Big achievements require big investments, and according to research firm PitchBook, autonomous vehicle (AV) startups spend $1.6M every month on average.
The lion’s share of that cost goes into testing and the infrastructure needed to support it. A single real-world autonomous prototype vehicle, outfitted with sensors and data recording gear, can cost up to $500,000. The cost of processing and storing all the data generated isn’t too far behind.
In 2017 carmakers and tech companies alike, such as GM, Hyundai, Volkswagen, and Waymo, were predicting self-driving cars would arrive by 2020, and spending big to make it happen. From August of 2014 to June of that year, automakers and tech companies invested $80B in AV technology according to a study by the Brookings Institution.
Only a year later, accidents involving self-driving prototypes seemed to cause developers to lose momentum. At the same time, the technical challenges required for Level 5 autonomy – full self-driving vehicles – have become ever more complex. By 2019 many developers were backing off of their 2020 plans.
The path to Level 5 is still ongoing and AV developers are still working on the societal improvements it will bring; but they also have some new priorities. They’ve also found new opportunities in cloud computing - which can slash costs and development times.
First, they’re refocusing on near-term paths to marketable products and services that mesh with their long-term goals: trucking and logistics, automated driver assist (ADAS) systems, and providing data insights. Some developers are building value and demonstrating real-world efficiencies right now.
“Companies like Wejo have hidden gems in their data,” says John Barrus, global business development manager for autonomous technology at Amazon Web Services (AWS). “They can partner with municipalities and provide vital information to maintain infrastructure, mapping assets like stop signs or identifying potholes and road closures. They’re just refining data they capture into value.”
Similarly, Level 4 autonomous trucking startup TuSimple launched an autonomous freight network in July. The company is demonstrating the kinds of safety and efficiency gains to be made from autonomous operation on paid cargo hauling while it refines its product in real-world testing.
Second, Barrus says, AV developers are looking to economize their existing workflows by doing more testing in virtual environments and speeding up processing and storage.
In both cases, cloud computing provides opportunities to speed up and scale development with great flexibility while making data more accessible for those nearer-term goals. COVID-19 has further accelerated existing trends toward cloud solutions.
After 2018 it became standard practice to have two people ride in every on-road AV test vehicle for safety reasons. Social distancing rules make that much more difficult, which means many AV testing fleets are currently parked.
“Many of our AV customers can’t test in the real world right now and want to do more simulation,” says Nisarg Modi, AWS’ head of worldwide business development. However, Modi adds, “If you increase your reliance on simulation but don’t have computing infrastructure ready, you’re going to burn a lot of cash.”
Barrus says that AWS sees itself as a partner for those who need computing infrastructure. “AV startups don’t need to be setting up their own hardware for computing or storage,” he adds. “It’s much more efficient to let a partner provide those pieces and turn those tasks into API calls.”