Citation

Yang XT, Chang GL, Zhang Z, Li PT. Transp. Res. Rec. 2019; 2673(5): 61-71.

Copyright

(Copyright © 2019, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198119837242

PMID

unavailable

Abstract

The intent of this paper is to develop a system that can integrate connected vehicle (CV) data and traffic sensor information to concurrently address the need to improve urban arterial safety and mobility. Under the mixed traffic pattern of CVs and human-driven vehicles (HVs), the system aims to achieve three primary objectives: proactively preventing rear-end collision, reactively protecting side-street traffic from red-light-running vehicles, and effectively facilitating speed harmonization along local arterials. The embedded safety function will integrate CV and roadside sensor data to compute the distribution of dilemma zones for vehicles of different approaching speeds in real-time. Such data fusion will enable the proposed system to offer the advice of either "stop" or "go" to both CVs and HVs so as to prevent rear-end collisions and side-angled crashes. Given the locations and speeds of CVs, and the number of vehicles monitored by sensors, the proposed system can further compute the time-varying intersection queue length. Then the embedded mobility function will optimize the arterial signal plan in real-time and produce the speed advisory for approaching vehicles to facilitate their progression through intersections.

RESULTS from extensive simulation experiments confirm the effectiveness of the proposed system in both reducing potential intersection crash rates and improving arterial progression efficiency. The proposed control framework also proves the effectiveness of using dilemma zone protection sensors for traffic mobility improvement.

Language: en