A Chinese tech giant has opened up its self-driving robo-taxis to the public on the streets of Shanghai. Passengers are able to hail one of the autonomous taxis at around 150 stations throughout the city’s Jiading area, a residential and commercial part of Shanghai. As the system is currently in a testing phase, the service is free and will operate from 9.30 pm to 11 pm daily through an app.
The autonomous taxis feature a combination of lidar, radar, cameras and GPS — similar to set-ups used by other self-driving technology companies, making them capable of Level 4 autonomy. This would mean that, in most cases, the vehicle does not require human interaction and can fully drive itself. A human overseer will, nevertheless, be on standby at all times during the Shanghai trials.
Autonomous vehicles have accumulated over 8.7 million miles of testing. Its goal is to put around two hundred vehicles on Shanghai’s roads in the near future and says that it is either testing or deploying five hundred vehicles across thirty cities. Shanghai is the fifth city in which the service has been rolled out after Guangzhou, Changsha, Cangzhou and Beijing, all cities with populations over 6.5 million.
The service has also expanded to Beijing as fully driverless robo-taxis began operating last April. The robo-taxis have an operator sitting in the passenger seat, rather than behind the wheel, in order to reassure passengers. Rides in Beijing cost 30 yuan (around £3.40), though elsewhere journeys remain free, as the system is still in its testing phase.
Apart from self-driving taxis, a leading Chinese autonomous driving firm has also unveiled its latest L4-level unmanned delivery vehicles and smart solutions recently, as self-driving commercialisation is revving up in the country with faster-than-expected driverless applications.
The latest unmanned delivery vehicles have already offered delivery services in communities in foreign markets, and are able to cope with complex scenarios of open roads in urban villages, urban-rural junctions as well as downtown areas. The unmanned delivery vehicles have been applied to sectors like automobile manufacturing, hazardous chemicals, food processing, agricultural breeding, civil aviation and industrial parks.
In China, a sound unmanned distribution business model has been formed with technologies able to support different needs. The overall industry is expected to eventually enjoy large-scale commercial applications.
For some time now, domestic tech companies have been gearing up efforts in unmanned delivery services, which are expected to generate huge commercial value in a variety of businesses like express delivery, food takeaway orders, fresh produce ordering and retail pharmaceuticals.
Beijing also issued temporary self-driving license plates to 99 vehicles from 15 companies including online food delivery giants, self-driving firms and ride-hailing platforms, which marked a milestone for the commercialisation of autonomous driving.
As reported by OpenGov Asia, the Ministry of Transport (MOT) and the Ministry of Science and Technology jointly issued a guideline mapping out key transport technology based on innovation for China through 2035. The guideline emphasises making technological breakthroughs in the transport sector. It sets the goal that self-reliance on key transport technology will be achieved by 2035. Mechanisms will optimise to spur the vitality of innovative entities as much as possible. Legislation in artificial intelligence (AI), autonomous driving, and unmanned aerial vehicles (UAV) will be studied and drawn up.
Though the smart public transport service is currently limited to selected areas, they have been tried in a variety of application scenarios such as residential communities, commercial areas, and industrial parks to increase transportation efficiency and save fuel consumption.
The demonstration pioneers have been constantly fine-tuning and upgrading the systems while extending the mileage of safe operation, increasing the number of passengers, pouring investment in technology upgrading, and infrastructure construction to cope with the demand for intelligent public transport.
