Fuel-Efficient Centralized Coordination of Truck Platooning
2016 (English)Licentiate thesis, monograph (Other academic)
The problem of how to coordinate a large fleet of trucks with given itinerary to enable fuel-efficient platooning is considered. Platooning is a promising technology that enables trucks to save significant amounts of fuel by driving close together and thus reducing air drag. A setting is considered in which a fleet of trucks is provided with transport assignments consisting of a start location, a destination, a departure time and an arrival deadline from a higher planning level. Fuel-efficient plans are computed by a centralized platoon coordinator. The plans consist of routes and speed profiles that allow trucks to reach their respective destinations by their arrival deadlines. Hereby, the trucks can meet on common parts of their routes and form platoons, resulting in a decreased fuel consumption.
First, routes are computed. Then, all pairs of trucks that can potentially platoon are identified. Potential platoon pairs are identified efficiently by extracting features from the routes and processing these features. In the next step, two types of plans are computed for each vehicle: default and adapted plans. An adapted plan is such that the vehicle can meet another vehicle en route and platoon. We formulate a combinatorial optimization problem that combines these plans in order to achieve low fuel consumption. An algorithm to compute optimal solutions to this problem is developed. The optimization problem is shown to be NP-hard, which motivates us to propose a heuristic algorithm that can handle realistically sized problem instances. The resulting plans are further optimized using convex optimization. The method is evaluated with Monte Carlo simulations in a realistic setting. We demonstrate that the proposed algorithm can compute plans for thousands of trucks and that significant fuel savings can be achieved.
Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2016. , 91 p.
TRITA-EE, ISSN 1653-5146 ; 2016:074
Research subject Electrical Engineering
IdentifiersURN: urn:nbn:se:kth:diva-187500ISBN: 978-91-7729-015-5OAI: oai:DiVA.org:kth-187500DiVA: diva2:930701
2016-06-13, E3, Osquars backe 14, Stockholm, 10:00 (English)
Negenborn, Rudy, Associate Professor
Dimarogonas, Dimos V., Associate Professor
QC 201605252016-05-252016-05-252016-05-25Bibliographically approved