Simulation based approach for testing and validation of autonomous vehicles

Simulation based approach for testing and validation of autonomous vehicles

On the first glance, autonomous vehicles seem to be just a simple continuation of the development of assistance systems which help the driver keeping the lane, holding the distance to other vehicles and avoiding accidents, with the vision of avoiding 80% of all accidents, because they are mainly caused by human errors. However, there is huge challenge with respect to the requirements on system performance and reliability for this step. As Herrtwich mentioned in [1], human drivers do quite well in driving a vehicle without accident, with statistically 7.5 million km between accidents on the German Autobahn network; if an assistance system helps a driver to avoid such accidents in (just for example) 9 out of 10 times, it does a good job by reducing the number of accidents by a factor of ten. However, autonomous vehicles with SAE level 3 or higher face the challenge to avoid or control any critical situation within a statistical distance of 75 million km between accidents, in order to achieve a similar performance compared to a level 2 (driver assisted) system. That includes many situations, which have traditionally been handled by human drivers easily, but might be difficult for automation. As Winner points out in [2], it would need test driving without accidents for hundreds of millions of kilometers to prove statistically, that the risk of autonomous vehicles is low enough to argue the safe operation; this kind of straight forward system verification would not lead to a practical implementation (because of time and cost issues) and furthermore would still leave gaps in an exhaustive safety argument. As in other industries with low risk requirements (aerospace, power supply systems, automated production systems, etc.), other methods have to be used to prove the safety performance of automated vehicles [3]. System design for such systems relies on redundant subsystems with well understood, logic-based safety arguments. But functional safety (based on robust and uncorrelated subsystems) is only one part of the design; functional completeness, i.e. the proof that any conceivable situation can be handled by the system, needs a very systematical system design and thorough verification and validation procedures. For this part of the development and testing task, simulation plays an important role [4]. This paper shall focus on the goals, the required tools and components, and the approaches of simulation for development and testing of autonomous vehicles.

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