Truck platooning is a promising technology for reducing energy consumption, increasing vehicle safety, and improving traffic efficiency. In this paper, we examine the cost-effectiveness of truck platooning from the perspective of a freight company fulfilling full truckload pickup and delivery requests over a transportation network. During transportation, trucks can form platoons on the traversed road sections to reduce the travel costs of the following trucks. The problem is how the routing and scheduling of trucks should be determined to take full advantage of truck platooning and minimize the total transportation cost. We propose two model formulations over a time-expanded network for this problem: a direct delivery model and an indirect delivery model, where the indirect delivery model allows trucks to visit intermediate locations during deliveries to facilitate the formation of platoons. In both models, trucks are permitted to wait at any traversed node provided that time windows of requests are not violated. We develop an improved dynamic discretization discovery (DDD) algorithm to solve the two models exactly. Through extensive computational experiments, we find that (1) the improved DDD algorithm can increase solution accuracy with much less computational effort compared with the basic DDD algorithm; (2) the cost-saving effect of truck platooning is favorable; and (3) for freight companies operating on small transportation networks, using the direct delivery model may be more appropriate.

中文翻译：

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卡车列队行驶的整车取货和送货问题


卡车列队行驶是一项很有前途的技术，可用于降低能耗、提高车辆安全性和提高交通效率。在本文中，我们从货运公司通过运输网络满足整车取货和送货请求的角度研究了卡车列队行驶的成本效益。在运输过程中，卡车可以在穿越的路段上列队行驶，以减少后续卡车的行驶成本。问题在于如何确定卡车的路线和调度，以充分利用卡车列队行驶并最大限度地降低总运输成本。针对这个问题，我们在时间扩展网络上提出了两种模型公式：直接交付模型和间接交付模型，其中间接交付模型允许卡车在交付期间访问中间位置，以促进列队的形成。在这两种模型中，只要不违反请求的时间窗口，就可以让卡车在任何遍历的节点等待。我们开发了一种改进的动态离散化发现 （DDD） 算法来精确求解这两个模型。通过大量的计算实验，我们发现 （1） 与基本的 DDD 算法相比，改进的 DDD 算法可以用更少的计算工作量提高求解精度;（2） 卡车列队行驶的节成本效果良好;（3） 对于在小型运输网络上运营的货运公司，使用直接交付模式可能更合适。