Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles

Ayoosh Bansal, Jayati Singh, Micaela Verucchi, Marco Caccamo, Lui Sha

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

14 Zitate (Scopus)

Abstract

Commonly used metrics for evaluation of object detection systems (precision, recall, mAP) do not give complete information about their suitability of use in safety critical tasks, like obstacle detection for collision avoidance in Autonomous Vehicles (AV). This work introduces the Risk Ranked Recall (R3) metrics for object detection systems. The R3 metrics categorize objects within three ranks. Ranks are assigned based on an objective cyber-physical model for the risk of collision. Recall is measured for each rank.

OriginalspracheEnglisch
Titel2021 10th Mediterranean Conference on Embedded Computing, MECO 2021
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9780738133614
DOIs
PublikationsstatusVeröffentlicht - 7 Juni 2021
Veranstaltung10th Mediterranean Conference on Embedded Computing, MECO 2021 - Budva, Montenegro
Dauer: 7 Juni 202110 Juni 2021

Publikationsreihe

Name2021 10th Mediterranean Conference on Embedded Computing, MECO 2021

Konferenz

Konferenz10th Mediterranean Conference on Embedded Computing, MECO 2021
Land/GebietMontenegro
OrtBudva
Zeitraum7/06/2110/06/21

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