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Self-Driving Vehicles Testing and Operation on Public Roads in Taiwan

Time / Place:

⏱️ 10/7 (Thur.) 21:10-21:35 at Online Track 1

Abstract:

The self-driving vehicle team at MMSL, ITRI completed all requested tests at Taiwan Car Lab in Tainan in July 2019 and obtained the first permission to test self-driving vehicles on public roads in Hsinchu, Taiwan in September 2019.

The team also obtained the permissions to test self-driving buses in Taichung in October 2020 and has completed the first stage operation verification in November 2020.

This talk will describe the experiences and lessons learned from over one year public road testing and operations of self-driving vehicles in Taiwan.

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Biography:

王傑智
  • 王傑智 Chieh-Chih (Bob) Wang Website: https://robopal.tw
  • ECE, NYCU / Professor

  • Chieh-Chih (Bob) Wang received his B.S. and M.S. from National Taiwan University, and received his Ph.D. in Robotics from the School of Computer Science at Carnegie Mellon University.

    Bob was an Australian Research Council (ARC) Research Fellow of the ARC Centre of Excellence for Autonomous Systems and the Australian Centre for Field Robotics at the University of Sydney from 2004 to 2005.

    He was with the Department of Computer Science and Information Engineering and the Graduate Institute of Networking and Multimedia at National Taiwan University from 2005 to 2015.

    Dr. Wang worked at the Special Projects Group of Apple Inc from 2015 to 2016. He is currently a professor with the Department of Electrical and Computer Engineering, National Chiao Tung University and the Chief Digital Officer at Mechanical and Mechatronics Systems Research Laboratories (MMSL), Industrial Technology Research Institute (ITRI).

    Dr. Wang received the best conference paper awards at 2003 IEEE ICRA and 2010 TAAI, the best reviewer award at 2007 ACCV, NTU Teaching Excellence Award in 2014, ITRI MMSL Outstanding Innovation Awards in 2018 and 2019, and ITRI Outstanding Research Award in 2019.

    His research interests include robotics, self-driving vehicles, machine perception and machine learning.

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