Autonomous vehicle routing problem solution based on artificial potential field with parallel ant colony optimization (ACO) algorithm

作者：Yan, Fanlei^*

来源：Pattern Recognition Letters, 2018, 116: 195-199.

DOI：10.1016/j.patrec.2018.10.015

• Pilot satisfaction
• Mapreduce
• Parallel ACO
• Autonomous flight

An autonomous vehicle routing problem solution (VRPS) algorithm with parallel ant colony optimization (ACO) considering pilot satisfaction is proposed in this paper to solve the problem in traditional autonomous vehicle routing, such as the service quality is affected by longer flying time of pilot due to too much emphasis on cost factors and ignoring of delivery time. First, the flying time of pilot is considered to improve traditional autonomous flight model so as to comprehensively consider autonomous cost and pilot satisfaction. Then, for NP problems in autonomous flight, a parallel ACO algorithm is used for global optimization and design Mapreduce improvement method of parallel ACO, to improve optimization performance of the algorithm and to obtain optimal global solution. At last, a contrast experiment is conducted and the results show that, the algorithm proposed herein can effectively reduce the flying time of pilot and help to improve the service quality.

• 出版日期2018-12-1
• 单位天津工业大学