LEAR: Robust LEArning methods for electric vehicle Route selection
Research Project, 2022
– 2026
The main focus of LEAR is on route planning for a commercial fleet of Connected Electrified Vehicles(CEVs). More specifically, the objective is to minimize energy consumption and plan charging, but also consider social aspects such as congestion, producing solutions that benefit both the fleet but also the other vehicles in the network and society in general. Extensive research efforts have been put into routing and resource allocation problems for CEVs over the years, including by the participants in this project. However, there are still several aspects that can be further studied and improved. One of them is the balance between the benefits for the fleet and for the other users of the transport network. Due to the inherent complexity of the problem, the project aims at using learning methods to provide efficient solutions. The methods developed in LEAR will provide benefits for (i) the vehicle industry (interfacing the vehicle into a network, data driven technology, mobility as a service concept), (ii) service provider (optimal resource allocation), and for the (iii) society (vehicle routing decisions involves social benefits). The project involves academia (Chalmers) and Volvo AB as core collaborative partners. However, via invitation to reference group, we incorporate perspectives from authorities, social scientists, municipality, and connected research project representatives.We believe that solving the real-time socio-strategic route coordination tasks for a fleet of CEVs is necessary to embed vehicles into a task allocation (distribution vehicles) and a traffic network (social compliance) context. Via LEAR, this step naturally comes, advancing the vehicle technology and industry to be proactive in the implementation of fleets of CEVs.
Participants
Balázs Adam Kulcsár (contact)
Chalmers, Electrical Engineering, Systems and control
Morteza Haghir Chehreghani
Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI
Attila Lischka
Chalmers, Electrical Engineering, Systems and control
Filip Rydin
Chalmers, Electrical Engineering, Systems and control
Jiaming Wu
Chalmers, Architecture and Civil Engineering, Geology and Geotechnics
Collaborations
Volvo Group
Gothenburg, Sweden
Funding
Swedish Electromobility Centre
Funding Chalmers participation during 2023–2026