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Car following theory with lateral discomfort

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  • Gunay, Banihan

Abstract

A car following model has been developed with particular reference to weak discipline of lane-based driving. The theory is based on the discomfort caused by lateral friction between vehicles. The movement of the following vehicle was formulated as a function of the off-centre effects of its leader(s). This incorporation of lateral friction offers a potential breakthrough in the fields of car following theory and microscopic simulation of traffic flow. Using a stopping-distance car following approach, the simulation presented in the paper pointed out the effect of the travel path width on the speed of the following vehicle, and the reduced following distance with increased lateral separation between the leader and follower. It was also shown that a special case of the proposed model (i.e. when the maximum escape speed is zero) produced the same results as the base model did for the conventional car following case. The simulation behaved rationally giving credibility to the author's staggered car following theory.

Suggested Citation

  • Gunay, Banihan, 2007. "Car following theory with lateral discomfort," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 722-735, August.
    • Handle: RePEc:eee:transb:v:41:y:2007:i:7:p:722-735
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    References listed on IDEAS

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    1. Daganzo, Carlos F., 2006. "In traffic flow, cellular automata = kinematic waves," Transportation Research Part B: Methodological, Elsevier, vol. 40(5), pages 396-403, June.
    2. Holland, E. N., 1998. "A generalised stability criterion for motorway traffic," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 141-154, February.
    3. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
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    1. Bouadi, M. & Jetto, K. & Benyoussef, A. & Kenz, A., 2016. "The effect of lateral interaction on traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 76-87.
    2. Karthiga Kasi & Gunasekaran Karuppanan, 2024. "Framework to Identify Vehicle Platoons under Heterogeneous Traffic Conditions on Urban Roads," Sustainability, MDPI, vol. 16(2), pages 1-20, January.
    3. Kanagaraj, Venkatesan & Treiber, Martin, 2018. "Self-driven particle model for mixed traffic and other disordered flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1-11.
    4. Faryal Ali & Zawar Hussain Khan & Khurram Shehzad Khattak & Thomas Aaron Gulliver & Akhtar Nawaz Khan, 2022. "A Microscopic Heterogeneous Traffic Flow Model Considering Distance Headway," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
    5. Banihan Gunay, 2007. "Detection Algorithms of Intentional Car Following on Smart Networks: A Primary Methodology," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(6), pages 627-642, July.
    6. Li, Yongfu & Zhao, Hang & Zhang, Li & Zhang, Chao, 2018. "An extended car-following model incorporating the effects of lateral gap and gradient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 177-189.
    7. Ponnu, Balaji & Coifman, Benjamin, 2015. "Speed-spacing dependency on relative speed from the adjacent lane: New insights for car following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 74-90.

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