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Two-layer pointer model of driving style depending on the driving environment

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  • Suzdaleva, Evženie
  • Nagy, Ivan

Abstract

This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as “urban”, “rural” and “highway”. The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as “low consumption”, “middle consumption” and “high consumption”. All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them; (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model; (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data.

Suggested Citation

  • Suzdaleva, Evženie & Nagy, Ivan, 2019. "Two-layer pointer model of driving style depending on the driving environment," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 254-270.
    • Handle: RePEc:eee:transb:v:128:y:2019:i:c:p:254-270
    DOI: 10.1016/j.trb.2019.08.009
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    References listed on IDEAS

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    1. Evans, L., 1996. "The dominant role of driver behavior in traffic safety," American Journal of Public Health, American Public Health Association, vol. 86(6), pages 784-786.
    2. Rangaraju, Surendraprabu & De Vroey, Laurent & Messagie, Maarten & Mertens, Jan & Van Mierlo, Joeri, 2015. "Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study," Applied Energy, Elsevier, vol. 148(C), pages 496-505.
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    Cited by:

    1. Zhang, Ruijun & Zhao, Wanzhong & Wang, Chunyan & Tai, Kang, 2024. "Research on personalized control strategy of EHB system for consistent braking feeling considering driving behaviors," Energy, Elsevier, vol. 293(C).
    2. Josef Jablonský & Michal Černý & Juraj Pekár, 2022. "The last dozen of years of OR research in Czechia and Slovakia," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 435-447, June.
    3. Chengqun, Qiu & Wan, Xinshan & Wang, Na & Cao, Sunjia & Ji, Xinchen & Wu, Kun & Hu, Yaoyu & Meng, Mingyu, 2023. "A novel regenerative braking energy recuperation system for electric vehicles based on driving style," Energy, Elsevier, vol. 283(C).

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