Toyota's Autonomous Car Test Mule Has Two Steerings
Highlights
- Toyota has equipped the test mule with a bunch of sensors
- Toyota testing various parameters to make a Level 4/5 autonomous car
- It's testing both Guardian and Chauffeur systems
Toyota Research Institute (TRI) has released a video which shows its first demonstration of the Guardian and Chauffeur autonomous vehicle platform. The video shows the advances TRI has made with Platform 2.1, the next iteration of TRI’s advanced safety research vehicle for autonomous driving. The company has been conducting several test maneuvers on a closed course. Platform 2.1 is the first research tool for testing both Guardian and Chauffeur systems on a single vehicle using the same technology stack of sensors and software.
Chauffeur is Toyota’s testing version of SAE Level 4/5 autonomy where the automated system is responsible for all driving tasks, while in Guardian mode, the automated driving system acts as a safety net for the human driver to help prevent an accident. In the Chauffeur scenario, the test vehicle’s ability to drive itself on a closed course and navigate around road obstacles was demonstrated. The system does calculations and makes a safe lane change around the stalled vehicle which is followed by the vehicle returning to the original lane.
The Guardian tests show the system’s ability to protect the vehicle and its occupants when the vehicle encounters a potentially hazardous situation and takes action if the driver does not react. The Guardian system also monitors the driver’s eyes for distracted or drowsy driving. When the vehicle ahead swerves out of the way, the Guardian system perceives the obstruction ahead and takes over for the driver to steer the car out of the way, retaining control until the driver is able to take back control of the car.
On Platform 2.1, TRI created a second vehicle control cockpit on the front passenger side with a fully operational haptic drive-by-wire steering wheel and pedals for acceleration and braking. This dual-cockpit setup allows for experimentation of effective methods to transfer vehicle control between the human driver and the autonomous system. It also supports the development of machine learning algorithms that can learn from expert human drivers and provide coaching to novice drivers.
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