General Motors self-driving car subsidiary, Cruise Automation, is still on track to commercialize an autonomous vehicle in 2019. GM CEO Mary Barra made it clear the timeline hasn’t changed in the automaker’s second-quarter earnings call, though ultimately, safety will guide the project.
GM Cruise has taken a do-it-all approach in its self-driving car development; the technology, software and hardware all come together under one roof. And one day, the automaker may have a business case to license out the technology. When asked by an analyst during the conference call if GM would ever consider licensing out its self-driving tech, Barra responded, “we will be open to all opportunities.”
“The key thing is to get the technology developed safely so we can deploy and validate that. And once we do that, we’re going to look at any and all opportunities to really ramp up and maximize the use of the technology to drive shareholder value,” she added.
GM itself could technically become a supplier for companies and other automakers that require self-driving technology or a complete self-driving vehicle; the move would keep companies from investing their own funds into developing similar technology. Ultimately, one or a handful of companies will become defacto options.
Comments
GM should consider establishing its methods as SAE recommendations so all the future AVs can use GM’s technology. It is cheaper and faster to market AVs that uses GM’ s research investment than trying to “reinvent the wheel”.
Why share the technology? I would keep it in house!
Interesting. I can see that. Keeping it in-house goes against the greater mission of saving lives and peoples’ time. From a strategic point of view, the faster/more you get the technology safely out there, on the road, the greater the acceleration to full autonomy. Unknown edge cases surface, bugs no one has yet to think of will arise, and all the data will reinforce their trajectory planning and all other algorithms. Not to mention the better their perception and object classification algorithms will become for more data to train on. Essentially, the real competitive advantage exists there. Good luck. We’re rooting for you!