Driving Style Classification Using Deep Temporal Clustering with Enhanced Explainability
Author:
Affiliation:
1. Imperial College London,Transport Systems and Logistics Laboratory,Department of Civil and Environmental Engineering,London,U.K.,SW7 2AZ
2. Singapore Hub, Singapore-ETH Centre at CREATE,Future Cities Lab Global,Singapore,138602
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10420842/10420843/10421826.pdf?arnumber=10421826
Reference19 articles.
1. Safety of autonomous vehicles: what are the insights from experienced industry professionals?
2. Behavioral correlates of individual differences in road-traffic crash risk: An examination of methods and findings.
3. Driving Style Analysis by Classifying Real-World Data with Support Vector Clustering
4. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms
5. Driving style recognition using fuzzy logic
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