Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data

Yuxiang Feng; Simon Pickering; Edward Chappell; Pejman Iravani; Chris Brace

doi:10.1007/978-3-319-93885-1_43

Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data

Yuxiang Feng, Simon Pickering, Edward Chappell, Pejman Iravani, Chris Brace

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

3 Citations (SciVal)

164 Downloads (Pure)

Abstract

With different cognitive abilities and driving style preferences, car-following behaviors can vary significantly among human drivers. To facilitate the replications of human driving behaviors on chassis dynamometer using a robot driver, this paper proposes a novel fuzzy logic driver model that attempts to perform humanized driving behaviors in the car-following regimes. An adaptive neuro-fuzzy inference system was developed to tune the fuzzy model using real driving data collected from an instrumented vehicle. Driver’s cognition parameters, such as headway distance, vehicle speed and pedal positions, were modelled as system inputs. Meanwhile, driver’s action parameters, such as pedal movements and gear selection, were selected as system outputs. Three models that possess different driving styles were calibrated using the system. Afterwards, in order to evaluate its performance of emulating human behaviors, the established fuzzy models were examined in a simulation scenario that is anchored to standard WLTC drive cycle tests.

Original language	English
Title of host publication	Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018
Publisher	Springer Verlag
Pages	481-490
Number of pages	10
ISBN (Print)	9783319938844
DOIs	https://doi.org/10.1007/978-3-319-93885-1_43
Publication status	Published - 1 Jan 2019
Event	AHFE International Conference on Human Factors in Transportation, 2018 - Orlando, USA United States Duration: 21 Jul 2018 → 25 Jul 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	786
ISSN (Print)	2194-5357

Conference

Conference	AHFE International Conference on Human Factors in Transportation, 2018
Country/Territory	USA United States
City	Orlando
Period	21/07/18 → 25/07/18

Funding

Acknowledgments. The author would like to thank University of Bath and China Scholarship Council (CSC) for their financial support to this project.

Keywords

Car-following model
Driving style simulation
Fuzzy logic
Human factors
Real driving data
WLTC

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-93885-1_43

driver modelling
This is a post-peer-review, pre-copyedit version of an article published in Advances in Human Aspects of Transportation. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-93885-1_43
Final published version, 651 KB

Cite this

Feng, Y., Pickering, S., Chappell, E., Iravani, P., & Brace, C. (2019). Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data. In Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018 (pp. 481-490). (Advances in Intelligent Systems and Computing; Vol. 786). Springer Verlag. https://doi.org/10.1007/978-3-319-93885-1_43

Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data. / Feng, Yuxiang; Pickering, Simon ; Chappell, Edward et al.
Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. Springer Verlag, 2019. p. 481-490 (Advances in Intelligent Systems and Computing; Vol. 786).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Feng, Y, Pickering, S , Chappell, E, Iravani, P & Brace, C 2019, Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data. in Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. Advances in Intelligent Systems and Computing, vol. 786, Springer Verlag, pp. 481-490, AHFE International Conference on Human Factors in Transportation, 2018, Orlando, USA United States, 21/07/18. https://doi.org/10.1007/978-3-319-93885-1_43

Feng Y, Pickering S , Chappell E, Iravani P, Brace C. Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data. In Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. Springer Verlag. 2019. p. 481-490. (Advances in Intelligent Systems and Computing). Epub 2018 Jun 28. doi: 10.1007/978-3-319-93885-1_43

Feng, Yuxiang ; Pickering, Simon ; Chappell, Edward et al. / Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data. Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. Springer Verlag, 2019. pp. 481-490 (Advances in Intelligent Systems and Computing).

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Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data

Abstract

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Keywords

ASJC Scopus subject areas

Access to Document

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