Fraunhofer IAO investigates the potential of artificial intelligence for autonomous driving in fleets
How can artificial intelligence (AI) be used in vehicle fleets? How can autonomous vehicles be integrated in car sharing information and communications technology (ICT) systems? The Fraunhofer IAO project KI4ROBOFLEET is investigating the possible applications of AI in the area of autonomous driving.
AI is the backbone of autonomous systems. Self-learning systems and AI applications are currently undergoing a period of dynamic development, shifting the focus of applied research to solution strategies and application scenarios, especially in the area of autonomous driving. Scientists at the Fraunhofer Institute for Industrial Engineering IAO are now analyzing the application potential of AI in this field, incorporating experience gained in earlier research on vehicle fleets, car sharing and electro-mobility.
Autonomous fleet vehicles: Personal transportation by day, package delivery by night
The research is taking place in the KI4ROBOFLEET project, supported by the Baden-Württemberg Ministry of Economic Affairs, Labour and Housing as a part of the SME mobility initiative ‘Mittelstandsoffensive Mobilität’ (MOM). The project team is investigating the potential future uses of autonomous vehicles for car sharing and in vehicle fleets. They also intend to use expanded application scenarios to take a closer look at technical, economic and traffic-ecology aspects.
The KI4ROBOFLEET project consortium, comprising Fraunhofer IAO, Esslingen University and the SMEs Stadtmobil Rhein-Neckar AG and PAN GEO Gesellschaft für Angewandte Geographie mbH, is focusing on two key questions: What new demands must be met when autonomous vehicles are used in vehicle fleets? And what (technical) requirements will arise when this kind of vehicle is integrated in car sharing ICT systems? “We want to find ways to effectively use vehicles and fleets beyond personal transportation. It’s conceivable that the autonomous vehicle could be used as a mobile energy carrier that dynamically compensates energy peaks at companies, or as an autonomous means of transport in logistics, for example in night-time package delivery services,” says Fraunhofer IAO project manager Ilko Hoffmann.
Mobility analyses and simulations to evaluate AI technologies
By the end of 2020 the two-year project will have completed, among other things, mobility analyses at car sharing providers such as Stadtmobil in order to identify and classify possible application scenarios. The project team also plans to investigate potential applications for self-learning algorithms and AI technologies, and will perform traffic simulations to analyze and evaluate specific application scenarios. The results and requirements will then be transferred to produce a system proposal indicating which AI technologies can be applied to the integration of autonomous vehicles in car sharing fleets. At the conclusion of the project, the findings derived from the analysis and evaluation of the application scenarios will be summarized and published.
The objective of the project is to develop realistic future scenarios and to test them for application potential and technical viability.