Scenario based methods for testing and validation of automated driving systems in virtual test environments are gaining importance and becoming an important component for verification and validation processes of automated driving systems. The high system complexity of such systems and the high testing costs lead to an exponential increase of test efforts for real world testing. Recent research works have shown that it is necessary to drive and test billions of kilometers to ensure the safety and reliability of automated driving systems. This amount of test kilometers is far from possible and achievable for any test procedure regarding the time and costs. Using different methods and procedures it is possible to reduce the number of scenarios, which should be tested to approve the safety and reliability of automated driving systems. The scenario space consisting of critical and non-critical scenarios and the test effort can be reduced to an infinite and comprehensible amount of relevant scenarios for the system under test. Using scenario and simulation based approaches this effort can be efficiently reduced concerning the costs and time. The biggest challenges hereby are the detection and selection of a suitable scenarios and simulation environments or platforms for the system under test. Besides, suitable safety metrics are essential for the detection, evaluation, and reduction of relevant scenarios for testing of automated driving systems. Current scientific work offers various strategies and approaches for generating relevant scenarios for automated driving systems. All of them have their advantages and disadvantages related to the used virtual environment, vehicle model, traffic model, and the integration complexity. This paper presents a survey through different approaches, methods, and safety metrics for scenario generation and evaluation for testing and validation of automated driving systems. The reader should get a state of the art overview on scenario based approaches of automated driving systems.
As the complexity of automated driving systemss (ADSs) with automation levels above level 3 is rising, virtual testing for such systems is inevitable and necessary. The complexity of testing these levels lies in the modeling and calculation demands for the virtual environment, which consists of roads, traffic, static and dynamic objects, as well as the modeling of the car itself. An essential part of the safety and performance analysis of ADSs is the modeling and consideration of dynamic road traffic participants. There are multiple forms of traffic flow simulation software (TFSS), which are used to reproduce realistic traffic behavior and are integrated directly or over interfaces with vehicle simulation software environments. In this paper we focus on the TFSS from PTV Vissim in a co-simulation framework which combines Vissim and CarMaker. As it is a commonly used software in industry and research, it also provides complex driver models and interfaces to manipulate and develop customized traffic participants. Using the driver model DLL interface (DMDI) from Vissim it is possible to manipulate traffic participants or adjust driver models in a defined manner. Based on the DMDI, we extended the code and developed a framework for the manipulation and testing of ADSs in the traffic environment of Vissim. The efficiency and performance of the developed software framework are evaluated using the co-simulation framework for the testing of ADSs, which is based on Vissim and CarMaker.
The increasingly used approach of combining different simulation softwares in testing of automated driving systems (ADSs) increases the need for potential and convenient software designs. Recently developed co-simulation platforms (CSPs) provide the possibility to cover the high demand for testing kilometers for ADSs by combining vehicle simulation software (VSS) with traffic flow simulation software (TFSS) environments. The emphasis on the demand for testing kilometers is not enough to choose a suitable CSP. The complexity levels of the vehicle, object, sensors, and environment models used are essential for valid and representative simulation results. Choosing a suitable CSP raises the question of how the test procedures should be defined and constructed and what the relevant test scenarios are. Parameters of the ADS, environments, objects, and sensors in the VSS, as well as traffic parameters in the TFSS, can be used to define and generate test scenarios. In order to generate a large number of scenarios in a systematic and automated way, suitable and appropriate software designs are required. In this paper, we present a software design for a CSP based on the Model–View–Controller (MVC) design pattern as well as an implementation of a complex CSP for virtual testing of ADSs. Based on this design, an implementation of a CSP is presented using the VSS from IPG Automotive (CarMaker) and the TFSS from the PTV Group (Vissim). The results showed that the presented CSP design and the implementation of the co-simulation can be used to generate relevant scenarios for testing of ADSs.
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