UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems

Aiming to comply with the requirement of parallel-transportation management systems (PtMS), this paper presents a short-term traffic flow prediction method for signal-controlled urban traffic networks (UTNs) based on the macroscopic UTN model. In contrast with other time-series-based or spatio-temporal correlation methods, the proposed method focuses more on using the substantial mechanism of traffic transmission in road networks and the topology model of the entire UTN. Furthermore, this approach employs a speed-density model based on the fundamental diagram (FD) to obtain more accurate travel times in links. In the comparison experiment, the microscopic traffic simulation software CORSIM is adopted to simulate the real urban traffic. The experiment results fully verify the outstanding performances of the proposed prediction method.