Cloud-Based Collision-Aware Energy-Minimization Vehicle Velocity Optimization

Abstract

In recent years, many efforts have been devoted to reducing vehicles' energy consumption through optimizing their velocities. However, all previous methods neglect avoiding vehicle collision when calculating vehicles' optimal velocity profiles. In this paper, we formulate a new problem, called the Collision-Aware vehicle Energy consumption Minimization (CAEM) problem that calculates the optimal velocity profiles which avoid vehicle collision. CAEM is more difficult to solve than the traditional velocity optimization problem that is for a single vehicle, since CAEM needs to take into account the mobility of all the vehicles together to avoid collision. This problem is a convex problem that cannot be directly solved by existing methods. Further, it is impractical to get the mobility information of all vehicles at the beginning. Even if it is feasible, the computation efficiency is very low. We propose a novel method that can tackle these challenges. In order to keep each vehicle velocity as stable as possible to reduce the energy consumption, it builds a light schematic map to help identify the green light time interval of each traffic light in the source-destination route of a vehicle, during which the vehicle must drive through the traffic light. Rather than considering the mobility of all vehicles at a time, it calculates each vehicle's velocity profile in sequence based on the starting time to prevent the vehicle from colliding with all the previously scheduled vehicles. Finally, CAEM is transformed to non-convex problem and can be solved by existing optimization methods. Simulation and real-world testbed experimental results demonstrate the superior performance of our method over the previous methods.