基于多点协作的团队出行路径优化算法

Path optimization algorithm for team navigation based on multiple point collaboration

针对团队出行过程中因信息孤岛导致出行路径非优化和延时等待等问题,提出了一种以团队成员信息共享为基础,以集中式计算为手段的协作式路径优化算法。该算法统筹考虑成员间会合的便捷性、路径/时间最短化等多种因素基础上,通过引入团队会合优先度因子对路径计算进行加权处理,从而实现整个团队出行路径的最优化。理论分析表明,协作式路径优化算法的计算复杂度随团队成员的数量线性增长,与传统的最短路径算法计算复杂度基本相当。仿真结果表明,会合优先度因子值的高低,将会影响会合点及出行路径的选择,因此,可根据实际需求设置会合优先度因子,实现团队会合和路径最短化的动态均衡。最后,以协作式路径优化算法的一个具体的工程应用,阐述团队成员间如何提供支持和帮助,从而安全、高效和有序地到达目的地。

Concerning the path non-optimization and the delay due to mutual-waiting caused by information island in the team travel, a collaborative path optimization algorithm was proposed which employed centralized computing based on information sharing among team members. The algorithm calculated the optimum navigation path weighted by the factor of meeting priority, taking meeting convenience and path/time shortening into overall consideration. Theoretical analysis shows that the computation complexity increases linearly with the number of team members, and is approximately equal to that of the traditional path optimization algorithm. The simulation results show that the factor of meeting priority has a great influence on optimization path and meeting place. So, the factor of meeting priority needs to be set according to the actual requirement to ensure the dynamic balance between team cooperation and shortening path. A typical application solution of collaborative path optimization algorithm was given to illustrate how to support and to help each other among team members, and to travel together to the destination in order, safely and quickly.