Nissan Leaf completes autonomous journey across UK
A research vehicle developed by Nissan has completed a self-navigated, autonomous journey of 370 km (230 miles) from the company's European Technical Centre in Cranfield, Bedfordshire to its manufacturing facility in Sunderland in what has been described as one of the most complex and challenging driverless car journeys ever undertaken in the UK.
The journey took place in November 2019 and marked the culmination of a closely-guarded , three-year long Nissan-led project named HumanDrive, which is aimed at developing technology that can help autonomous vehicles to drive in a more "human" manner in order to make passengers feel more comfortable with the new technology.
The £13.5-million (€16-million) initiative, which was undertaken by a Nissan-led consortium of nine industry partners and funded by the UK government's Centre for Connected and Autonomous Vehicles (CCAV), consisted of two main element: the "grand drive" from Cranfield to Sunderland and a test track-based activity that examined how AI could be further used to improve autonomous vehicle performance.
Bob Bateman, Senior Engineer at Nissan, led the project. He explained that the grand drive enabled the group to put its technology to test in one of the world’s most complex and unique road environments.
“The HumanDrive project allowed us to develop an autonomous vehicle that can tackle challenges encountered on UK roads that are unique to this part of the world, such as complex roundabouts and high-speed country lanes with no road markings, white lines or kerbs,” he said.
Enabling driverless vehicles to deal with these conditions in a way that is recognisably human is considered to be one of the keys to driving consumer confidence in the technology, he added.
“This project aimed to use advanced technologies for autonomous vehicles to try and emulate a human-like experience to ensure that the customer feels comfortable and safe. We’re trying to move from a taxi service to a luxury chauffeur surface.”
The trials used a heavily modified Nissan Leaf, with racks of computers in the boot and a range of radar, LIDAR and camera systems, as well as a highly accurate differential GPS system, that is used to build up a perception of the world around it.
Commenting on the decision to use the Leaf for the project, Nissan research engineer Chris Holmes said: “It’s our key icon for intelligent mobility research. Also electric vehicles lend themselves quite well towards utilising computers in the boot and also have nice clean electric power source for running the system.”
An additional element of the project, carried out on Nissan’s private test track, used technology developed by consortium partner Hitachi Europe Ltd to explore how real-time machine-learning AI could be used to further enhance the performance of driverless cars. Nick Blake, chief innovation strategist at Hitachi explained that this system uses a dataset of previously encountered traffic scenarios and solutions, so-called “learned experience”, to enable the vehicle to recognise and cope with future scenarios that it may encounter.
He added that through the project the group developed an easily reconfigurable AI technology that enables autonomous vehicles to have different driving styles for different people.
Other partners in the consortium included Leeds University, which helped with the simulation and evaluation of controllers that mimic human behaviour, as well as Cranfield University, Horiba and MIRA, which provided test facilities and Atkins, which developed the cybersecurity framework.
According to Bateman, there are no immediate plans to commercialise the tech developed in the project, but its findings will feed into the overarching Intelligent Mobility vision that has seen a host of driver assistance technologies introduced onto its production vehicles. He added that attention will now turn to a soon to be launched follow on project that will focus on the challenges of autonomous city driving.
Back to Homepage
Back to Transportation