Stochastic modelling of Autonomous Vehicles Driving Scenarios using PEPA
| Autor: | Wei Chen, Leila Kloul |
|---|---|
| Přispěvatelé: | IRT SystemX (IRT SystemX), Données et algorithmes pour une ville intelligente et durable - DAVID (DAVID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Parallélisme, Réseaux, Systèmes, Modélisation (PRISM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
PEPA Stochastic modelling Computer science Distributed computing Process calculus Context (language use) 02 engineering and technology Formal methods Field (computer science) law.invention 020901 industrial engineering & automation [INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL] Order (exchange) law 0202 electrical engineering electronic engineering information engineering [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY] 020201 artificial intelligence & image processing [INFO]Computer Science [cs] Radar ComputingMilieux_MISCELLANEOUS |
| Zdroj: | International Symposium on Model-Based Safety and Assessment (IMBSA 2019) International Symposium on Model-Based Safety and Assessment (IMBSA 2019), Oct 2019, thessaloniki, Greece Model-Based Safety and Assessment ISBN: 9783030328719 IMBSA |
| Popis: | Autonomous vehicles perceive the environment with different kinds of sensors (camera, radar, lidar...). They must evolve in an unpredictable environment and a wide context of dynamic execution, with strong interactions. Therefore, ensuring the functionality and safety of the autonomous driving system has become one of the focuses of research in the field. In order to guarantee the safety of the autonomous vehicle, its occupants and the others road users, it is necessary to validate the decisions of the algorithms for all the situations that will be met by the vehicle. These situations are described and generated as different scenarios. The main objective of this work is to generate all these scenarios and find out the critical ones. Therefore, we use a scenario-generation methodology which uses the Performance Evaluation Process Algebra (PEPA) for modelling the transitions between the driving scenes. To apply our approach, we consider a running example about a riding autonomous vehicle in the context of a three-lane highway. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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