Dynamic Multipath Signal Progression Control Based on Connected Vehicle Technology

Abstract

In recent years, connected vehicle (CV) technology has reached a level of maturity and can be beneficial for traffic control at signalized intersections. Enriched information provided by CVs could be utilized to perform a more efficient signal control. This paper proposes a methodology to dynamically adjust the offsets to provide progression bands for multiple critical paths in a CV environment. The critical paths refer to the routes connecting origin-destination (OD) pairs with the highest volumes and are determined based on the CV trajectory. A real-time optimization model is constructed to design a coordination plan, and the control objective is to provide maximum green bandwidth along the determined critical paths by optimizing the offsets of all intersections along an arterial. To solve this model, a solution algorithm based on dynamic programming is proposed. A real-world arterial in Salt Lake City, Utah, is modeled in commercially available software to evaluate the effectiveness and efficiency of the proposed control strategy. Simulations are conducted to compare the proposed system with a fixed coordination strategy. The results reveal that the travel times of those critical paths by the proposed coordination strategy are lower the ones by the fixed coordination strategy. The average delay and average number of stops of critical paths are reduced by about 16.82% and 5.94%, respectively, compared with the fixed coordination strategy. Moreover, results also indicate that the proposed coordination strategy outperforms the fixed coordination strategy by reducing 7.84% and 5.79% of the average delay and average stops, respectively.