Nissan LEAF Goes On 230-Mile Fully Autonomous Drive

February 8th, 2020 by  

Nissan Beats Tesla To The Post?

The subtitle “Nissan Beats Tesla To The Post?” definitely needs the question mark in it, as, with autonomous driving, there are too many unknowns to make any definite comparisons. Not all documentations of journeys are published, and we know Tesla and Waymo have millions or billions of miles of driving data tucked away. Also, who knows when the first truly autonomous vehicle will be generally available to be used by almost anyone, anywhere?

Level 5 Autonomy?

All we can say for sure about the Nissan announcement of a 230 mile journey completed in November 2019 in an automated LEAF is that it is a record for length of an autonomous journey in the UK. It is also remarkable in that it was completed without human intervention, on all kinds of roads, including motorways (freeways) and ordinary rural roads with no markings. Many systems exist, including the current Nissan ProPilot suite, which will quite happily follow well defined lane markings on the motorway, but put it on a rural road, with no markings, and the system will go into meltdown, with too many variables to compute.

Autonomous LEAF

LEAF, on 230 mile autonomous drive.

There’s a bit of confusion, and different rating systems for that matter, regarding different levels of autonomy. If you want to know the definitions of all the levels from 0 to 5, there is a table at the end, but it is simple to explain. In level 3 the driver is ultimately responsible for driving at all times, but the autonomous system will replace the driver, controlling steering, speed, and stopping when safely delegated to do so. In level 5, the autonomous system is fully responsible at all times, and the driver is not required to intervene at all. Between those two is where, if the autonomous system can’t manage, it will safely come to the side of the road and stop, ideally. Tesla Autopilot, and all other driver assist systems, are currently between level 2 and level 3.

The drive taken by the LEAF appears to be at level 5. I say it appears to be because Nissan does not say so. A level 3 system could, theoretically, complete a drive all on its own as well, if never encountering a point where it needed human intervention. A level 4 system could complete that drive, never having to pull over and admit defeat if the route and traffic are adequate enough. They also say that a human driver took over at the service areas for charging up, but they do not say whether this was a matter of choice or lack of capability in the system. Autonomous systems depend on satellite navigation, and when I go to a service area to charge up, my satellite navigation system does not guide me all the way to the charging station. It does not guide me exactly to the point to park and plug in — I have to navigate that part myself.

So, what do we have; a level 5 system let down by the lack of mapping information at the service area, or a level 3 system which performed way beyond any other level 3 system? Whatever we define it as technically, it remains a remarkable achievement for autonomous driving.

Monitored by Engineers at All Times

Nissan say that the “Grand Drive” journey was successfully completed on 28th November 2019, with two engineers onboard and monitoring the vehicle’s actions at all times. Both were fully trained to conduct autonomous vehicle testing, with one behind the wheel and ready to take control if required and the second supervising the car’s control and monitoring systems.

Autonomous LEAF - Engineers

The engineers monitoring the systems.

The Route of “The Grand Drive”

The “Grand Drive” started from Nissan Technical Centre at Cranfield, Bedfordshire, north of London, going to Nissan in Sunderland, 230 miles further north, with 4 scheduled charging stops on the way. The achievement was the culmination of 30 months of work by the HumanDrive consortium, a team led by Nissan engineers in the UK, working in partnership with consortium members. The 230 mile journey saw the lessons learned in those 30 months put into practice in a range of driving conditions — negotiating country lanes with no or minimal road markings, junctions, roundabouts (rotaries), and motorways.

The autonomous technology changed lanes, adjusted speed, merged, stopped, and started, when necessary. Contributing to that ability were artificial intelligence systems developed by fellow consortium member Hitachi Europe Ltd, which enable real-time machine learning. By building a dataset of previously encountered traffic scenarios and solutions, it used this “learned experience” to handle similar scenarios on the journey and plot a safe route around any obstacles (no running into the back of parked police cars or fire engines, presumably).

Autonomous LEAF - Route

The route.

