Mahnam Saeednia

A Consensus-Based Algorithm for Truck Platooning

The platooning of trucks can be considered to be a potential approach to mitigate some of the negative effects that trucking can have on traffic streams. This paper proposes a cooperative distributed approach for forming/modifying platoons of trucks based on consensus algorithms. In this approach, trucks exchange information about their current status in real time, and the platoon is formed in consecutive iterations. This distributed consensus-based algorithm is compared with a centralized optimization-based algorithm for truck platooning, in which the trucks move with a set of predetermined speeds for a definite amount of time to form a platoon. The two approaches are tested and compared using various scenarios generated based on real data collected on a highway in Basel, Switzerland. Based on the results, the consensus-based algorithm proved to be a more general scheme that is able to form platoons even in cases with large initial separation of trucks. This algorithm is able to handle complex situations using its capability to form partial platoons.

Planning truck carriers operations in a cooperative environment

Abstract This paper proposes a heuristic approach for planning the activity of multiple carriers cooperating with the goal of eliminating empty truck trips while maximizing the cost saving resulting from their collaboration. The approach foresees three main phases: in the first step, the transportation demand is decomposed in two parts based on freight flows trade-off; in the second step, a linear optimization model, which takes into account compensation mechanisms among carriers, allows to combine two by two trips belonging to different carriers in order to decrease the number of empty movements. In this second phase, the importance of customers is explicitly taken into account by assigning to each trip a preference value. Finally, in the third step, a second optimization problem enables assigning, for each carrier, trucks to trips with the goal of minimizing their travel costs. The proposed heuristic approach has been tested on some instances and the results obtained are analyzed and discussed in the paper.

Analysis of Strategies for Truck Platooning: Hybrid Strategy

Trucks typically use the same infrastructure as cars do, and this imposes negative effects on the overall traffic operations. To mitigate such effects as well as their negative environmental impacts, platooning of trucks can be considered a potential solution. For platooning a set of trucks, two main strategies are typically assumed: a catch-up strategy (i.e., the upstream trucks accelerate to catch up with the leading trucks) and a slow-down strategy (i.e., the leading trucks decelerate so that the upstream trucks can catch up and platoon with them). The behavior of trucks when platooning with either of these two strategies was analyzed. Then a hybrid platooning strategy was developed that combined the two approaches in an optimal manner. The performance of the hybrid strategy was further analyzed and compared with that of the individual approaches. Results show that the hybrid strategy is the most general scheme capable of forming a platoon in various cases. Moreover, it is the fastest strategy considering the required time for platooning. In regard to performance, the hybrid strategy is capable of forming a platoon using the maximum platooning speeds of trucks. These characteristics make it a suitable strategy for large-scale deployment in truck platooning.

A Decision Support System for real-time platooning of trucks

Trucks and cars share the same type of infrastructure, i.e. highways. The presence of trucks on highways, in addition to negative environmental impacts, may result in the reduction of the highways capacity. In recent years, platooning trucks has been considered as a potential approach to mitigate such negative impacts. In spite of this, platooning trucks is not deployed in a large scale. This paper, develops a traffic evaluation building block for studying the effect of truck platoons on the system-wide traffic operations on highways using variational theory. The results of some representative scenarios show that the effectiveness of platooning strategies highly depends on the initial traffic state, as well as the characteristics of the platoon, i.e. its speed and length. Then, it proposes an event-based Decision Support System for real-time platooning of trucks on highways, based on the traffic evaluation building block.