[Shinpei Kato] Risk and Anomaly Prediction in Fully Autonomous Driving

Research Director

Shinpei Kato

Shinpei Kato

The University of Tokyo
Graduate School of Information Science and Engineering
Associate Professor

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Outline

This research contributes to production of autonomous driving 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 autonomous driving technology. This research develops its platform.

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Program

Program
  • CREST
  • PRESTO
  • ERATO
  • ACCEL
  • ACT-C
  • Promoting Globalization on Strategic Basic Research Programs
  • ALCA
  • RISTEX
  • act-i
  • s_innov
  • Development of Advanced Measurement and Analysis Systemsicon
Finish programs
  • Pamphlet