摘要

Confined by the real-time and accuracy of traditional traffic collecting parameters, the existing traffic delay estimation models are generally with poor performance in guiding practical applications. In the Cooperative Vehicle-Infrastructure System, the real-time entire space-time driving state information of a single intelligent vehicle provides new data supporting for road traffic status evaluation. Fully extracting the value of this kind of new data, this paper proposes a new real-time traffic delay estimation method based on the Webster signalized intersection delay model. Taking each intelligent vehicle as a benchmark point, the vehicle arriving/leaving characteristics of the signalized intersection are spatially interpolated by the stopping state of a small amount of benchmark vehicles. In order to obtain the critical queuing dissipation point, the linear fitting method is used to forecast the critical stopping time and further the Markov model is used to estimate the number of queuing vehicles at the critical stopping time. Based on the real-time vehicle queuing characteristics, a new traffic delay estimation model is built according to the Webster estimation mechanism. The case study shows that, compared with the traditional Webster model, the proposed method can effectively improve the traffic delay estimating accuracy.