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Self-Driving Engineer

Training Base

Playground For Engineers
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Self-driving Engineer
Training Base
End of 2019

Course Contents

Practice and test of Autoware algorithms on real cars

General course about Drive-by-wire and Car Electronics


Metal 3D printing in car manufacturing

Training and lecture of Autoware, the world's first open source autonomous driving software

Autonomous driving road tests

Complete challenges from Udacity course such as traffic light recognition, lane detection etc

Hardware Support

  • 5 self-driving development cars

  • Full set of sensors – LiDAR, industrial camera, GPS inertial navigation, millimeter wave radar, etc. 

  • Various industrial CNC machining equipment 

  • Metal 3D printing system 

  • Training venue, testing roads and setup , application scenes

  • By-wire control, vehicle retrofitting, racing events 

  • Real car Hands-on practice creating Autonomous Driving Systems with the world's first open-source software“Autoware”


The Training Site


  • 5000 square meters

  • Test site in industrial park 

The Open Road Test Site


One square kilometer's urban road In Guiyang Hi-tech district





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Alexander Carballo Segura

Autoware Software Mentor

Designated Assistant Professor at Nagoya University, Research Consultant at TierIV Inc. Doctor of Engineering (D.Eng.) in Computer Science from University of Tsukuba, Japan. Member of the Institute of Electrical and Electronics Engineers (IEEE) Robotics and Automation Society (RAS), Computer Society, and Systems, Man and Cybernetics Society. Professional Member of the Robotics Society of Japan (RSJ). Active reviewer for IEEE Int ref Intelligent Robots and Systems (IROS), also Advanced Robotics Journal and the Journal of the Robotics Society of Japan. Great research and work experiences in the autonomous driving industry. Main research interests: Human-robot interaction, social robotics, autonomous robot navigation, autonomous vehicles, robotic perception, machine learning, computer networks, unmanned aerial vehicles.

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Dowson Tseng

Vehicle Hardware Mentor

Full-stack engineer at PIX. Deep proficiency in car hardware and software. Specialized in applying software and controls into vehicles to realize autonomous driving applications in real scenarios. Majored in Automation, Dowson holds years of experience in autonomous driving and have participated in the mechanical designs of PIX Robo-vehicle and coffee car. Dowson is the main lead in the mechanical and drive-by-wire controls of PIX cars, with rich engineering experience in the autonomous driving upper system.



9:00 AM - 12:00 PM

• Comprehensive introduction: Self-driving Training Base and PIX self-driving car
• Overview: Onsite training tasks, goals and daily training contents
• Introduction: The world's first self-driving open source software - Autoware
• Warming-up: Catch up and get to know each other; 5 students form a team and choose their own car

• Safety Training Session

13:30 PM - 18:00 PM

• System and software deployment of each team
   - Tensorflow installation (GPU version)
   - Autoware installation
• Day1 summary, wrap-up and sharing


9:00 AM - 12:00 PM

• Team practice on physical car
   - Connecting sensors, opening software, collecting and mapping, and enabling the basic self-driving mobility in each team’s car

13:30 PM - 18:00 PM

Team practice on physical car, modify the Autoware source code and add the project to Autoware framework, enabling the traffic light recognition function of the course in Autoware
Day3 summary, wrap-up and sharing


9:00 AM - 12:00 PM

   - Courses of By-wire Control, Electric Vehicle Generative Design and Metal 3D Printing
   - Keep optimizing the task performances

13:30 PM - 18:00 PM

• Group JAM:  Bring out each team's creativity to realize more functions on the self-driving car under the premise of safety.
• Show & Tell from each team


9:00 AM - 12:00 PM

   - Applying Autoware On Cars, Professor Alex Segura from Nagoya University
   - Further understand Autoware framework and the relationship between each node, practice and learn map collection