Ad hoc distributed simulation for transportation system monitoring and near-term prediction

The widespread deployment of sensors, computers, and communications in vehicles and roadways is creating new challenges and opportunities to effectively exploit the wealth of real-time data and information that is now becoming increasingly available. In this paper the authors capitalize on these rapid technological advancements using a technique termed on-line ad hoc distributed simulation. This approach utilizes a dynamic collection of autonomous simulations interacting with each other and with real-time data in a continuously running, distributed, real-time simulation environment. Within the ad hoc distributed simulation approach a rollback-based time synchronization method is used to allow the simulations to adapt to unanticipated changes in traffic and to changes in predictions produced by other simulations. The proposed approach is tested on a transportation network with different geographical distributions of client locations and randomized network partitioning under different traffic demand scenarios. The results demonstrate that the proposed approach has the ability to share complex traffic data among participating vehicles and process the data in an effective way to provide drivers/system monitoring with near-term traffic predictions.