The platooning of trucks has been considered in many studies as a potential approach to reduce some of the negative effects caused by trucking on the highways. A platoon of trucks is formed by decreasing the spacing between the trucks and adjusting their speeds at the same time. On one hand, truck platooning can have a positive effect on highway capacity by mitigating the negative effects of multiple moving bottlenecks, and can also increase the fuel efficiency of truck transportation. On the other hand, a platoon of trucks creates a long moving bottleneck, which might block the traffic and reduce the discharge rate, eventually contributing to the formation of queues. To this day, an overall picture with a full evaluation of pros and cons of platooning in terms of traffic operations is not yet available.
In this project, we have investigated the aforementioned issues, in order to fully understand the effects of platooning strategies on system-wide traffic operations on the highways. To do so, we have theoretically analyzed these effects to determine the limitations of the platooning of trucks, so it is possible to decide when and how forming platoons can improve highway traffic operations. A theoretical building block for evaluating the interactions between one or multiple bottlenecks of different sizes and car traffic was developed based on variational theory. The results have been validated using real world data (from Basel, Switzerland). Then, a framework for implementing platooning strategies along a highway was proposed. The goal of such framework is to connect a platooning algorithm (i.e. consensus algorithm for forming, modifying, and separating a platoon) and a real-time highway level management algorithm (i.e. decision algorithm to capture and respond to the interactions between a platoon of trucks and its environment as it moves along the highway). Within this framework, the platoons are formed/modified/separated as a result of the occurrence of various events (including changes in the traffic conditions) using the consensus-based algorithm. Such algorithm takes into account the constraints of each individual truck as it tries to achieve a consensus regarding optimal speed to form a platoon. The traffic interaction building block provides the basis for understanding the relation between different traffic conditions and multiple truck platooning strategies, from a traffic operations perspective. The consensus algorithm provides the control model to actually form the platoon. The overall framework is then useful for the evaluation of truck platooning strategies, and the development of guidelines for real-world implementations.