Roadside tech could speed up sluggish autonomous vehicle rollout

China’s rollout already includes upgrading motorways to a level of smartness that far exceeds our efforts. For example, the recently upgraded Shanghai-Hangzhou-Ningbo Expressway includes embedded sensors that connect to a cloud computing network to monitor vehicles in real time. Sections even come with embedded wireless charging for EVs. 

The mission is partly to improve traffic speeds, with the data infrastructure eventually allowing the mass control of driverless cars to speeds of 75mph, much higher than current averages, by commanding vehicles to brake and accelerate at the same time.

Initially, the first users of autonomous-enabling roadside infrastructure in China will be lorries, UBS predicts, which are seen as delivering the biggest cost benefits for self-driving because they eliminate the drivers, which currently account for around a quarter of haulage costs, UBS estimates. Essentially, the corridors would be road versions of railways, with the autonomous lorries offloading to logistics centres and manned vehicles carrying out the final-mile delivery.

Right now, the burden for delivering autonomous vehicles lies with specialist companies such as Cruise, Argo AI, Waymo or, on the trucking side, Aurora or TuSimple. This is incredibly expensive, with little visibility of when they would ever turn a profit. Shares in US-listed Aurora and and TuSimple have dropped 80% and 70% respectively since the beginning of the year, while Argo AI laid off 150 staff in July and GM cancelled its IPO of Cruise back in March.

Roadside infrastructure would reduce their burden significantly. The bottleneck right now for independently operating self-driving cars are the vehicle sensors, which suffer blindspots. Roadside sensors would help cut those. UBS reckons China is planning to install, per kilometre, 50 cameras, 20 lidars, 20 millimetre-wave radars, 10 intelligent roadside units (with mobile connectivity), and four oxygen sensors on roads with selective autonomous driving support, with commercial adoption from around 2026.

This is where it gets tricky when looking at UK applications of a similar solution. China can pay for this by increasing road tolls, especially for commercial vehicles. We’re still debating tolls themselves, with every subsequent government kicking the debate about how we pay for road use in the future into the long grass. We’re also far more wary about the privacy issue, something that’s not up for debate for China’s heavily monitored citizens.

China’s centralised control can also mandate solutions that would entail lengthy agreements between private companies and the state in the UK and elsewhere in Europe. “Industry needs to come up with a standard way before anyone can invest in infrastructure,” said Shelley Cheshire, marketing lead for Zenzic, a government-funded organisation encouraging investment in autonomous technology in the UK.

The governmental body tasked with steering strategy in this area, the Centre for Connected and Autonomous Vehicles (CCAV), is putting the onus on the vehicle companies. “In the early days, we are expecting that automated vehicles won’t be dependent on safety-critical external infrastructure because it’s not there yet,” a source there said under condition of anonymity. “It’s a bit chicken and egg.”

That’s not to say the UK isn’t looking at infrastructure. For example, ServCity is a government-funded autonomous trial in London’s Greenwich in which six self-driving Nissan Leaf hatchbacks (manned with a back-up safety driver) drive around the busy suburb with support from a network of roadside cameras and sensors.

Meanwhile, UTAC’s Millbrook test site in Bedfordshire has a site-wide connected network that allows companies “to fail in private” when it comes to relying on external data to help autonomously controlled vehicles, as UTAC’s Stoker put it.