Data-Driven Driving Skill Characterization: Algorithm Comparison and Decision Fusion

2009-01-1286

04/20/2009

Event
SAE World Congress & Exhibition
Authors Abstract
Content
By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-1286
Pages
8
Citation
Zhang, Y., Lin, W., and Chin, Y., "Data-Driven Driving Skill Characterization: Algorithm Comparison and Decision Fusion," SAE Technical Paper 2009-01-1286, 2009, https://doi.org/10.4271/2009-01-1286.
Additional Details
Publisher
Published
Apr 20, 2009
Product Code
2009-01-1286
Content Type
Technical Paper
Language
English