§ It’s been widely stated that for Autonomous vehicles to be road-ready they have to be tested for at least 11 billion miles

§ For this to be viable virtual road scenarios must contribute towards these miles, and WMG at the University of Warwick and Deepen AI have made a globally accessible database of scenarios for Governments, manufacturers and researchers to test their autonomous vehicle technology

§ The Safety Pool^TM Scenario Database and its role in enabling efficient testing will not only provide insights into the safety and readiness of Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS), but will also help speed up the adoption of autonomous vehicles globally by providing the largest public scenario database in the world

The Safety Pool^TM Scenario Database, the largest public repository of scenarios for testing autonomous vehicles in the world, has been launched today by WMG at the University of Warwick, and Deepen AI.

The database provides a diverse set of scenarios in different operational design domains (ODDs i.e. operating conditions) that can be leveraged by governments, industry and academia alike to test and benchmark Automated Driving Systems (ADSs) and use insights to inform policy and regulatory guidelines.

Initial scenarios have been generated using a novel hybrid methodology developed by WMG, at the University of Warwick, using both knowledge-based and data-based approaches. The Safety Pool^TM Scenario Database will allow organisations to create scenarios in their own libraries, collaborate with other organisations via both shared and public libraries and enable the public to submit challenging real world scenarios.

Enabling scenarios to be matched to specific environments and operating conditions means that trials and tests can be undertaken in the simulated environment, controlled test facilities and on public roads, with evidence from each environment being used to inform our understanding of safe behaviours, bringing Autonomous Vehicles closer to market at pace.

It is becoming ever more apparent that Autonomous Vehicles and the Connected and Automated Mobility (CAM) that they enable are one of today’s most exciting technological advances with industry, academia and governments investing in the research and development of safe and secure Autonomous Vehicles.

CAM will provide a once in a lifetime opportunity to have a global impact on societal issues around road safety, traffic efficiency and emissions.

However, to ensure that Autonomous Vehicles are road-ready and will be safer than the average human driver, it has been suggested that they must be tested on 11 billion miles of roads, an insurmountable goal in the real world. Therefore, the ability to test on virtual roads in simulation environments is paramount for manufacturers and government bodies to ensure safe behaviours and assure that Autonomous Vehicles are a positive influence on road safety. The true test of an Autonomous Vehicles will not be in just the number of miles driven, but also the quality and complexity of those miles, leading to a wide spread industry adoption of a scenario-based testing approach to ensure that the Autonomous Vehicle’s behaviours and capabilities are ready for the real world.

Dr Siddartha Khastgir, from WMG, University of Warwick, holds a UKRI Future Leaders Fellowship enabling him to create methods to test autonomous vehicles over a seven year programme, having already worked on the UK Government’s Centre for Connected and Autonomous Vehicles and Innovate UK funded Midlands Future Mobility, which offers a real-world ecosystem for development and trialling of Connected and Automated Technology as part of the Zenzic coordinated CAM Testbed UK capability and was fundamental in the development of the scenario database which forms the core of Safety Pool^TM initiative Siddartha stresses the importance of a global database of scenarios:

“Safety of automated driving systems is a hard research challenge and can only to solved by national and international collaboration and knowledge sharing. With the launch of Safety Pool^TM Scenario Database, we are inching closer to seeing automated driving systems on the roads. Testing and validating automated driving systems transparently in an integrated simulation-based framework and in real-world scenarios will not only provide insights into the readiness of ADS, but also speed up the adoption globally. WMG and MFM are grateful for the support of CCAV and Innovate UK in developing the database and we are excited to be at the forefront of this revolution.”

“The Safety Pool^TM Scenario Database lays a key foundation stone for autonomous vehicle safety” said Mohammad Musa, CEO & Co-founder of Deepen AI. “We are working closely with governments across the world to create a framework for ADS certification that will bring vehicle manufacturers one giant step closer to deploying safe and secure autonomous vehicles on the roads.”

Scenarios in Safety Pool^TM Database can be applied to a range of different autonomous vehicle systems, such as Automated Lane Keeping Systems (ALKS), which would see cars drive in an automated manner on motorways by adapting to speed and traffic around them, to trucking, to fully autonomous vehicles and even pods that could be used in town centres and pedestrianised areas as a ‘last mile’ mode of transport.

Safety Pool^TM Initiative invites stakeholders to share learnings in the form of scenarios to expedite validation, testing and certification for the entire community.

Safety Pool^TM Initiative is a global multi-stakeholder initiative with the mission of bringing transparent, certifiable safety to ADSs, uniting the autonomous vehicle community around standardised certification programs for ADSs worldwide.

Michelle Avary, Head of Automotive from World Economic Forum, comments:
“We are thrilled to work closely with Deepen AI & WMG, University of Warwick, to launch the Safety Pool^TM Scenario Database. We believe Safety Pool^TM Initiative is going to play a crucial role in standardising and bring transparency to ADS certification globally. We are already in advanced talks with many countries to adopt ADS certification frameworks based on Safety Pool^TM database scenarios.”

Richard Morris, Innovation Lead for CAV at Innovate UK, comments:

“I am very pleased that the effort and hard work of producing this scenario database has been so successful and is now gaining the recognition it deserves. Scenario testing, both in simulation and physical tests, is widely recognised as the practical route to verifying the safety of ADS, and a comprehensive scenario database is crucial for that, and we are proud to have supported this work.”

Safety Pool^TM initiative is welcoming government and industry stakeholders from all over the world to join the initiative and take the front row in bringing safety standards and certifications to their country. Members of the autonomous vehicle industry can also join the Safety Pool^TM community and access safety scenarios to transparently test, validate and benchmark ADS. Visit http://www.safetypool.ai for more information.

ENDS

31 MARCH 2021

NOTES TO EDITORS

Images - credit WMG, University of Warwick.

Image scenario 1: Agent vehicle (red on the left) is cutting into ego vehicle's (grey) lane, while another agent vehicle (red on the right) is at front right position, on a motorway in a sunset condition

Image scenario 2: Ego vehicle (in black) is overtaking agent vehicle (red) on a motorway in a sunset condition.

Video available at: https://www.youtube.com/watch?v=YjO28ode6mU (credit WMG, University of Warwick)

Please visit https://www.safetypool.ai/ for more information.

About WMG, University of Warwick

WMG is an academic department at the University of Warwick and is the leading international role model for successful collaboration between academia and the public and private sectors, driving innovation in science, technology and engineering, to develop the brightest ideas and talent that will shape our future.

www.warwick.ac.uk/fac/sci/wmg 

About Deepen

Deepen AI is a Silicon Valley based startup and the only safety-first data lifecycle tools and services company focused on machine learning and AI for autonomous systems. With tools and services that are customizable to suit the needs of enterprises as well as start-ups they have happy customers of every size across the globe. Visit Deepen.ai for more information.

About the Centre for Connected and Autonomous Vehicles

CCAV is a joint Department for Business, Energy & Industrial Strategy (BEIS) and Department for Transport (DfT) unit. Established in 2015, CCAV is an expert unit that is working with industry and academia to make everyday journeys greener, safer, more flexible and more reliable by shaping the safe and secure emergence of connected and self-driving vehicles in the UK.

Innovate UK

Innovate UK drives productivity and economic growth by supporting businesses to develop and realise the potential of new ideas, including those from the UK’s world-class research base. They connect businesses to the partners, customers and investors that can help them turn these ideas into commercially successful products and services, and business growth.