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Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Author

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  • Danish Farooq

    (Department of Transport Technology and Economics, Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary)

  • Janos Juhasz

    (Department of Transport Technology and Economics, Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary)

Abstract

Lane changing of traffic flow is a complicated and significant behavior for traffic safety on the road. Frequent lane changing can cause serious traffic safety issues, particularly on a two-lane road section of a freeway. This study aimed to analyze the effect of significant traffic parameters for traffic safety on lane change frequency using the studied calibrated values for driving logic “conscious” in VISSIM. Video-recorded traffic data were utilized to calibrate the model under specified traffic conditions, and the relationship between observed variables were estimated using simulation plots. The results revealed that changes in average desired speed and traffic volume had a positive relationship with lane change frequency. In addition, lane change frequency was observed to be higher when the speed distribution was set large. 3D surface plots were also developed to show the integrated effect of specified traffic parameters on lane change frequency. Results showed that high average desired speed and large desired speed distribution coupled with high traffic volume increased the lane change frequency tremendously. The study also attempted to develop a regression model to quantify the effect of the observed parameters on lane change frequency. The regression model results showed that desired speed distribution had the highest effect on lane change frequency compared to other traffic parameters. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency.

Suggested Citation

  • Danish Farooq & Janos Juhasz, 2019. "Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:5976-:d:280854
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    References listed on IDEAS

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    Cited by:

    1. Qiang Luo & Xiaodong Zang & Xu Cai & Huawei Gong & Jie Yuan & Junheng Yang, 2021. "Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking," Sustainability, MDPI, vol. 13(9), pages 1-16, May.
    2. Yakup Çelikbilek & Sarbast Moslem, 2023. "A grey multi criteria decision making application for analyzing the essential reasons of recurrent lane change," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 916-941, June.
    3. Danish Farooq & Sarbast Moslem & Arshad Jamal & Farhan Muhammad Butt & Yahya Almarhabi & Rana Faisal Tufail & Meshal Almoshaogeh, 2021. "Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model," IJERPH, MDPI, vol. 18(20), pages 1-17, October.
    4. Fadyushin Alexey & Zakharov Dmitrii, 2020. "Influence of the Parameters of the Bus Lane and the Bus Stop on the Delays of Private and Public Transport," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    5. Danish Farooq & Sarbast Moslem, 2022. "Estimating Driver Behavior Measures Related to Traffic Safety by Investigating 2-Dimensional Uncertain Linguistic Data—A Pythagorean Fuzzy Analytic Hierarchy Process Approach," Sustainability, MDPI, vol. 14(3), pages 1-21, February.
    6. Xu, Ting & Zhang, Zhishun & Wu, Xingqi & Qi, Long & Han, Yi, 2021. "Recognition of lane-changing behaviour with machine learning methods at freeway off-ramps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

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