Coordinated route optimization for heavy-duty vehicle platoons

Abstract

Abstract-Heavy-duty vehicles traveling in platoons consume fuel at a reduced rate. In this paper, we attempt to maximize this benefit by introducing local controllers throughout a road network to facilitate platoon formations with minimal information. By knowing a vehicle's position, speed, and destination, the local controller can quickly decide how its speed should be possibly adjusted to platoon with others in the near future. We solve this optimal control and routing problem exactly for small numbers of vehicles, and present a fast heuristic algorithm for realtime use. We then implement such a distributed control system through a large-scale simulation of the German autobahn road network containing thousands of vehicles. The simulation shows fuel savings from 1-9%, with savings exceeding 5% when only a few thousand vehicles participate in the system. We assume no vehicles will travel more than the time required for their shortest paths for the majority of the paper. We conclude the results by analyzing how a relaxation of this assumption can further reduce fuel use.

The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control

“…Solutions have been proposed to aid the localization of CACC vehicles (Shladover et al, 2015), for instance, 1) infrastructure lane identification by radio frequency identification (RFID), 2) vehicle-based lane identification by on-broad sensors (e.g., GPS, inertial measurement unit, and camera), 3) vehicle-based confirmation of the predecessor by using visual or infrared-camera-visible marking, and 4) visual confirmation by the drivers. Lastly, global coordination uses advance planning to coordinate vehicles traveling with the same origin-destination pair even before the CACC vehicles entering the highway (Larson et al, 2013). The most likely application for global coordination would be long-haul trucking or lengthy commute trip on congested highways.…”

Planning of Truck Platoons: A Literature Review and Directions for Future Research

“…Liang et al (2016) adjust the speeds for two trucks to form a platoon while also taking the deadlines into account. For multi-truck platoons, they propose a pairwise matching heuristic that is similar to the one presented in Larson et al (2013) where eahc pair of trucks with 335 fuel savings are fixed as one unit in the subsequent step of the heuristic and so on. To find the savings per pair of trucks, they use a fuel model which considers the speeds in addition to topographic and vehicle characteristics.…”

“…They also introduce a simpler version of the problem called the unlimited platooning problem where the deadlines are discarded. Like Larson et al (2013), they propose a heuristic where they merge the pair of platoons with the highest savings. In addition to this best pair heuristic, 385 they also present a hub heuristic where the problem is broken down into sub-problems.…”

“…Then, they use a local search to further improve the results of both the heuristics. They test their 390 approaches on instances on a graph representing the German autobahn network similar to the one used by Larson et al (2013). For instances involving up to ten trucks, optimal solutions are generated within minutes and the heuristics produce near optimal solutions in most cases.…”

“…Instead of the optimization being repeated after a certain time, it also could be triggered by an event such as the arrival of a new entity as the system. This is the case with event-based planning and 625 is considered by Van de Hoef (2016) and Larson et al (2013) who repeat the optimization when new information becomes available.…”