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Authors: Omar Wahbi ; Yasmin Mansy ; Nourhan Ehab and Amr Elmougy

Affiliation: German University in Cairo, Cairo, Egypt

Keyword(s): Explainable Artificial Intelligence, Self-Driving Cars, Counterfactual Explanations.

Abstract: In the current state of the art, intelligent decision-making in autonomous vehicles is not typically comprehensible by humans. This deficiency prevents this technology from becoming socially acceptable. In fact, one of the most critical challenges that autonomous vehicles face is the need for making instantaneous decisions as there are reports of self-driving cars unnecessarily hesitating and deviating when objects are detected near the vehicle, hence possibly having car accidents. As a result, gaining a thorough understanding of autonomous vehicle reported accidents is becoming increasingly important. In addition to making real-time decisions, the autonomous car AI system must be able to explain how its decisions are made. Therefore, in this paper, we propose an explanation framework capable of providing the reasons why an autonomous vehicle made a particular decision, specifically in the occurrence of a car accident. Overall, results showed that the framework generates correct expl anations for the decisions that were taken by an autonomous car by getting the nearest possible and feasible counterfactual. (More)

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Paper citation in several formats:
Wahbi, O.; Mansy, Y.; Ehab, N. and Elmougy, A. (2023). A Framework for Explaining Accident Scenarios for Self-Driving Cars. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 366-373. DOI: 10.5220/0011674000003393

@conference{icaart23,
author={Omar Wahbi. and Yasmin Mansy. and Nourhan Ehab. and Amr Elmougy.},
title={A Framework for Explaining Accident Scenarios for Self-Driving Cars},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={366-373},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011674000003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - A Framework for Explaining Accident Scenarios for Self-Driving Cars
SN - 978-989-758-623-1
IS - 2184-433X
AU - Wahbi, O.
AU - Mansy, Y.
AU - Ehab, N.
AU - Elmougy, A.
PY - 2023
SP - 366
EP - 373
DO - 10.5220/0011674000003393
PB - SciTePress

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