December 11, 2018
15 Hurdles to Scaling for Driverless (Part 2)
by Chunka Mui
How much of what Waymo learns on Phoenix's polite streets applies to Boston's roundabouts or Beijing's pedestrian congestion?
Will driverless cars (AVs, for autonomous vehicles) live up to the revolutionary potential imagined by many, including me? In part one of this series, I asked whether AVs might develop like the Segway personal transporter and be relegated to narrow niche applications. To avoid going the way of the Segway, AV developers must overcome significant hurdles to scaling, trust, market viability and managing secondary effects.
In this article, I outline the challenges to scaling. Building and proving an AV is a big first step. Scaling AVs into industrial size and strength business operations delivering transportation as a service (TaaS) is an even bigger step. Here are seven giant hurdles related to scaling:
1. Mass production. Hand crafting or retrofitting a few thousand cars with AV technology is good enough for development and testing. Industrialization will require producing hundreds of thousands of cars at scale. But, as Tesla learned the hard way, building cars at scale is more complicated than it looks.
2. Electric charging infrastructure. Almost all AV efforts are being developed on top of electric vehicle (EV) platforms. Before EV fleets can operate at scale in any market, a whole new electric charging infrastructure must be built. This will take time and lots of money.
3. Mapping. The industrialization of the detailed, high-definition (HD) maps on which AVs depend limits where AVs can operate. Even though the cars are loaded with sensors, cameras and software, they need up-to-date maps to figure out where they are and what to do.
See also: Driverless Cars and the ’90-90 Rule’
4. Fleet management and operations. Industrialization will require flawless maintenance and efficient operation of tens of thousands of AVs widely distributed across large metropolitan service areas. Doing so will entail much more than cleaning windows and vacuuming carpets. It will entail maintaining complex computers on wheels. It will require complex predictive analytics to recharge, dispatch and load balance in response to spiky customer demand. Both public safety and business viability depend on this.
5. Customer service and experience. AV TaaS services are like a hospitality business built on a fleet of mobile hotel rooms with no on-property staff. Even the shortest trip can become arbitrarily messy and unruly—especially because there will be no human supervision in the car. Acceptable service and experience will have to extend to non-customers, as well, because AVs must interact with pedestrians, cyclists, other drivers, emergency personnel, other companies’ AVs and a host of other actors outside the car.
6. Security. Computer security is a challenging issue, in general, and networked armadas of computers on wheels will be attractive hacking targets. There are physical security issues, too. Physical security involving disgruntled drivers and bystanders, pranksters, thugs and others could also create security issues for both passengers and the public at large.
7. Rapid localization. How much of what Waymo and others are learning on the well-marked, well-lit, well-laid-out and relatively polite streets of Phoenix is transferable to the not-so-polite paved cow paths and roundabouts of Boston or the congested, pedestrian-filled city centers of New York, Paris and Beijing? Much—but not all. That is why every developer tests in multiple regions, to understand the peculiarities of local infrastructure, weather, cultural norms, etc. How fast and how well such localization can be done is another hurdle to scaling.
See also: How to Adapt to Driverless Cars
In part three of this series, I’ll explore the challenges to market acceptance. I will discuss eight industrialization hurdles that deal with trust, market viability and secondary effects.