Joint Optimization and Online Algorithms of Fuel-Aware Multi-Objective Routing for Autonomous Vehicles

Abstract

It is extremely important for autonomous vehicles to automatically complete refueling and various other tasks. However, most of the existing approaches are only suitable for conventional vehicles with large fuel tank, while the routing performance degrades, especially for electric vehicles and aerial vehicles that are constrained by small fuel capacity. This paper proposes a fuel-aware routing framework for autonomous vehicle that is employed for uninterruptedly visiting targets in logistics industry. By decoupling the topology representation and optimization process, the framework can express various optimization objectives, such as fuel consumption, trip delay and refueling cost, in a consistent way. For the fixed-path refueling problem, we propose an iterative method to improve the routing efficiency by minimizing unnecessary fuel reservation and design an efficient online solution to make trade off between routing efficiency and computation complexity. For the tour refueling problem, we propose a two-stage approach, which can simplify the routing calculation based on the solution to the fixed-path refueling problem. The simulation results demonstrate that the proposed scheme outperforms the alternative approaches in terms of both routing efficiency and computation complexity, while supporting for joint optimization of multiple objectives.