Network-wide performance assessment of urban traffic based on probe vehicle data

Traffic congestion, which is represented by stochastic short-term traffic interference of varying duration and frequency, is a key influencing factor of traffic characteristics and quality of service of urban street network. The two-fluid (the vehicles in traffic flow are divided into moving vehicles and stopped vehicles) model is able to describe the average operating performance of urban traffic, but it is difficult to collect individual vehicles data in the network for practical application of the model in urban area. The sampling strategies on data collection based on probe vehicles are stated in the paper and trip histories of probe vehicles are aggregated across link-based microtrip in order to estimate the model parameters. The algorithm of cost function is applied to map-matching with the help of GIS (Geographic Information System). The critical speed for identifying the vehicle state is determined through sensitivity analysis. The field experiments showed that the application of probe vehicle data is reliable to assess the network performance and traffic condition of urban street network.