People could be driving fully automated vehicles by 2035 but getting there will involve handling vast volumes of data, creating connectivity and overcoming human distrust of computers, experts say.
鈥淲e are not looking at automobile 2.0,鈥� Silicon Valley Mobility founder and managing director Sven Beiker told a Vancouver crowd Aug. 14.
鈥淚t really is about looking at what transportation is all about.鈥�
And, what needs to be considered in that, he explained, is vehicles becoming part of the Internet for connectivity, electrification and shared vehicles 鈥� including car and ridesharing.
The benefits, the Palo Alto, California-based Beiker said, could include fewer accidents and lower economic losses as a result.
And, he said, 94% of accidents are caused by human error.
鈥淎 computer is never tired and is never distracted,鈥� he said. 鈥淔ewer accidents, fewer injuries, fewer economic losses.鈥�
Moreover, he said, automated vehicles could increase mobility for those who do not or cannot drive.
On the flip side, Beiker said, automated vehicles could put a significant number of commercial drivers out of work.
Further, he said, automakers would have to consider changing business models from individual sales to fleet sales as people potentially move away from owning cars. That could also include a shift to fleets of self-driving taxis in urban centres.
By 2030, it鈥檚 an industry that could be worth $5.5 trillion.
Now, if any of this sounds new, it鈥檚 not.
Beiker said modern cars are already marvels of technology, incorporating multiple onboard systems to assist drivers. Those include road sensors, cameras and GPS systems.
Caliber Data Labs founder and CEO Yaser Khalighi said modules on automated cars could include cameras, a form of radar, laser radar, and GPS.
Beiker explained the evolution of automated vehicles involves five stages:
鈥⒙燣evel 0 where the human does everything;
鈥⒙燣evel 聽1 with driver assistance with lane keeping and adaptive cruise control;
鈥⒙燣evel 2 with partial automation with all driving done by computer with human monitoring
鈥⒙燣evel 3 with conditional automation where the human could be disengaged but alerted when needed;
鈥⒙燣evel 4 with high automation where the human is remains plan B in emergencies,; and
鈥⒙燣evel 5 which Beiker described as a vehicle being automated 鈥渨henever, wherever, whatever the weather.鈥�
He said Tesla鈥檚 autopilot capabilities are at level 2 while Audi has created a level 3 vehicle.
鈥淟evel 4 we might see early in the 2020s,鈥� he said, noting level 5 might not be realized for 15-20 years.
What鈥檚 holding things back, Beiker explained, is regulatory advancement (which is moving), technology and connectivity coupled with the need to handle vast volumes of data generated by cars.
Traditional cars have been self-contained.
鈥淚 would call this an introverted system,鈥� Beiker said.
That will not be the case with the vehicle of the future as it interacts through sensors and the internet with the world around it.
鈥淲e need to make vehicles more extroverted,鈥� he said.
That interaction, however, means the generation of huge volumes of data. A modern vehicle creates about one gigabyte of data each hour, Beiker said. That could soon reach 350 gigabytes, he said.
And that, he explained, is going to create a 鈥渇antastic opportunity鈥� for entrepreneurs creating systems to handle such volumes.
鈥淧eople who could handle all that data could be positioned to get rich,鈥� he said.
鈥淭hose sensors create quite a bit of data,鈥� Khalighi said. 鈥淲e need a unified way to understand data through data fusion, which can be used for vehicle control.鈥�
That, Khalighi said, is where artificial intelligence comes in.
鈥淎I is heavily used to go from receiving data to control,鈥� he said. 鈥淲e use an algorithm which transforms itself and learns itself. With each addition of data it becomes smarter and smarter.鈥�
The challenges now, Khalighi said, are handling data collection, managing that data and labelling it so it is useful
Another complicating factor is society coming to an understanding of what an acceptable death rate is on roads with automated vehicles.
With humans driving, that rate is about 34,000 a year in the United States.
Khalighi said humans average an estimated one fatality per 100 million miles driven. He said automated driving data would need five billion miles to show an improvement of human capabilities. That data can be generated through actual driving or through simulations.
