming Ni, are conducting the research, which is sponsored by the SUNY Sustainability Fund. The research was featured in the March 6 issue of the UB Spectrum.