- The autonomous vehicle industry faces two big challenges it needs to overcome — technology and business models that can make money, according to Michelle Avary, head of autonomous mobility at the World Economic Forum.
- Avary explained that companies in the space must ensure the technology actually works — that it can identify objects and then understand how to move around them.
- Companies also have to figure out what business model works best when it comes to self-driving cars.
Automakers and technology companies have invested billions into researching autonomous vehicles.
But the industry has two big challenges it needs to overcome before self-driving cars become widespread — technology and business models that can make money, according to Michelle Avary, head of autonomous mobility at the World Economic Forum.
"We've got a couple of big challenges in front of us. The first, obviously, is a technological challenge," Avary told CNBC's Geoff Cutmore and Arjun Kharpal at the World Economic Forum in Dalian, China.
"Really making sure that the technology is working in the areas of perception, which is vision — being able to identify objects and then understand how to move around them. That has yet to be solved."
The industry relies on collaboration and sharing of data among companies to build the technology. If the ongoing trade tensions between the U.S. and China prevent firms from sharing geography-specific datasets, Avary said it will "actually stymie the growth of the industry" and prevent companies from operating outside their own countries.
Still, Avary said, there's likely going to be more mergers and acquisitions as well as partnerships happening in the space between auto manufacturers and technology companies.
Recently, smartphone giant Apple purchased an autonomous vehicle start-up, Drive.ai, which confirmed the iPhone-maker's continued interest in self-driving car software.
"The two sides need each other and the market is enormous, so, I think there's a lot of opportunities for everyone to come out as winners," she said.
The other big challenge, according to Avary, is the business model for self-driving vehicles.
"We see some big divergence between the whole idea of the business model of the robo-taxi versus what we see in areas like commercial trucking, mining and construction, where the business model case might be more readily made," she said.
Robo-taxis refer to driverless ride-sharing services, which are being tested in various areas around the United States. Last month, Waymo, a subsidiary of Google-parent Alphabet, made some of its self-driving minivans available to customers of ride-sharing company Lyft. The latter's rival Uber is also working to deploy self-driving cars without safety drivers in limited areas.
For its part, Waymo is developing autonomous vehicles and related services, and has signed deals with Renault and Nissan to develop self-driving cars and trucks for use in France, Japan and possibly other countries in Europe and Asia.
The use of autonomous vehicles — such as trucks — to move goods on highways is a more lucrative business model compared to the so-called robo-taxis, which focus on transporting people, according to Avary.
"Even in mining and construction equipment, where we see a lot of advances in solid business case models being made in things like digging trenches for laying oil pipelines," she said, adding, "there's a lot of lucrative opportunities for automated technologies to play in these sectors."
Autonomous trucking has become a hot area for investors to back start-ups that are developing the technology for self-driving trucks. The appeal is simple: Self-driving trucks could lower the cost of shipping goods by eliminating drivers.
Amazon, for example, is reportedly using autonomous trucks developed by a company called Embark to haul some cargo on an interstate highway in the U.S.
— CNBC's Phil LeBeau contributed to this report.