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Automatic detection of emergency Maneuvers, crashes, and strong jolts in naturalistic riding data from e-bicycles and e-scooters

delete2026-08-03
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OA
AI
C
Claire Naude *
E
Ebrahim Riahi
B
Bastien Canu
T
Thierry Serre
DOI:10.1016/j.aap.2026.108698delete
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Abstract

Abstract

En 中文
• Smartphone sensors detected emergency maneuvers, crashes and strong jolts. • Thresholds were derived from track tests and naturalistic riding data. • Video review confirmed the relevance of most detected events. • Rotational dynamics improved real-world crash and fall detection. • E-scooters showed more hard braking and strong jolts than e-bikes.
Keywords:
Micromobility
Performance
Vehicle dynamics
Emergency maneuver
Track test
Naturalistic data
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

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Accident Analysis and Prevention
IF:
6.2
Papers:
7.4K
Citations:
3.2W

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