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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.

安全粪便l 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.

安全池情景数据库将使组织能够在自己的库中创建场景，通过共享和公共图书馆与其他组织合作，并使公众能够提交具有挑战性的现实世界情景。使场景与特定环境和操作条件相匹配，这意味着可以在模拟环境，受控测试设施和公共道路上进行试验和测试，并在每个环境中使用每个环境的证据来告知我们对安全行为的理解，并带来自动驾驶汽车距离市场更近。

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.