| Autor: |
Bingqing Xu, Qin Li, Tong Guo, Dehui Du |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 140566-140587 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2943184 |
| Popis: |
Considering diverse scenarios in urban traffic, the safety assessment of the decision-making process in automated driving is of great concern for years. And the difficulties of assessing safety lies in the computation of massive spatio-temporal data, the classification of scenarios, and the representation of the uncertainty in the environment with mixed traffic of manned and automated driving. Formal methods are often advocated as the way of increasing confidence in the safety-critical systems via its rigorous mathematical logic. Thus, we propose an assessment scheme which involves: i) the abstract model for decision-making, ii) characterization of composable scenarios, and iii) a corresponding formal verification method to assess safety. The abstract model captures features from the real-time observation and the estimation of the feasible driving alternatives of the surrounding vehicles, as the scenario is regarded as the dynamic evolution of the spatio-temporal data in the static road geometry over time. These features enable the specification and reasoning of the spatial guard conditions and safety properties, and also contribute to the connection and composability of the scenarios. Due to our scenario-based model verification method, we can assess the safety of decisions in scenario transitions by quantitative verification on the probability of the satisfaction of safety property through mapping from our approach to UPPAAL SMC. For illustration, case studies in the fundamental scene structures and the multi-lane roundabout are introduced. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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