Data-Driven Test Scenario Generation for Cooperative Maneuver Planning on Highways
| Autor: | Frank Diermeyer, Christian Knies |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Operations research
Computer science Plan (drawing) lcsh:Technology Data-driven Single test lcsh:Chemistry Perspective (geometry) Order (exchange) 0502 economics and business test scenarios General Materials Science Instrumentation lcsh:QH301-705.5 Road user Fluid Flow and Transfer Processes Statement (computer science) 050210 logistics & transportation lcsh:T Process Chemistry and Technology 05 social sciences General Engineering CAV lcsh:QC1-999 Computer Science Applications ddc cooperative driving lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 connected vehicles automated vehicles Scenario testing lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
| Zdroj: | Applied Sciences Volume 10 Issue 22 Applied Sciences, Vol 10, Iss 8154, p 8154 (2020) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app10228154 |
| Popis: | Future automated vehicles will have to meet the challenge of anticipating the intentions of other road users in order to plan their own behavior without compromising safety and efficiency of the surrounding road traffic. Therefore, the research area of cooperative driving deals with maneuver-planning algorithms that enable vehicles to behave cooperatively in interactive traffic scenarios. To prove the functionality of these algorithms, single test scenarios are used in the current body of literature. The use of a single, exemplary scenario bears the risk that the presented approach only works in the presented scenario and thus no general statement can be made about the performance of the algorithm. Furthermore, there is a risk that fictitious traffic scenarios may be solved which do not occur in reality. Therefore, we present a procedure for generating test scenarios based on real-world traffic datasets that require cooperation of at least one of the involved vehicles and thus are challenging from the perspective of cooperation. This procedure is applied to a large highway traffic dataset, resulting in a test scenario catalog that allows a comprehensive performance evaluation. The extracted scenarios are clustered according to the cooperative actions used to solve the respective scenario, which enables a more detailed understanding of the underlying cooperative mechanisms. In order to serve as a basis for making comparisons between different behavior planners and thus contribute to the development of future maneuver planning algorithms, a tool to extract the test scenarios from the used traffic dataset is made publicly available. |
| Databáze: | OpenAIRE |
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