Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios
This paper discusses ongoing work in demonstrating research in mobile autonomy in challenging driving scenarios. In our approach, we address fundamental technical issues to overcome critical barriers to assurance and regulation for largescale deployments of autonomous systems. To this end, we presen...
| Main Authors: | , , , , |
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| Formato: | Conference item |
| Idioma: | English |
| Publicado em: |
IEEE
2021
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| _version_ | 1826264008060043264 |
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| author | Gadd, M de Martini, D Marchegiani, M Newman, P Kunze, L |
| author_facet | Gadd, M de Martini, D Marchegiani, M Newman, P Kunze, L |
| author_sort | Gadd, M |
| collection | OXFORD |
| description | This paper discusses ongoing work in demonstrating
research in mobile autonomy in challenging driving scenarios.
In our approach, we address fundamental technical issues to
overcome critical barriers to assurance and regulation for largescale deployments of autonomous systems. To this end, we present
how we build robots that (1) can robustly sense and interpret
their environment using traditional as well as unconventional
sensors; (2) can assess their own capabilities; and (3), vitally in the
purpose of assurance and trust, can provide causal explanations
of their interpretations and assessments. As it is essential that
robots are safe and trusted, we design, develop, and demonstrate
fundamental technologies in real-world applications to overcome
critical barriers which impede the current deployment of robots
in economically and socially important areas. Finally, we describe
ongoing work in the collection of an unusual, rare, and highly
valuable dataset. |
| first_indexed | 2024-03-06T20:00:56Z |
| format | Conference item |
| id | oxford-uuid:274433c7-e9c5-4a71-a11d-d22ae747205b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:00:56Z |
| publishDate | 2021 |
| publisher | IEEE |
| record_format | dspace |
| spelling | oxford-uuid:274433c7-e9c5-4a71-a11d-d22ae747205b2022-03-26T12:05:58ZSense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenariosConference itemhttp://purl.org/coar/resource_type/c_5794uuid:274433c7-e9c5-4a71-a11d-d22ae747205bEnglishSymplectic ElementsIEEE2021Gadd, Mde Martini, DMarchegiani, MNewman, PKunze, LThis paper discusses ongoing work in demonstrating research in mobile autonomy in challenging driving scenarios. In our approach, we address fundamental technical issues to overcome critical barriers to assurance and regulation for largescale deployments of autonomous systems. To this end, we present how we build robots that (1) can robustly sense and interpret their environment using traditional as well as unconventional sensors; (2) can assess their own capabilities; and (3), vitally in the purpose of assurance and trust, can provide causal explanations of their interpretations and assessments. As it is essential that robots are safe and trusted, we design, develop, and demonstrate fundamental technologies in real-world applications to overcome critical barriers which impede the current deployment of robots in economically and socially important areas. Finally, we describe ongoing work in the collection of an unusual, rare, and highly valuable dataset. |
| spellingShingle | Gadd, M de Martini, D Marchegiani, M Newman, P Kunze, L Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title | Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title_full | Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title_fullStr | Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title_full_unstemmed | Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title_short | Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios |
| title_sort | sense assess explain sax building trust in autonomous vehicles in challenging real world driving scenarios |
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