Route and Speed Co-optimization for Improving Energy Consumption of Connected Vehicles

Real-time vehicle route and speed co-optimization play a vital role in improving its energy consumption with rapidly shifting traffic and environmental conditions (e.g., traffic jams, temperature, gust wind, etc.). In this article, a novel vehicle eco motion planning (VEMP) method is proposed to optimize the vehicle route and speed simultaneously for minimizing its energy usage with a given origin-destination pair and a travel time limit. The proposed VEMP method is based on the modified Dijkstra algorithm and gradient descent speed optimization to find and update the optimal route and corresponding speed profile in real-time based on changing traffic and driving environment information. Cosimulation studies are conducted for the developed VEMP method in MATLAB with the SUMO traffic model using a real-world map. The simulation results show that for the studied driving environment, the speed optimization in the VEMP method is able to reduce the energy usage by 2.27% over the case of only using speed limits on a fixed route, and the VEMP can reduce the total energy consumption by 23.83% over the fastest route created by the Dijkstra algorithm. The simulation of a sudden traffic jam demonstrates the ability of real-time updating for the proposed VEMP method to handle sudden traffic situations such as vehicle cut-in.