Towards a Universal Evaluation Model for Careful and Competent Autonomous Driving
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914893638139904 |
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| author | Reddy, Kethan Nassif, Elias Angeloudis, Panagiotis Quddus, Mohammed Ochieng, Washington |
| author_facet | Reddy, Kethan Nassif, Elias Angeloudis, Panagiotis Quddus, Mohammed Ochieng, Washington |
| contents | Virtual scenario-based testing methods to validate autonomous driving systems are predominantly centred around collision avoidance, and lack a comprehensive approach to evaluate optimal driving behaviour holistically. Furthermore, current validation approaches do not align with authorisation and monitoring requirements put forth by regulatory bodies. We address these validation gaps by outlining a universal evaluation framework that: incorporates the notion of careful and competent driving, unifies behavioural competencies and evaluation criteria, and is amenable at a scenario-specific and aggregate behaviour level. This framework can be leveraged to evaluate optimal driving in scenario-based testing, and for post-deployment monitoring to ensure continual compliance with regulation and safety standards. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15596 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards a Universal Evaluation Model for Careful and Competent Autonomous Driving Reddy, Kethan Nassif, Elias Angeloudis, Panagiotis Quddus, Mohammed Ochieng, Washington Robotics Virtual scenario-based testing methods to validate autonomous driving systems are predominantly centred around collision avoidance, and lack a comprehensive approach to evaluate optimal driving behaviour holistically. Furthermore, current validation approaches do not align with authorisation and monitoring requirements put forth by regulatory bodies. We address these validation gaps by outlining a universal evaluation framework that: incorporates the notion of careful and competent driving, unifies behavioural competencies and evaluation criteria, and is amenable at a scenario-specific and aggregate behaviour level. This framework can be leveraged to evaluate optimal driving in scenario-based testing, and for post-deployment monitoring to ensure continual compliance with regulation and safety standards. |
| title | Towards a Universal Evaluation Model for Careful and Competent Autonomous Driving |
| topic | Robotics |
| url | https://arxiv.org/abs/2407.15596 |