Data-Driven Methodology for the Investigation of Riding Dynamics: A Motorcycle Case Study
Author:
Affiliation:
1. Department of Industrial Engineering, University of Florence, Florence, Italy
2. Université Gustave Eiffel, Champs-sur-Marne, TS2/SATIE/MOSS, France
3. SATIE/MOSS, Université Paris-Saclay, ENS Paris-Saclay, CNRS, SATIE,, Gif-sur-Yvette, France
Funder
Agence Nationale de la Recherche (ANR), France, through the VIROLO++
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10235283/10122165.pdf?arnumber=10122165
Reference19 articles.
1. An Unsupervised Approach for Inferring Driver Behavior From Naturalistic Driving Data
2. Automated extraction of driver behaviour primitives using Bayesian agglomerative sequence segmentation
3. Rider skill identification by probabilistic segmentation into motorcycle maneuver primitives
4. Extraction of descriptive driving patterns from driving data using unsupervised algorithms
5. Novel high-fidelity tyre model for motorcycles to be characterised by quasi-static manoeuvres – rationale and numerical validation
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1. Understanding the behaviour of motorcycle riders: An objective investigation of riding style and capability;Transportation Research Interdisciplinary Perspectives;2023-11
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