New standard to promote good data management practices in automated vehicle trials for safety investigations
30 March 2021
BSI, in its role as the UK National Standards Body, publishes the first consensus standard to enable data collection and management for automated vehicle trials for the purpose of incident investigation. It is the fourth publication from the CAV Standards Programme, backed by the government’s Centre for Connected and Autonomous Vehicles (CCAV) and delivered in conjunction with the Department for Transport, Department for Business, Energy and Industrial Strategy (BEIS), Innovate UK and Zenzic.
The new standard, PAS 1882:2021, Data collection and management for automated vehicle trials for the purpose of incident investigation – Specification, ensures consistency in information collection across trialling organizations and to improve safety across all trials being undertaken in the UK. The data collected by automated vehicles can provide a valuable source of information to support forensic or fact-finding investigation, key to gaining knowledge of safety issues and performing incident analysis that in-turn can build trust.
PAS 1882 specifies requirements for the collection, curation, storage and sharing of information during automated vehicle trials and advanced trials in the UK in relation to information collected or received by the system. The information requirements relate to data deemed essential to the operation of the automated driving system. This also includes information the system or trialling organization may receive, generate or hold but which is not used for the direct operation of the vehicle. The PAS includes recommendations for additional information that a trialling organization should seek to collect.
Nick Fleming, Head of Mobility and Transport Standards at BSI, said: “Data captured by automated vehicles, or driverless cars, will play an important role in promoting trust and safety improvements by enabling incident investigation and analysis. PAS 1882, contains common set of requirements for data collected in automated vehicle trials and was developed with the experts across the UK CAV eco-system. A consistent approach to data collection and management during trials showcases the UK’s commitment to safe innovation”.
David Webb, Head of Innovation at Centre for Connected and Autonomous Vehicles, said: “The Centre for Connected and Autonomous Vehicles is proud to be continuing to support the BSI CAV Standards Programme and its latest work on helping us deliver safe Connected and Automated Mobility trials on UK Roads. The deployment of CAM in the UK has the potential to make our everyday journeys greener, safer, easier and more reliable. However, they are safety-critical technologies, and we must do all we can to ensure that the deployments are as safe as possible. PAS 1882, with its focus on data collection and management to support incident investigations is a key step in doing so”.
The latest publication builds on the requirements set out in PAS 1881, Assuring the safety of automated vehicle trials and testing – Specification, which provides the safety case framework for trials by supporting operational safety assurance through the development of information requirements for incident investigation.
This standard has been produced by a steering group1 of technical experts representing organizations in the UK CAV eco-system, including automated vehicle developers, testbeds, road authorities. Burges Salmon, Loughborough University and the University of York acted as technical authors for the new PAS.
Download the free standard here: www.bsigroup.com/cav
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Notes to the editor:
Axa Insurance, Bosch, Burges Salmon, Centre for Connected and Autonomous Vehicles (CCAV), Driver and Vehicle Standards Agency (DVSA), FiveAI, Fusion Processing Ltd, Highways England, Loughborough University, National Centre for Cyber Security (NCSC), Oxbotica, Oxfordshire County Council, Society of Motor Manufacturers and Traders (SMMT), StreetDrone Ltd, Thatcham Research, TRL, University of York, Wayve Technologies Ltd, WMG, University of Warwick.