TEST, SAFETY & SYSTEMS
by imitation how to drive. Constant improvements can be made through this process, as the computer does not require additional programming to improve its driving. “Through this, the system learns
how to drive better and better, the same way I’m sitting in a vehicle with my daughter instructing her what she should and shouldn’t do whilst driving,” Ofir continues. “The future is mapless. No one can map the world in a resolution of 5cm as it is very costly and it will never be updated enough.” Unsupervised training gives systems
mass amounts of data and lets them lean how to operate through trial and error simulations. This can be risky and can potentially lead to a vehicle developing dangerous driving habits. On the other hand, supervised training of the system involves a person grading the decisions the vehicle makes. Supervised training can ensure
the vehicle learns best practice for driving and safe operation. “Because we are not using external
Supervised
training can ensure the vehicle learns best practice for driving and safe operation
Buses that support drive-by-wire can be retrofitted with the technology
maps but instead undertaking real- time processing, our latency, which is the most important parameter of autonomous driving, is shorter and we can respond faster to everything that happens on the road,” Ofir explains. “A system that is receiving external orders regarding how to drive on the road is prone to cyber-attacks by definition. A system that is self- sufficient will respond by itself and will not be prone to any threats from the outside.” The only external instructions
provided to the vehicle are directions, such as from Google Maps, which tells the vehicle where it needs to go, but it does not tell the vehicle what it expects to see on the road. By not using HD maps, the vehicle can detect and adapt to things that will not be
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