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In these equations, s denotes the traveled distance along the reference curve, d the lateral distance to the reference curve, t is the time and c si respectively c di are the polynomial coefficients. Others are developed with a focus on fault injection and failure analysis The SET Level project, supported by the German Federal Ministry of Economic Affairs and Climate Action, aims at providing an environment for simulation-based tests and the development of automated driving functions, which is flexible to be used for a large variety of different test objectives. Some examples of simulation frameworks with a focus on scenario-based testing of the behavior of the vehicle can be found in. For complex mechatronic systems, shifting tests to simulation means also shortening the development process and improving its flexibility.

Therefore, replacing a high quote of real driving tests with simulation leads to a major benefit for the development of automated vehicles. One of the major challenges of testing and validating automated vehicles is covering the enormous amount of possible driving situations, due to the complexity and the high number of variables of the interaction of a vehicle with the environment and other traffic agents including rare events. Furthermore, the impact of the active suspension system on lateral vehicle motion is shown. Using the presented closed-loop model chain, the effect of different actuator control strategies on ride comfort is compared, such as curve tilting. It is designed directly for use in autonomous cars and uses inputs from the vehicle motion planning subsystem for planning the suspension actuator motion. As a use case, the testing of an active suspension control system is discussed. Each subsystem can easily be exchanged to adapt the model chain with respect to the simulation objectives. It includes trajectory planning, motion control, and a model of the vehicle dynamics in a closed loop. In this paper, a modular model chain is presented, which is developed for testing systems with an impact on vehicle motion. This simulation setup must include all subsystems of the autonomous vehicle, which significantly interact with the system under test. Costs and duration of tests can be reduced if more tests can be performed numerically in a feasible simulation framework. Ensuring their functional safety and optimizing their performance requires thorough testing. Automated driving functions are expected to increase both the safety and ride comfort of future vehicles.

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