Unlike other autonomous vehicles, the focus here is not on reacting to unforeseen events in the environment, but primarily on mastering particularly high speeds – an aspect that will be of great importance later on, especially for flowing traffic on motorways. Prof. Dr. Johannes Betz, Head of the Autonomous Vehicle Systems department, explains what matters:
TUM Team Autonomous Motorsport:
“Our overarching goal is to continuously develop the existing software and prove its full potential on the racetrack. To this end, various sub-projects are being implemented, each of which contributes specifically to the overall architecture of the autonomous vehicle. The focus is on interactive trajectory planning in interaction with several vehicles at the limits of driving dynamics as well as reliable environment perception and localization at high speeds.
To achieve this goal, it is necessary to predict the behavior of competing racing vehicles precisely and in real time, while at the same time determining the dynamic limits of the driver's own vehicle. Finally, test drives with the Dallara IL-15 and the Dallara Super Formula serve to comprehensively evaluate the real-time capability, performance and reliability of the developed algorithms.”
See also the first part of our series "State of the art – research for the future of mobility":
Artificial Intelligence in Vehicle Technology
