Estimation of left-turning travel time at traffic intersection

Abstract

Traffic guidance is a promise approach of traffic congestion alleviation, and the travel time is one of the most important basic data for the reasonable and effective route planning which is the core of traffic guidance. The traffic intersection is one of the chief components of the whole traffic road networks, so the estimation of travel time of the intersection plays an important role in traffic guidance. This paper pays more attention to the estimation of travel time for left-turning lane connected to an intersection, introduces the features for travel time estimation, and designs an estimator based on the learning vector quantity (LVQ) neural network. A suite of reasonable test shows that the method can effectively estimate the travel time of vehicles at left-turning lane with lower error to the real data.