Application of Real-time Sensor Data to Evaluation of Performance of Ad Hoc Distributed Traffic Simulation

Abstract

Recent advancements in sensor and wireless communication technologies are creating new opportunities to effectively exploit real-time traffic data. Onboard sensors on vehicles collect real-time traffic data and simulate traffic states in a distributed fashion. A local transportation management center coordinates the overall simulation with an optimistic execution technique. In this paper, we presents a study of the application of real-time sensor data to the evaluation of the performance of ad hoc distributed traffic simulation. In this study, the real-time field data would be replaced with the streaming sensor data in a field implementation. Two scenarios were investigated to evaluate the performance. The first scenario examined how the system adequately captures changes in traffic conditions when the sensor reports a sudden increase in traffic volume and decreases under uncongested traffic conditions. The second scenario investigated how well the ad hoc distributed traffic simulation operates when a traffic incident occurs. The proposed ad hoc distributed traffic simulation with real-time sensor data was found to be capable of capturing dynamically changing traffic conditions in both the peak traffic and incident scenarios. In both scenarios, the prediction accuracy drops when the traffic state changes. However, the ad hoc approach appears generally capable of capturing dynamically changing traffic conditions when the real-time field sensor data are available.