Semi-controlled testing at the Culham Science Centre

The UKAEA owned Culham Science Centre is located in Oxfordshire and has some 10km of private (gated) roads and hosts approaching 2,500 tenants. As the roads are not classed as ‘the public highway’ we have been able to host trials of Level 4 self-driving vehicles¹ for in excess of 4 years with a high degree of safety throughout. During this time we have had to address what is sometimes called the self-driving vehicle paradox: arguably the greatest benefit from introducing such vehicles is improved road safety, but the single biggest challenged faced at the moment is proving that they can operate safely.

Figure 2: Culham Science centre roads (Note positions of pedestrian and pedestrian crossing)

For example in 2017 NASA launched the Space Robotics Challenge² as a virtual competition to advance robotic software and autonomous capabilities for space exploration missions on the surface of extra-terrestrial objects, such as Mars or the moon. The participants were asked to programme a NASA Valkyrie (prototype) humanoid robot to complete specified tasks using the Gazebo open-source robotics simulator³. This development in simulation, followed by implementation in ‘the real’ highlight the advantage of the approach in that the competition allowed multiple teams to look at the problem without having to queue up and take turns to utilise a scarce resource. The individual who ‘won’ the challenge was invited to implement his simulation based approach on one of only four physical Valkyrie robots, and it was reported that it took 3 hours to achieve this⁴.

However, simulation is not a panacea. The NASA challenge focused on a number of very difficult but well-defined tasks, and if the robot had been tasked with doing anything else it would have failed. This illustrates the strength of simulation where we can envisage allowing self-driving vehicles to demonstrate the ability of their systems to respond to well-defined challenges, and as such can be argued to demonstrate their ability to undertake the minimum range of manoeuvres that a robot/AI needs to be able to safely undertake. This ‘library’ can (and will) grow with time.

Figure 3: Cars on a flooded road

However, no matter how good simulators are, unexpected things happen and we need to react to the seemingly random behaviour of individuals etc. (such as the pedestrian in Figure 1). As well as individual behaviour changing, so can the physical location – for example Figure 3 shows traffic on a road in Renfrewshire⁶ following heavy rain, where successful navigation of the flood requires knowledge of both where the road is, the water depth and its impact of steering/traction etc.

Figure 4: A surface defect?

One implication of this inherent unpredictability is that it is good practice to match simulations with real-world locations contexts and with this introduce a mechanism for incorporating ‘non-routine’ scenarios into the simulated analogue. Hence, we at the Culham Science Centre are looking to OmniCAV to produce a digital twin of our site, that will help improve safety, support increased learning and extend our relevance to those testing self-driving vehicles by supporting:

Figure 5: An ‘untypical car

An emerging area where we foresee simulation playing an increasing prominent role is in exploring how a self-driving vehicle responds to unforeseen incidents. For Level 4 vehicles the presence of an always-engaged safety operator means that when a vehicle finds itself outside its defined ODD the option of handing control of the vehicle back to the on-board safety operator always exists. However, as the much discussed fatal accident involving an Uber vehicle tragically illustrated⁸ this does not always work.

The development of global standards for vehicles is guided by the work of the United Nations Economic Commission for Europe (UNECE). A body that operates under the jurisdiction of the United Nations and promotes economic cooperation and integration⁹. One area where it is currently active is in the development of policy and regulation pertaining to self-driving road vehicles. In their deliberations they are guided by the principle that “When in the automated mode, the automated/autonomous vehicle should be free of unreasonable safety risks to the driver and other road users and ensure compliance with road traffic regulations¹⁰.”

Figure 6: Dutch style roundabout in Cambridge opened August 2020

The emerging UNECE guidelines, which following a recent Law Commission consultation¹¹, look likely to be introduced into UK legislation require vehicle manufacturers to provide information to the technical service about which kind of minimum risk manoeuvres are foreseen depending on the given traffic situation. Given that it is essentially inherently dangerous to set up conditions where a vehicle needs to actively invoke a minimal risk manoeuvre. It is our expectation that simulation will play a huge role in supporting manufacturers in showing compliance with the expected legislation.

We believe that OmniCAV, with Culham as one of its physical twins, is very well placed to play a prominent role in addressing the self-driving vehicle safety paradox and in so doing help this exciting technology become a major factor in global thinking on personal mobility.