Stringent requirements in terms of vehicle safety and comfort are driving the development of networked vehicle components and systems. These work in connection and their interactions affect one another. In addition vehicle systems are increasingly connected with external sources (e.g. car-to-car, car-to-infrastructure, flashing over the air). To ensure the reliable and safe operation of such highly complex systems, data must be available at the right location and at the right time.
As a result of technologies such as driver assistance systems and automated vehicles, which have led to increased system complexity, the requirements for testing and validation have also increased. For instance, in the future it will no longer be possible to test and validate all possible driving scenarios in advance ahead of a vehicle’s launch. Instead, systems will need to be able to safely control and navigate around unexpected scenarios (such as animals on the road or stopped traffic following a bend); inadequate conditions of the vehicle surroundings (e.g. dirt, missing road markings); and even negligent or abusive operation.
Sufficient safety is only achievable within a controlled setting in the absence of variables such as unexpected hazards or inadequate conditions of the driving infrastructure. However with today’s testing methods it is not possible to cover the enormous variety of test scenarios with real-world tests. This is why there is a need for new testing methods that can demonstrate how extremely sophisticated systems are able to safely and reliably cope with unforeseen situations.
To achieve this, model-based and simulated verification and validation methods are becoming increasingly important. The most significant new testing methods are those for requirements development, automated testing, static test planning (e.g. design of experiment or functional analysis, and system technics enhanced for quantified functional analysis), and model-based testing and validation methods. Using these methods, influencers of traffic and environmental conditions are taken into account from the very start of vehicle development, and the vehicle is evaluated later on in the development process by means of systematically planned and specifically targeted testing in real-world traffic. Thus model- and simulation-based verification and validation methods offer the potential to make risks predictable as well as manageable.
Existing testing and validation processes for product safety remain relevant and applicable, however, the safety and reliability of the individual components must also still be guaranteed. The increasingly stringent and complex requirements for these systems are giving rise to a growing number of testing and validation methods, and a greater need for efficient management of these methods using simulation and models. The systematic planning and structuring of development processes is becoming an important prerequisite for vehicle development.
June 16, 2016