Lane-Level Travel Time Estimation and Space-Time Routing for Connected Vehicles with Real-Time Data at Intersections

The rapid expansion and advancement of roadside detectors has led to an abundance of traffic data, which can be directly forwarded to vehicles through V2X communication. The comprehensive dynamic real-time data brings opportunities for more precise applications to improve the traffic. Based on the real-time signal timing and queue length data before the stop bar, this study presents a method for estimating lane-level travel time varying in seconds. In addition, an algorithm for routing has been developed to compute a space–time path with the minimum travel time. To address uncertainty and randomness, the routing algorithm is embedded into a rolling horizon framework. The routing algorithm has been tested and validated using the SUMO (Simulation of Urban Mobility) simulation. The results show that, in comparison with the spatial shortest path obtained by the Dijkstra algorithm as the baseline, the proposed algorithm achieves an average reduction of 11.84% in total travel time.