The future of the eHighway system: a vision of a sustainable, climate-resilient, and artificially intelligent megaproject

Abstract Artificial intelligence (AI) can be used to support intelligent and sustainable mobility solutions. For AI to be functional, it must be supplied with reliable data. With the continuous expansion of the data base for AI, it can fill data gaps based on learning effects and thus increase data quality. The electric Highway (eHighway) system as a sustainable mobility solution for long-distance road freight transport is a megaproject where the use of AI can be helpful. As a case study for this paper, the research project ELISA (‘ELektrifizierter, Innovativer Schwerverkehr auf Autobahnen’ = ‘electrified, innovative road freight transport on motorways’) was chosen in which the eHighway has been tested on a 10 km test track in Hesse (Germany) for about 2.5 years. The data on overhead line hybrid trucks and overhead line infrastructure obtained from the project was analysed in terms of their availability and combined to the overall availability of the eHighway system. These results provided the basis for a subsequent SWOT analysis to evaluate the integrability of AI in the eHighway system. The findings from the SWOT analysis show that with the continuous improvement of data availability and quality, the use of AI in the eHighway system is feasible. Energy, cost, and operational improvements in the eHighway system are expected through the use of AI.