Verification and validation coverage is one of the most important aspects in the journey towards automated driving. Numerous reported incidents of malfunctions during autonomous drives lead to concerns about whether the industry is ready to take self-driving vehicles mainstream. Manufacturers must first focus on mitigating the cause of the failures, which occur mainly due to the absence or lack of verification and validation coverage. Verification and validation are an integral part of system engineering, which is also a very important part of the development of autonomous vehicles.
Verification and validation cycles cover the depth and scale of test cases at all levels - unit, functional, system and integration testing, as well as testing the behaviour of the autonomous features against dynamic environment scenarios in the laboratory before they get incorporated into the vehicle. In addition, these cycles also test coverage to depth at each component level and covering the test cases against safety cases to identify malfunctions.
The need of the hour is for extremely short development cycles, which can be addressed by simulation-based validation of autonomous systems. Performance, safety and reliability of the autonomous features need to be validated on the bench. A method of achieving higher coverage is through validation of feature performance, ensuring reliability and safety against critical scenarios and utilising use cases through simulation. Creation of virtual environments to test and validate self-driving systems enables thousands of use cases and scenarios to be created and modelled. Millions of test cases get generated out of the library of use cases and tested in the virtual simulation environment. Furthermore, a closed-loop test bench on the other end can assure the closed-loop validation of the features.
Coverage of verification and validation is claimed to be the only way to assure performance of autonomous vehicles on the road. The coverage needs to be assured through both bench and road validation. A simulation-based validation methodology results in a higher level of test coverage, thereby reducing the road testing cost, along with increasing the reliability and robustness of the system.
(Inputs from KPIT)