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Asymmetric Microscopic Driving Behavior Theory

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  • Yeo, Hwasoo

Abstract

Numerous theories on traffic have been developed as traffic congestion gains more and more interest in our daily life. To model traffic phenomena, many traffic theorists have adopted theories from other fields such as fluid mechanics and thermodynamics. However, their efforts to model the traffic at a microscopic level have not been successful yet. Therefore, to overcome the limitations of the existing theories we propose a microscopic asymmetric traffic theory based on analysis of individual vehicle trajectories. According to the proposed theory, vehicle traffic is classified into 5 phases: free flow, acceleration, deceleration, coasting, and stationary. The proposed theory suggests that traffic equilibrium exists as 2-dimensional area bounded by A-curve and D-curve, and explains phase transitions. The basic theory was extended to address driver behavior such as vehicle maneuvering error and anticipation. The proposed theory was applied to explain several traffic phenomena in congested traffic such as traffic hysteresis, capacity drop, stability, relaxation after lane change, and stop-and-go waves. We provided reasonable and intuitive explanations on these phenomena which cannot be easily understood with existing theories.

Suggested Citation

  • Yeo, Hwasoo, 2008. "Asymmetric Microscopic Driving Behavior Theory," University of California Transportation Center, Working Papers qt1tn1m968, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt1tn1m968
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    Cited by:

    1. Oh, Simon & Yeo, Hwasoo, 2015. "Impact of stop-and-go waves and lane changes on discharge rate in recovery flow," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 88-102.
    2. Runkun Liu & Haiyang Yu & Yilong Ren & Shuai Liu, 2022. "The Analysis of Classification and Spatiotemporal Distribution Characteristics of Ride-Hailing Driver’s Driving Style: A Case Study in China," IJERPH, MDPI, vol. 19(15), pages 1-19, August.
    3. Yibing Wang & Long Wang & Xianghua Yu & Jingqiu Guo, 2023. "Capacity Drop at Freeway Ramp Merges with Its Replication in Macroscopic and Microscopic Traffic Simulations: A Tutorial Report," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    4. Kai Yuan & Victor L. Knoop & Serge P. Hoogendoorn, 2017. "A Microscopic Investigation Into the Capacity Drop: Impacts of Longitudinal Behavior on the Queue Discharge Rate," Transportation Science, INFORMS, vol. 51(3), pages 852-862, August.
    5. Wei, Dali & Liu, Hongchao, 2013. "Analysis of asymmetric driving behavior using a self-learning approach," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 1-14.

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