Autonomous Vehicles Panel Summary
In recent years, autonomous vehicles have become a hot topic for investors worldwide. ThinkTank.vc recently hosted a panel of investors and founders to discuss the state of the market, technology trends, and challenges to watch out for. Companies represented included Toyota Research Institute, Grishin Robotics, Lux Capital, Nuro, Innoviz, Auro Robotics, Founder’s Guild, Pearl Automation and others.
To level-set, it’s worth defining the various levels of autonomy (this article does a good job).
- Level 0: this is driving as most people know it. The human controls everything.
- Level 1: the driver-assistance level, where certain functions like steering or accelerating can be done by the vehicle automatically
- Level 2: Driver doesn’t have to have hands on steering wheel or pedals, but must be ready to take over
- Level 3: Drivers still necessary but most “safety-critical” functions are shifted to the vehicle
- Level 4: Fully-autonomous, car can drive itself
- Level 5: no steering wheel in the car
Aftermarket/retrofit (incremental innovation) vs Designing for Level 5
The panelists seemed to agree that increasing capabilities incrementally is the way to go as it provides a foundation for further development. It makes sense to gain experience with a lower level of autonomy and use lessons learned to grow from there. New sensors, algorithms, and systems will eventually make their way into OEMs, similar to how safety, emissions, and in-car entertainment slowly trickled their way into the mainstream.
The question that comes up relates to Hardware — there is consensus that machines are trained on sensors, but which sensor is best to use to train the algorithm? Is it better to go for expensive sensors that allow a system to grow into them, or go for cheaper ones that enable you to get to market sooner? The latter option may seem appealing but will necessitate rewriting all prior code when the “sensor suite” becomes commoditized and drops in price.
While Tesla started with Cameras and was able to achieve Level 2/3, their hardware is now limiting them from growing further and they may face a system re-design using LIDAR. In parallel, Google made a bet that LIDAR prices will drop by the time the market is ready for autonomous vehicles, and has designed for a LIDAR system from the beginning. Participants generally agreed that Google is in a better position in this race. An article featuring a more in-depth discussion of Tesla vs Google autonomous vehicles can be found here.
Investors pointed out that in addition to autonomous vehicles, there will be many businesses that spring up around the autonomous economy: e.g., fleet operators, insurers, baggage handlers
The Autonomous Ecosystem
The autonomous market is still early and many startups are trying to position themselves for a future that should be “really big” and are leveraging VC funding until they get there. Some, like Cruise and Mobileye have already realized multi-billion-dollar outcomes, but those may be the exceptions to the rule. It’s worth noting that Mobileye took more than 15 years to build its position as a supplier to OEMs, which may be longer than some investors are willing to wait.
Startups that have a tangible business model and focus on generating revenue (e.g., Auro, Starsky, Drive.ai) will be in a good position to capitalize on the burgeoning autonomous economy. Participants gravitated towards the idea that shared mobility companies, which will operate fleets of self-driving cars, will be few and far in between: namely 2–3 (or fewer) of them would own the market. It’s also interesting to note that more niche markets outside of passenger cars may present unique investment opportunities: e.g., food delivery, materials for contractors, construction supplies.
Cities like New York, Chicago, San Francisco, and Boston are familiar with ride-sharing and are likely to see the direct impact of autonomous vehicles sooner than their rural counterparts. Urbanization will impact the transition to autonomous vehicles since many suburbs and rural areas will likely prefer to still own their cars due to convenience and cost. Furthermore, government regulation will play a big role; as regulators realize that the technology underlying autonomy has sufficiently matured and safety is guaranteed, they will be increasingly open to minimizing regulatory roadblocks and enabling mass adoption.
Investors and founders agreed that while Level 4 is feasible in the next 5 years, Level 5 will be very difficult given consumers’ low tolerance for machine-made mistakes. Industrial applications that don’t involve passengers are likely to see full autonomy quicker.
There was general optimism across participants regarding the future of autonomous vehicles, with most opportunities splitting into two buckets: enabling companies that provide systems/components (e.g., LiDAR, Radar, Computer Vision, etc.), and the service operators (i.e. the ones who actually move people, goods, and products). The major outstanding concerns relating to progress remain public sentiment (what if one company rushes to market and instills fear in the average consumer?), too much focus on improving technology without keeping in mind the broader transportation/accessibility problems, and regulations.
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Authored by Alex Malorodov