Advances in Artificial Intelligence are making "autonomous vehicles" more responsive and smarter at making decisions
NISSAN car chiefs are overtaking the opposition in the driverless car race by taking a space-age new passenger on board – NASA.
Advances in Artificial Intelligence are making "autonomous vehicles" more responsive and smarter at making decisions.
But they can still run into a roadblock when faced with unpredictable situations like an accident or building work.
Now Nissan have announced the Seamless Autonomous Mobility (SAM) system, where the car links up with a central command centre.
An expert programmes commands into the vehicle to allow it to manoeuvre past the obstacle.
The autonomous vehicle then shares its new knowledge with other cars, so they will automatically know what to do in a similar situation.
Eugene Tu, Centre Director, NASA Ames Research Center, said: “This is not only a demonstration of the transfer of space technology to industry, but also the application of their research back to our space technology.
“It has additional uses for our unmanned aircraft systems research. This is a perfect example of technology literally driving exploration and enabling future space missions.”
Maarten Sierhuis, former NASA scientist and director of the Nissan Research Center in Silicon Valley, said: “Our goal is to change the transportation infrastructure.
“We want to reduce fatalities and ease congestion.
“We need a huge number of vehicles out there. What we are doing at Nissan is finding a way to have this transportation system not in 20 years but now.”
The system was unveiled at this year’s state-of-the-art Consumer Electronics Show (CES) in the US.
SAM ensures a seamless mobility system in which millions of autonomous cars can operate safely and smoothly.
If for instance a vehicle is moving through a city and comes across an accident, with police using hand signals to direct traffic, perhaps across double yellow lines and against traffic lights, it cannot and should not, reliably judge what to do by itself.
Vehicle sensors – cameras and radars – can tell the car where obstacles are, the traffic light state, and even recognize some hand gestures, but human judgment is needed to understand what other drivers and pedestrians are doing and decide on the appropriate course of action.
With SAM, the autonomous vehicle becomes smart enough to know when it should not attempt to negotiate the problem by itself.
Instead, it brings itself to a safe stop and requests help from the command centre.
The request is routed to the first available mobility manager – a person who uses vehicle images and sensor data to assess the situation, decide on the correct action, and create a safe path around the obstruction.
The mobility manager does this by ‘painting’ a virtual lane for the vehicle to drive itself through. When the policemen wave the vehicle past, the manager releases the car to continue on by itself along the designated route.
Once clear of the area, the vehicle resumes fully autonomous operations, and the mobility manager is free to assist other vehicles calling for assistance.
As this is all happening, other autonomous vehicles in the area are also communicating with SAM. The system learns and shares the new information created by the Mobility Manager. Once the solution is found, it’s sent to the other vehicles.
As the system learns from experience, and autonomous technology improves, vehicles will require less assistance and each mobility manager will be able to guide a large number of vehicles simultaneously.
There are several factors that will determine how many managers are necessary: for example, how busy the zone is, and what service the vehicle is providing, whether it’s for robo-taxis, robo-shuttle, or a robo-delivery vehicle.
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