标题： 车队协同行驶路径优化框架 显示英文标题

标题： Joint Travel Route Optimization Framework for Platooning

摘要： 编队代表一种先进的驾驶技术，旨在帮助驾驶员在不同长度的交通车队中行驶，提高道路安全性，减少驾驶员疲劳，并提高燃油效率。 先进的自动驾驶辅助系统促进了这一创新。 编队的最新进展强调了由车辆通信技术支持的集中式和分布式架构中的协作机制。 本研究引入了一个协作路线规划优化框架，旨在通过系统层面的集中编队形成策略促进编队的采用。 这种方法被设想为从个体（自我）驾驶到完全协作驾驶的过渡阶段。 此外，这项研究制定了与燃油消耗、驾驶员疲劳和行程时间相关的旅行成本指标，并考虑了连续驾驶时间的监管限制。 这些成本指标的性能已在网络图框架内使用Dijkstra算法和A*最短路径算法进行了评估。 结果表明，与单独的路线规划相比，所提出的架构在长途旅行中平均成本提高了14%。 显示英文摘要

摘要： Platooning represents an advanced driving technology designed to assist drivers in traffic convoys of varying lengths, enhancing road safety, reducing driver fatigue, and improving fuel efficiency. Sophisticated automated driving assistance systems have facilitated this innovation. Recent advancements in platooning emphasize cooperative mechanisms within both centralized and decentralized architectures enabled by vehicular communication technologies. This study introduces a cooperative route planning optimization framework aimed at promoting the adoption of platooning through a centralized platoon formation strategy at the system level. This approach is envisioned as a transitional phase from individual (ego) driving to fully collaborative driving. Additionally, this research formulates and incorporates travel cost metrics related to fuel consumption, driver fatigue, and travel time, considering regulatory constraints on consecutive driving durations. The performance of these cost metrics has been evaluated using Dijkstra's and A* shortest path algorithms within a network graph framework. The results indicate that the proposed architecture achieves an average cost improvement of 14 % compared to individual route planning for long road trips.