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A Fuzzy-Logic Approach Based on Driver Decision-Making Behavior Modeling and Simulation

Author

Listed:
  • Abdulla I. M. Almadi

    (Department of Civil and Architectural Engineering, Lawrence Technological University, 21000 West Ten Mile Road, Southfield, MI 48075, USA
    Department of Civil Faculty of Technical Sciences, Sebha P.O. Box 18758, Libya)

  • Rabia Emhamed Al Mamlook

    (Industrial Engineering and Engineering Management, Western Michigan University Kalamazoo, Kalamazoo, MI 49008, USA
    Department of Aviation Engineering, Al-Zawiya University, Al-Zawiya P.O. Box 16418, Libya)

  • Yahya Almarhabi

    (Department of Surgery, Faculty of Medicine, King Abdulaziz University, Jeddah 22254, Saudi Arabia
    Center of Excellence in Trauma and Accidents, King Abdulaziz University, Jeddah 22254, Saudi Arabia)

  • Irfan Ullah

    (School of Transportation and Logistics, Dalian University of Technology, Dalian 116024, China
    Department of Business and Administration, ILMA University, Karachi 75190, Pakistan)

  • Arshad Jamal

    (Transportation and Traffic Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

  • Nishantha Bandara

    (Department of Civil and Architectural Engineering, Lawrence Technological University, 21000 West Ten Mile Road, Southfield, MI 48075, USA)

Abstract

The present study proposes a decision-making model based on different models of driver behavior, aiming to ensure integration between road safety and crash reduction based on an examination of speed limitations under weather conditions. The present study investigated differences in road safety attitude, driver behavior, and weather conditions I-69 in Flint, Genesee County, Michigan, using the fuzzy logic approach. A questionnaire-based survey was conducted among a sample of Singaporean ( n = 100) professional drivers. Safety level was assessed in relation to speed limits to determine whether the proposed speed limit contributed to a risky or safe situation. The experimental results show that the speed limits investigated on different roads/in different weather were based on the participants’ responses. The participants could increase or keep their current speed limit or reduce their speed limit a little or significantly. The study results were used to determine the speed limits needed on different roads/in different weather to reduce the number of crashes and to implement safe driving conditions based on the weather. Changing the speed limit from 80 mph to 70 mph reduced the number of crashes occurring under wet road conditions. According to the results of the fuzzy logic study algorithm, a driver’s emotions can predict outputs. For this study, the fuzzy logic algorithm evaluated drivers’ emotions according to the relation between the weather/road condition and the speed limit. The fuzzy logic would contribute to assessing a powerful feature of human control. The fuzzy logic algorithm can explain smooth relationships between the input and output. The input–output relationship estimated by fuzzy logic was used to understand differences in drivers’ feelings in varying road/weather conditions at different speed limits.

Suggested Citation

  • Abdulla I. M. Almadi & Rabia Emhamed Al Mamlook & Yahya Almarhabi & Irfan Ullah & Arshad Jamal & Nishantha Bandara, 2022. "A Fuzzy-Logic Approach Based on Driver Decision-Making Behavior Modeling and Simulation," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8874-:d:867034
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    References listed on IDEAS

    as
    1. Arshad Jamal & Waleed Umer, 2020. "Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network," IJERPH, MDPI, vol. 17(20), pages 1-22, October.
    2. Muhammad Safdar & Arshad Jamal & Hassan M. Al-Ahmadi & Muhammad Tauhidur Rahman & Meshal Almoshaogeh, 2022. "Analysis of the Influential Factors towards Adoption of Car-Sharing: A Case Study of a Megacity in a Developing Country," Sustainability, MDPI, vol. 14(5), pages 1-25, February.
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    Cited by:

    1. Guilherme Henrique Alves & Geraldo Caixeta Guimarães & Fabricio Augusto Matheus Moura, 2023. "Battery Storage Systems Control Strategies with Intelligent Algorithms in Microgrids with Dynamic Pricing," Energies, MDPI, vol. 16(14), pages 1-30, July.
    2. Muhammad Ijaz & Lan Liu & Yahya Almarhabi & Arshad Jamal & Sheikh Muhammad Usman & Muhammad Zahid, 2022. "Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 19(17), pages 1-24, August.
    3. Arshad Jamal & Muhammad Ijaz & Meshal Almosageah & Hassan M. Al-Ahmadi & Muhammad Zahid & Irfan Ullah & Rabia Emhamed Al Mamlook, 2022. "Implementing the Maximum Likelihood Method for Critical Gap Estimation under Heterogeneous Traffic Conditions," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    4. Chen, Yingda & Li, Keping & Zhang, Lun & Chen, Yili & Xiao, Xue, 2024. "Modeling and analysis of mixed traffic flow capacity and stability considering human-driven vehicle drivers' trust attitude towards intelligent connected vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).

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