Decentralized coordination for truck platooning

Abstract

Coordination for truck platooning refers to the active formation of a group of heavy-duty vehicles traveling at close spacing to reduce the overall truck operations costs. Conventionally, this coordination is achieved by optimizing various truck-related parameters, such as schedules, velocities, and routes, based on an objective function that minimizes a certain cost, for example, fuel usage. However, prevalent algorithms for the coordination problem are typically integer-constrained, which are not only hard to solve but are not readily scalable to increasing fleet sizes and networks. In this paper, to overcome these limitations, we propose a centralized formulation to optimize the truck parameters and solve a multidimensional objective cost function including fuel, operation time costs and preferential penalty. Furthermore, to improve the scalability of our proposed approach, we propose a decentralized algorithm for the platoon coordination problem involving multiple fleets and objectives. We perform both theoretical and numerical studies to evaluate the performance of our decentralized algorithm against the centralized solution. Our analysis indicates that the computation time of the proposed decentralized algorithms is invariant to the increasing fleet size, at the cost of a small relative gap to the optimum cost given by the centralized method. We discuss these results and present future directions for research.

Adaptive Truck Platooning with Drones: A Decentralized Approach for Highway Monitoring

“…Truck platooning [3,8] has been widely studied, aiming to improve efficiency and safety. Initial research focused on Adaptive Cruise Control (ACC) systems for maintaining safe distances between vehicles [9], while newer studies have shifted toward cooperative adaptive cruise control (CACC), exploiting vehicle-to-vehicle (V2V) communication for enabling closer truck spacing, and thereby enhancing performance [10][11][12].…”

“…Truck platooning involves a group of trucks traveling in close proximity to each other, taking advantage of the reduced air resistance and improved traffic flow. However, the current centralized approaches to truck platooning have limitations, such as reliance on infrastructure-based communication systems and the need for extensive pre-planning [3,4]. On the other hand, drones have become increasingly popular due to their versatile applications in various domains, including monitoring, surveillance, and communication [5,6].…”

Poster: Scalable Simulation of Platoon Formation Maneuvers with PlaFoSim

“…In addition to the vehicle-to-platoon assignments, the algorithms compute speed profiles, routes, and departure times [26] for the trucks in order to fulfill the desired platoons. Recently, such optimization was proposed also for trucks from multiple fleets with different objectives, utilizing the trucks' computational resources [27]. The complexity of such centralized optimization has been shown to be NP hard [22].…”

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