This article was written by Dr Siddartha Khastgir, Head of Verification & Validation, Intelligent Vehicles at WMG (Warwick Manufacturing Group). He recently received the prestigious UKRI Future Leaders Fellowship focussing on creating a novel evaluation continuum for connected and automated mobility (CAM). WMG, at The University of Warwick, lead the Midlands Future Mobility testbed, which is part of CAM Testbed UK and is coordinated by Zenzic.
The myth of ‘absolute safety’
Studies have suggested that we will need to drive over 11 billion miles to prove connected and self-driving vehicles are safer than those driven by humans. However, the issue here is that the number of miles travelled is not a meaningful metric to judge safety. Driving billions of miles up and down deserted roads is of limited value if you want to deploy connected and self-driving vehicles in the centre of London, San Francisco, Paris or Tokyo. While billions of dollars are being spent racking up real-world miles, focus needs to switch to the types of scenarios encountered by the vehicles, which is critically more important.
Nevertheless, due to the unbounded number of scenarios that a vehicle may encounter in its lifetime, it is unreasonable to expect they will ever be 100% responsible for our safety. As a result, the concept of ‘absolute safety’ (the possibility of injury from all possible causes as being zero) is actually a myth!
Safety is fundamental to the development of public trust and acceptance in CAM technologies, products, services and vehicles. Achieving safe deployment relies on two factors. We not only need to ensure the product is safe, but also that it is used safely. So, the question is, how do we deliver the safe deployment of connected and self-driving vehicles?
The importance of defining ODD
While absolute safety is challenging to achieve, being able to accurately define what a connected and self-driving vehicle can and cannot handle in terms of real-world scenarios is a more realistic expectation from manufacturers and developers. In order to establish their true capabilities and limitations, we need to first define its Operational Design Domain (ODD). ODD refers to the operating environment (road type, weather conditions, traffic conditions) in which a vehicle can drive safely. For example, for Low-Speed Automated Driving (LSAD) systems such as pods and shuttles, the ODD may include urban areas with predefined routes that include pedestrians and cyclists. On the other hand, for a motorway chauffer system, an ODD may include a four-lane divided motorway and dry conditions only. The types of scenarios a vehicle may encounter will be a function of its defined ODD, making this fundamental to any safety evaluation and scenario identification.
Creating ‘Informed Safety’
One of the requirements when defining an ODD is the need to be aware of each attribute used to define it. This is primarily for the vehicle to understand when it is within its defined ODD and when it is not. However, the lack of a standard set of attributes that create the definition has meant these are approached at a high level. This means evaluating safe performance of connected and self-driving vehicles is harder, as well as making informed safety more challenging due to the lack in specificity of an ODD and system capabilities.
Industry and regulators acknowledge the need for a common ODD definition methodology and taxonomy. The UK has been one of the first countries to initiate this activity through the Centre for Connected and Autonomous Vehicles (CCAV) sponsored BSI PAS 1883, which defines a taxonomy for ODD definition. Other standardisation and regulatory bodies (ISO, ASAM and UNECE – VMAD) are now also discussing definitions in their committees.
The UK’s CAV standardisation efforts
CCAV, together with Zenzic and BSI have identified the role of standards as a key enabler for accelerating CAM technology and ensuring the safe deployment of connected and self-driving vehicles in the UK. To this end, CCAV sponsored BSI’s CAV PAS programme, which will be used by developers and regulators at different stages of development to ensure connected and self-driving vehicles are safe and secure. As specified in BSI’s PAS 1881 and the TRL-led Zenzic’s Safety Case Framework, the development of a connected and self-driving vehicle starts with the identification of its system requirements, which requires defining the ODD.
BSI’s PAS 1883, which is being developed as part of this programme, provides a taxonomy for an ODD definition that lists the minimum set of attributes to define the operating environment. One of the motivations for this PAS and the corresponding ISO activity (ISO 34503), is the huge variation in the ODD definitions being created by multiple manufacturers. By serving as the technical author for BSI PAS 1883 and ISO 34503 standard on ODD, I have learned there is a need for further research focused on the measurability of ODD attributes – an area which requires a multi-disciplinary approach.
How WMG is delivering the safe future of mobility
WMG is proud to be part of the UK’s CAV standardisation efforts and are leading the development of numerous national and international standards (such as BSI PAS 1883, ISO 22737, ISO 34503). We are leveraging learnings from our involvement in UK Research and Innovation (UKRI), CCAV and Zenzic funded collaborative R&D projects such as Midlands Future Mobility, UKRI Future Leaders Fellowship, and OmniCAV to ensure future standards have foundations in strong research outputs. Standards not only enable interoperability; they also develop public trust in technology by establishing and explaining the capabilities and limitations of the technology to its users. This creates a state of informed safety.
Realising the safe future of CAM is challenging, but through knowledge sharing, strong collaboration and rigorous regulatory framework, the UK is well positioned to play an international leadership role. At WMG, we continue to collaborate globally in order to realise our mission to deliver the safe future of mobility.