Risk and Anomaly Prediction in Fully Autonomous Driving (December 2016-)
Autopilot systems will be deployed in the near future, reducing traffic accidents and mitigating traffic jams while minimizing human resources and optimizing mobility services. This projects aims at production of complete autopilot systems that continuously improve intelligence by run after run. The scope of intelligence includes not only a basic automation capability, such as perception, planning, and control, but also a prediction capability for risk of driving scenes and anomaly of the running system. We believe that risk and anomaly prediction is becoming the most significant capability to ensure safety and comfort of emerging autopilot systems. This project contributes to building their platform.
Email: crest pf.is.s.u-tokyo.ac.jp