Research Article
Model Based Generation of Driving Scenarios
@INPROCEEDINGS{10.1007/978-3-319-93710-6_17, author={Thomas Hempen and Sanjana Biank and Werner Huber and Christian Diedrich}, title={Model Based Generation of Driving Scenarios}, proceedings={Intelligent Transport Systems -- From Research and Development to the Market Uptake. First International Conference, INTSYS 2017, Hyvink\aa{}\aa{}, Finland, November 29-30, 2017, Proceedings}, proceedings_a={INTSYS}, year={2018}, month={7}, keywords={Model based testing MBT Simulation Automotive testing Maneuver based testing Test case generation Test Verification Validation}, doi={10.1007/978-3-319-93710-6_17} }- Thomas Hempen
Sanjana Biank
Werner Huber
Christian Diedrich
Year: 2018
Model Based Generation of Driving Scenarios
INTSYS
Springer
DOI: 10.1007/978-3-319-93710-6_17
Abstract
For the system test of automotive safety systems, thousands of kilometers need to be driven on real roads. In the future, that number will increase significantly through higher complexity of the functions. To reduce that number and guarantee the controllability, reproducibility and increase the flexibility, a high amount of virtual driving kilometers will be done in X-in-the-Loop (XiL) tests, simulating sensors, weather conditions, vehicle dynamics, car drivers, vulnerable road users, etc. Defining these driving scenarios manually is very complex, time consuming and can not be traced to test coverage conditions. This paper presents an approach to extract simulation based driving scenarios from state based test models. Through building a test model of the requirements and expending that with scenery and maneuver information of the driving tests, it is shown, that complete driving scenarios can be generated automatically to reach every possible state of the system under test.