A two-stage traffic sensor location method for low-volume road incident detection

Low-volume road always lied at the area with few inhabitants and few traffic monitoring equipment, thus it's difficult to detect traffic incident and take traffic rescue in a timely manner. However, most research focused on high-volume road traffic sensor location for OD matrix estimation, travel time estimation and traffic volume estimation, not aiming to low-volume road for incident detection. Firstly, a two-stage traffic sensor location method was proposed for low-volume road incident detection, with the optimization objective of maximizing incident detection rate. At the first stage, high-resolution camera Automatic Vehicle Identification (AVI) was used to monitor closed road segments, at the second stage, video was used to monitor both the closed road segments and intersection segments. Then, reliability theory was adopted to model the incident detection rate of AVI and video parallel detection system. Next, a real-coded genetic algorithm was proposed to optimize the traffic sensor location problem. Finally, a case study was conducted and the case study result shows that incident detection rate of the first and second stage increase by 36.39% and 7.68% respectively, this demonstrates that the proposed method is effective.