车辆编队行驶
Vehicle Platooning
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中文总结 AI 辅助
针对不同路段长度的道路网络，研究车辆编队的排序与重排序问题，提出算法框架，实现节能目标，启发式算法性能优异。
中文摘要 AI 辅助
车辆编队行驶具有显著优势，包括降低能耗、减少排放、提升道路利用率、增强安全性以及减轻驾驶员疲劳。随着智能驾驶技术的不断进步，编队规模预计将大幅增加，这使得车辆的高效排序与重排序愈发重要。我们研究了道路网络上的车辆编队排序与重排序问题，该网络包含不同长度的路段，考虑两个基本目标：最小化总能耗和最小化任意车辆的最大能耗。针对车辆与道路特性的典型组合，我们提供了完整的计算复杂性分类，要么开发多项式时间算法，要么证明其计算难解性。针对若干难解情形，我们设计了具有可证性能保证的 fully polynomial-time approximation scheme（完全多项式时间近似方案）和多项式时间启发式算法。计算研究表明，所提出的启发式算法得到的平均解与最优解的偏差在1%以内。我们还考虑了仅能获得与位置相关的节能信息有限的情形，并开发了具有有界最坏情况性能的启发式算法。此外，我们提出了一种高效算法，用于在仅允许有限位置变化的道路场景下进行车辆重排序。综上，这些结果为节能型车辆编队的排序与重排序提供了全面的算法框架。
英文摘要
Vehicle platooning offers significant benefits, including reduced energy consumption, lower emissions, improved road utilization, enhanced safety, and reduced driver fatigue. As intelligent driving technologies continue to advance, platoon sizes are expected to increase substantially, making the efficient sequencing and resequencing of vehicles increasingly important. We study the vehicle platoon sequencing and resequencing problem on road networks with varying segment lengths under two fundamental objectives: minimizing total energy consumption and minimizing the maximum energy consumption of any vehicle. For the typically encountered combinations of vehicle and road characteristics, we provide a complete computational complexity classification, either developing polynomial-time algorithms or proving computational intractability. For several intractable cases, we design fully polynomial-time approximation schemes and polynomial-time heuristics with provable performance guarantees. A computational study demonstrates that the proposed heuristics achieve average solutions within 1\% of optimal. We also consider settings in which only limited information about position-dependent energy savings is available and develop a heuristic with bounded worst-case performance. In addition, we present an efficient algorithm for on-road vehicle resequencing when only limited position changes are permitted. Together, these results provide a comprehensive algorithmic framework for energy-efficient vehicle platoon sequencing and resequencing.
