The objective of this project is to harness the state-of-the-art cellular communication technologies to solve the following two well-defined problems: 1. establishing requirements on the communication to enable a safe interaction of connected autonomous vehicles (AVs) with the surrounding environment and 2. learning, and then predicting, the behavior of human road users in traffic situations.
The results expected from this project consist of a set of algorithms providing 1) the required quality of service levels in a 5G cellular network for multi-vehicle applications and 2) the predicted motion behavior of human road users (pedestrians, cyclists, drivers) in traffic situation, tracked by the 5G communication network. The algorithms will be demonstrated in experimental settings, which resemble challenging urban scenarios for self-driving vehicles and/or ADAS.
The project will last four years and consists of the following five work-packages. WP 1. Project management, exploitation and dissemination WP 2. Benchmark scenarios and requirements definition WP 3. Joint communication and control WP 4. Learning of VRUs’ behavior WP 5. Experimental validation.
Professor at Chalmers, Electrical Engineering, Systems and control, Mechatronics
Funding Chalmers participation during 2019–2023