A massive database developed by Deepen AI and the WMG group at Warwick University is boosting testing of Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) for driverless cars.
The Safety Pool Scenario Database provides a wide range of scenarios in different operating conditions that can be used 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 hybrid methodology developed by WMG using both knowledge-based and data-based approaches.
The Safety Pool 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.
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, which is not possible in the real world. Testing on virtual roads in simulation environments is vital for manufacturers and government bodies to ensure safe behaviours and assure that driverless cars are a positive influence on road safety.
“Safety of automated driving systems is a hard research challenge and can only to solved by national and international collaboration and knowledge sharing,” said Dr Siddartha Khastgir, from WMG, University of Warwick who has been developing the database over the last seven years. “With the launch of Safety Pool 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.”
“The Safety Pool 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 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.
This will be part of the Safety Pool initiative which aims to bring together government and industry stakeholders from all over the world to work on safety standards and certifications to their country. Members of the autonomous vehicle industry can also join the Safety Pool community and access safety scenarios to transparently test, validate and benchmark ADS.
“We are thrilled to work closely with Deepen AI & WMG, University of Warwick, to launch the Safety Pool Scenario Database,” said Michelle Avary, Head of Automotive from World Economic Forum.
“We believe Safety Pool 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 database scenarios.”
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