Aims & Objectives

Bob Bateman, Project Manager for Nissan Technical Centre in Europe, said:

“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.”

The HumanDrive collaborative project is jointly funded by the UK government through the Centre for Connected, and Autonomous Vehicles (CCAV) and by Innovate UK and nine other consortium partners. The joint funding package for the project totaled £13.5 million. It explores not just practical autonomy, but also how new technologies can make autonomous vehicle systems feel more human-like and natural.

HumanDrive also went beyond the development of autonomous driving technology to focus additionally on advancing cyber-security features in autonomous vehicles, developing testing and safety methodologies, and investigating the implications of autonomous vehicles on the wider transport system.

The Car

The test vehicle used was an older, 2nd generation Nissan LEAF, probably a 30 kWh Tekna. It is similar to my own, but featuring GPS, radar, LIDAR, and camera technologies that build up a perception of the world around it. Using that perceived world, the system can make decisions about how to navigate roads and obstacles it encounters on a journey.

Autonomous LEAF -

Autonomous LEAF. Look — no road markings, ma! Image from the press release.

The 6 Levels of Autonomy, 0–5










Human driver monitors the driving environment


No Automation

In this driving mode, there is the full-time performance by the human driver of all aspects of the dynamic driving task, even when enhanced by warning, or intervention systems





Drive Assistance

In this driving mode, there is specific execution by a driver assistance system of either steering, or acceleration/deceleration using information about the driving environment, but with the expectation that the human driver perform all remaining aspects of the dynamic driving task

Human, and Robot




Partial Automation

In this driving mode, there is specific execution by one, or more driver assistance systems of both steering, and acceleration/deceleration using information about the driving environment, but with the expectation that the human driver performs all remaining aspects of the dynamic driving task




Automated driving system monitors the driving environment


Conditional Automation

In this driving mode, there is specific performance by an automated driving system of all aspects of the dynamic driving task, but with the expectation that the human driver will respond appropriately to a request to intervene





High Automation

In this driving mode, there is specific performance by an automated driving system of all aspects of the dynamic driving task, even when a human driver does not respond appropriately to a request to intervene





Full Automation

In this driving mode, there is full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway, and environmental conditions with no requirement for any intervention by a human driver




Table data taken from Wikipedia

Human-Drive Project Consortium Members and Areas of Expertise

  1. Nissan — Lead partner, and in autonomous vehicle (AV) development.
  2. Hitachi Europe Artificial Intelligence (AI) — Provides human-like control and perception.
  3. University of Leeds — Understanding humanistic driving and its application to AVs whilst also developing a driver-risk model.
  4. Connected Places Catapult (CPC) — Project management, communications, and marketing activity, dissemination, and safety case elements of the project
  5. HORIBA MIRA — Provider of test facilities, supported safety aspects of the project.
  6. SBD Automotive — Cyber security support and AV human machine interface (HMI) studies.
  7. Cranfield University — Provider of test facilities, and supported AV demonstrations.
  8. Atkins Ltd. — Provision of a Cyber Security Framework.
  9. Aimsun Ltd. — “Studying the impact of AVs on the transport system.”
  10. Highways England — Understanding the infrastructure needs for AV deployment


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About the Author

As a child, I had the unrealistic expectation that I would learn about, and understand, absolutely everything during the course of growing up. Now, at the other end of life, I am fully aware of how much I have not learnt and do not understand, and yet, I remain interested in everything. My education, starting with an arts degree and going on to postgraduate studies in everything from computer science to hypnotism reflected my broad interests. For 20 years, I worked in local government. I am now retired, living in North Leicestershire in the UK, with plenty of time for doing whatever I like. I have always had a keen interest in everything alternative, which includes renewable energy and energy efficiency and, of course, electric vehicles. So, naturally, I have taken ownership of an EV, now that they are affordable and practical forms of transport. Writing is also one of my great pleasures, so writing about EVs and environmental issues is a natural evolution for me. You can find my work on EV Obsession, and CleanTechnica, and you can also follow me on twitter.