Freeway Traffic State Estimation and Prediction Based on ETC-Based Path Identification Toll System

Electronic toll collection systems are convenient for a freeway toll, and it also provides a new resource for the extraction of freeway traffic state information. This paper analyzed the principle of traffic information collection based on the dedicated short range communication (DSRC) technology based ambiguous path identification toll system. A method of estimating traffic volume of road sections and the average travel time is proposed by processing and fusing the path information and toll data in the system. The average travel time of the link is predicted by using BP artificial neural network. Finally, the field experiments verified the feasibility of the proposed method and analyzed the error of average travel time prediction for freeways based on ETC-based path identification toll system on the test section of Nanjing-Hangzhou Expressway. The average percentage error of prediction results is 9.2%, which indicates satisfactory results.