Autonomous delivery vehicles deployed in Chinese cities amid the Covid-19 pandemic

JD Logistics plans to roll out 100 of these autonomous delivery vehicles in Changshu, Jiangsu province before the end of 2020.
JD Logistics plans to roll out 100 of these autonomous delivery vehicles in Changshu, Jiangsu province before the end of 2020.ST PHOTO: DANSON CHEONG

BEIJING - For the past three months, robots have been making parcel deliveries in Changshu.

The autonomous delivery vehicles trundling around the Chinese city look like little red minivans or delivery lockers on wheels, armed with an array of sensors and cameras.

JD Logistics, the e-commerce firm that launched the delivery robots, plans to roll out 100 of these vehicles on the streets of Changsu before the end of the year.

Similar to JD, two other Chinese companies, Meituan and Cainiao, have been racing to put autonomous delivery vehicles on the road.

Covid-19 has given them a boost.

At the height of the pandemic earlier this year, these robotic couriers were deployed to coronavirus-epicentre Wuhan.

They delivered parcels to people's homes as well as to a hospital, when there was widespread fear of infection through human contact.

Their success spurred companies to speed up deployments on public roads in Changshu and elsewhere.

In a February speech, Chinese President Xi Jinping mentioned autonomous deliveries as an emerging industry for which Covid-19 had provided major opportunities.

That statement from the country's top leader spurred local governments to embrace these technologies, said JD Logistics chief scientist Kong Qi.

The company sped up deployment of the robots by half a year, and picked Changshu - a city of less than a million residents - as it was typical of many other cities in China, said Mr Kong.



JD logistics worker Wang Jie loading an autonomous delivery vehicle with parcels before it sets off on a delivery in Changshu, Jiangsu, on Oct 22, 2020. ST PHOTO: DANSON CHEONG

He added that if the Changsu deployment proved successful, deployments in other Chinese cities would follow.

Currently, the autonomous minivans handle about 70 per cent of deliveries where they operate.

They require a delivery worker to load parcels and input destinations, before they are sent out to make their deliveries.

Reaching its destination, the system notifies recipients to come out and claim their deliveries by scanning a QR code on a screen.

JD delivery worker Wang Jie, 27, said the three autonomous vehicles at his station do the work of about two delivery workers.

"This vehicle can help me reduce my workload, and I can use the extra time to collect parcels," he said.

The business case for autonomous delivery is clear - last-mile delivery can take up more than half of a parcel's delivery cost, according to a 2016 McKinsey report.

Much of that cost goes to paying an army of deliverymen like Mr Wang, who are responsible for delivering millions of parcels each day. Last year, more than 60 billion parcels were delivered in China.

Experts say this is why companies are keen to leverage autonomous driving technology.

"From the perspective of business applications and the maturing of the technology... we feel that there will be explosive growth in the next three to five years," said Mr Kong.

Other Chinese firms are also hurrying to put their robotic vehicles on the city streets.

In February, food delivery giant Meituan began piloting driverless deliveries on the outskirts of a Beijing district.

And Alibaba's logistics arm Cainiao has said it will deploy autonomous vehicles in Beijing, Hangzhou and Shenyang for the upcoming "Singles Day" online festival on Nov 11.

But Dr Luo Jun, secretary-general of the International Robotics and Intelligent Equipment Industry Alliance, pointed out the several roadblocks to widespread adoption of the technology.

Unmanned driving technology was still "not yet fully mature" and China lacked a legal framework to regulate these machines on the road, he said.

"In the event of an accident, how would you delineate responsibility?" he asked.

"This technology is basically still in the trial stage, I think it'll take another five years before we see any explosive growth."