A cooperative truck platoon is a set of virtually linked trucks driving with a small intra-vehicle headway enabled by connected and automated vehicle technologies. One of the primary benefits of truck platooning is energy savings due to the reduction of aerodynamic drag on the platooned vehicles. The focus of this paper is on scheduling travel itineraries of a given set of trucks to facilitate the formation of platoons to maximize energy savings. By constructing a time-expanded network, we formulate the problem as a minimum concave-cost network flow problem, and devise a few solution methods to find the optimal or high-quality solutions. The solution methods include an outer approximation algorithm for solving a mixed-integer convex minimization reformulation of the problem, a dynamic-programming-based heuristic scalable to large-scale instances, and a fast approximation algorithm with guaranteed performance for a restrictive version of the problem. All the proposed algorithms are examined and benchmarked on medium to large networks under various test scenarios. The numerical results demonstrate the efficiency of the proposed methods and their applicability in real-world settings.

协作卡车排是一组虚拟连接的卡车，通过互联和自动化车辆技术实现小车内车距。卡车编队的主要好处之一是由于减少了编队车辆的空气阻力而节省了能源。本文的重点是安排一组给定卡车的旅行路线，以促进排队的形成，从而最大限度地节省能源。通过构建时间扩展网络，我们将问题表述为最小凹成本网络流问题，并设计了一些解决方法来寻找最优或高质量的解决方案。解决方法包括用于解决问题的混合整数凸最小化重构的外逼近算法，基于动态规划的可扩展到大规模实例的启发式算法，以及对问题的限制性版本具有保证性能的快速逼近算法。在各种测试场景下，所有提出的算法都在大中型网络上进行了检查和基准测试。数值结果证明了所提出方法的效率及其在实际环境中的适用性。