An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology. (January 2020)

• Record Type: Journal Article
• Authors: Liang, Xiao (Joyce); Guler, S. Ilgin; Gayah, Vikash V.
• Is Part Of: Transportation research. Volume 110(2020)
• Page Start: 81
• Page End: 97
• Publication Date: 2020-01
• Subjects: Traffic signal optimization -- Equitable traffic signal control -- Connected Vehicles; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2019.11.005
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Real-time, Connected Vehicle-based traffic signal control algorithm. Algorithm seeks to balance between efficiency and equity. Algorithm minimizes average delay while limiting the maximum individual delay. Equity at intersections can be improved with minimum loss of efficiency. Abstract: This paper extends a real-time, Connected Vehicle-based traffic signal control algorithm at isolated intersections to balance between two competing intersection objectives: efficiency and equity. In this approach, a central controller is used to collect real-time locations of connected vehicles at regular intervals, which can then be used to also identify the existence of some of the non-connected vehicles. The control algorithm then aims to optimize the discharge sequence of naturally occurring platoons of vehicles based on their proximity. Specifically, the strategy selects the platoon discharge sequence—and associated signal phase and timing plan—that minimizes average vehicle delay (measure of efficiency) while limiting the maximum delay any individual vehicle may experience (measure of equity). The latter objective is only possible with detailed vehicle-level information available from connected vehicles. The results show that without the threshold on maximum individual vehicle delay, average delay is often minimized at the expense of very large delays imposed onto some vehicles. By implementing a threshold, both the maximum vehicle delay and the distribution of individual vehicle delays—as measured by the standard deviation and a common measure of population inequity, the Gini coefficient—can be improved, often with only negligible impacts to intersection efficiency. However, the tradeoff between equity and efficiency becomes more significant as the maximum vehicle delay threshold decreases. Sensitivity tests show that this control algorithm works well for different total traffic demands and different demand patterns. The proposed algorithm is also effective under imperfect connected vehicle penetration rates when the connected vehicles make up more than 40% of the traffic stream. The results suggest that the proposed strategy can help significantly reduce long delays and inequitable treatment of vehicles at an intersection when vehicle-level information is available to a signal controller.