Urban Traffic State Estimation Techniques Using Probe Vehicles: A Review

Abstract

Accurate and economical traffic state estimation is a challenging problem for future smart cities. To curb this problem, fixed roadside sensors are used for traffic data collection traditionally, but their high costs of installation and maintenance has led to the use of probe vehicles or mobile phones containing GPS-based sensors as an alternative cost-effective method for traffic data collection. However, the data collected by the latter method are sparse because the probe vehicles are very randomly distributed over both time and space. This survey paper presents state-of-the-art techniques prevalent in the last few years for traffic state estimation and compares them on the basis of important parameters such as accuracy, running time, and integrity of the data used. The dataset used for the implementation of techniques comes from probe vehicles such as taxis and buses of cities such as San Francisco, Shanghai, and Stockholm with different sampling rates (frequencies) of probes. Finally, it represents the challenges that need to be addressed along with the possible data processing solution.