February 15, 2017 by Canadian Underwriter
Companies aiming to deploy autonomous vehicles in the next few years are “typically” referring to vehicles that are only autonomous under certain conditions, such as good weather, a Toyota executive suggested this week to a subcommittee of the United States House of Representatives.
The Subcommittee on Digital Commerce and Consumer Protection of the House of Representatives Committee on Energy and Commerce held a hearing Tuesday on self-driving cars.
The U.S. Federal Autonomous Vehicles Policy uses SAE international definitions of automation. At SAE Level 0, the human does everything. At SAE Level 1, the automated system can sometimes assist the human on some part of the driving tasks. At SAE Level 2, the automated system can conduct some parts of the driving task but the human continues to monitor the driving environment and performs the rest of the driving task. At SAE level 3, the automated system conducts some part of the driving and monitors the driving environment in some instances but the human must be ready to take back control.
At SAE Level 4, the automated system can conduct the driving tasks and the human does not need to take back control, but the automated system can only operate in certain environments and under certain conditions.
“This may include limited areas of operation, limited speeds, limited times of day or limited weather conditions,” Gill Pratt, executive technical advisor and CEO of Toyota Research Institute, told the subcommittee Tuesday. “When companies say they intend to deploy fully autonomous vehicles in the next few years, they are typically referring to Level 4.”
SAE Level 5 is “the ability of an autonomous car to go anywhere and any time, no matter what the weather or the traffic,” Pratt said, in reply to a question from Leonard Lance, a Republican representing the 7th District of New Jersey in the House of Representatives.
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“It is going to be pretty hard to make a vehicle that is safe in all conditions, that is the Level 5 vehicle that we keep talking about and the standards may be very high because it’s a machine that’s going to be running this, not a human being,” Pratt said. “We as an industry believe it will be some time before we get to Level 5. All automakers are aiming to achieve Level 5, where the system can drive under any traffic or weather condition in any place and at any time. Although this is a wonderful goal, none of us in the automotive or information technology industries are close to achieving Level 5.”
Also appearing at the hearing was Mike Ableson, vice president of global strategy at General Motors.
“We are doing testing on public roads right now but to be honest the exact date is going to depend on how quickly the data can be gathered,” Abelson said of autonomous vehicles. “We have to prove both to ourselves and to regulators that we are ready to go driverless.”
Autonomous vehicles “are improved by the process of machine learning where computers are designed to learn better ways of behaving ,” said Nidhi Kalra, co-director and senior information scientist with the Rand Corp.’s Center for Decision Making Under Uncertainty.
“There are many ways to reduce risk, either reducing the likelihood that a crash occurs, which means restricting their operation, for example, to good weather or reducing the consequences of a crash,” said Kalra.
“Vehicle-to-vehicle as well as vehicle-to-infrastructure communication is of critical importance to autonomous vehicles,” Pratt said. “Of course we drive using our own eyes to see other vehicles. But the potential is there for autonomous vehicles to use not only the sensors on the vehicle itself, but also the sensors on neighbouring vehicles in order to see the world better. So for example if you are going around a corner, and there are trees or a building that is blocking the view, vehicle to vehicle communication can give you the equivalent of X-Ray vision, because you are seeing not only your own view, but the view from other cars as well.”
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