On 5 January at CES in Las Vegas, Nissan Motors announced their new technology, Seamless Autonomous Mobility (SAM) that the company hopes to utilize toward getting more autonomous driving cars on the road faster.

SAM was developed by Nissan using NASA technology as a basis. Through growth of the system’s AI, the vehicle will become smarter over time thus working to improve its response time, and the system is now able to determining driving conditions in a number of different situations and environments. However, the technology is still not at a point where all decisions can be left up to the system itself, and the company is now working with how to get the vehicle to adapt and support completely unexpected situations. This issue is certainly one of the most pressing for completely autonomous driving at this stage in development. It was in this vein that Nissan began developing SAM.

The makeup of SAM is as follows. As an example, consider that you are riding in an autonomous vehicle through a metropolitan area where an accident has occurred. It is possible or even probable that a police officer will be directing traffic manually in order to keep traffic flowing around the site of the accident. In this instance, the car is not running on traffic signals but would need to follow the directions of the police officer and straddle the middle and current lanes in order to pass.

That said, the vehicle at this state cannot make these kinds of determinations due to the fact that it determines where obstacles are, what color traffic lights are, and even the movements of the police officer via laser readers, cameras, and other types of sensors. However, in order to perform the proper action at this stage, a human driver able to determine the movements of other cars and people in the surrounding area would prove necessary.

If a SAM car were to encounter a situation such as this, it would first bring the vehicle safely to a halt, and send out report to the command center. From there, the vehicle’s mobility manager which receives data from sensors monitoring the vehicle’s status, would request a correct course of action. Here, the proper response is to ignore the traffic light and move according to the police officer’s hand signals. From here, the mobility manager would indicate the proper route that the vehicle should take, and once the car had passed the police officer, the mobility manager would return the vehicle to normal autonomous driving mode where the car receives requests from other vehicles in terms of driving support.

Moreover, when an autonomous car is confronted with a problem, it stores the method of support for that issue in a cloud data bank that other cars travelling through that area can access. Via this system, autonomous cars can determine their own appropriate detours, meaning that the same support will not be required each and every time.

Regarding SAM, a Nissan representative stated that “This system is one we hope not just to outfit thousands of Nissan vehicles with but all autonomous vehicles in an effort to support safe driving when autonomous cars encounter unforeseen accidents and obstacles while driving.”

[Translated by Bryce Clarke]