Abstract: Combined with the characteristics of information sharing and real-time route selection ofunmanned vehicle in the environment of intelligent network, the optimization of its routingproblem is studied. Through the introduction of key point update strategy, the path selection strategy of pre-planning and real-time adjustment for unmanned vehicle is formulated, and a two-stage VRP model based on real-time traffic information is proposed in the intelligent network connection environment. The pre-planning stage model determines the initial path, including the customer points to be served by each vehicle, The real-time adjustment model adjusts routes of each vehicle. The optimization model is solved by genetic algorithm, and the feasibility of the model and algorithm is verified by an example. The research results show that the optimization model of unmanned vehicle constructed in this paper can effectively combine the characteristics of real-time communication and route selection of unmanned vehicles, and save the delivery time. The research has certain exploration significance for the promotion and application of unmanned vehicle in the field of third-party logistics distribution.

Key words: unmanned vehicle, vehicle routing problems, optimization, path update, genetic algorithm

摘要： 结合智能网联无人车实时信息共享与路径选择的特点,研究其配送路径优化问题。通过引进关键点更新策略,制定路径预规划阶段和路径实时调整阶段无人车路径选择策略,提出智能网联环境下基于实时交通信息的车辆路径问题两阶段模型。其中,路径预规划阶段模型确定初始路径与每辆车服务的客户点,路径实时调整阶段模型对每辆车的路径实时调整。对于该优化模型设计遗传算法进行求解,并通过算例验证了模型与算法的可行性。研究结果表明,本文构建的无人车配送优化模型,有效的结合了无人车实时通信与路径选择的特点,节省了无人车配送时间。研究对于无人车在第三方物流配送领域的推广应用具有一定的探索意义。

关键词: 无人车, 车辆路径问题, 优化, 路径更新, 遗传算法