Decentralized arterial traffic signal optimization with connected vehicle information

This paper proposes a decentralized signal control algorithm that leverages connected vehicle information to improve traffic operations along arterials. The proposed algorithm obtains real-time vehicle locations and speeds, as well as information on pedestrians waiting to cross individual intersections, to optimize signal phasing and timing plans. Signal timing is optimized at individual intersections; however, information about vehicle platoons passing a given intersection is shared with neighboring intersections to facilitate natural coordination between adjacent intersections. The decentralized algorithm is compared to a centralized algorithm that optimizes signal timing at all intersections simultaneously, as well as a traditional coordination strategy. The proposed algorithm is shown both to be more computationally efficient than the centralized approach and provide better operational performance (in terms of person, vehicle and pedestrian delay) than both the centralized algorithm and the traditional strategy. The algorithm is robust to a range of demand patterns and can be applied under scenarios in which not all vehicles are connected or full information about pedestrian arrivals is not available.