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Microscopic Traffic Behaviour near Incidents

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Abstract

Much of the delays on road networks are caused by incidents. This is partially caused by blockage or closure of lanes, but also by the change of driving behaviour in the remaining lanes. This contribution analyses traffic flow conditions near an incident both microscopically and macroscopically. A theory is proposed to describe drivers’ behaviour, which is tested using traffic data of individual vehicles, collected using a helicopter. A bimodal headway distribution is observed, centred around two mean values, 2 seconds and 4 seconds. To understand the underlying mechanisms a car-following model is fitted to the drivers’ behaviour. The model parameters show that the reaction time is much higher than usual. Using this model-based analysis, we conclude that the incident distracts the drivers and less attention is paid to the driving process. The consequence is that the queue discharge rate for the unblocked lanes is 30% lower than the usual queue discharge rate per lane.

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References

  • Cassidy, M.J. and Bertini, R.L. (1999). Some traffic features at freeway bottlenecks. Transportation Research Part B, 33(1), 25-42.

    Article  Google Scholar 

  • Chakravarti, I.M., Laha, R.G. and Roy, J. (1967). Handbook of methods of applied statistics: techniques of computation, descriptive methods, and statistical inference, New York, John Wiley and Sons.

    Google Scholar 

  • Chung, K., Rudjanakanoknad, J. and Cassidy, M.J. (2007). Relation between traffic density and capacity drop at three freeway bottlenecks. Transportation Research Part B, 41(1), 82-95.

    Article  Google Scholar 

  • Dijker, T., Bovy, P.H.L. and Vermijs, R.G.M.M. (1997) Car-following under non-congested and congested conditions. Delft, Delft University of Technology.

    Google Scholar 

  • Hall, F.L. and Agyemang-Duah, K. (1991). Freeway capacity drop and the definition of capacity. Transportation Research Record: Journal of the Transportation Research Board, 1320, 91-98.

    Google Scholar 

  • Heikoop, H., Hoogendoorn, S.P. and Martens, G.J. (2007). Onderzoek Verkeersafwikkeling en capaciteitswaarden discontinuïteiten Autosnelwegen. Rijkswaterstaat, Adviesdienst Verkeer en Vervoer.

    Google Scholar 

  • Highway Capacity Manual (2000). Washington D.C., Transportation Research Board.

    Google Scholar 

  • Hoogendoorn, S., Van Zuylen, H.J., Schreuder, M., Gorte, B.G.H. and Vosselman, M. (2003). Microscopic traffic data collection by remote sensing. Transportation Research Record, 1885, 121-128.

    Article  Google Scholar 

  • Hoogendoorn, S.P. and Van Lint, J. W.C. (2007). Estimation of car-following models using prior information. In Proceedings of the IEEE conference on Intelligent Transport Systems.

    Google Scholar 

  • Knoop, V.L., Hoogendoorn, S.P. and Van Zuylen, H.J. (2008). Capacity reduction at incidents: empirical data collected from a helicopter. Transportation Research Record,Accepted for publication.

    Google Scholar 

  • Kwon, J., Mauch, M. and Varaiya, P. (2006). The components of congestion: delay from incidents, special events, lane closures, weather, potential ramp metering gain, and excess demand. In Proceedings of the 85th annual meeting of the Transportation Research Board, Washington.

    Google Scholar 

  • Ossen, S., Hoogendoorn, S. and Gorte, B.G.H. (2006). Interdriver differences in car-following: a vehicle trajectory-based study. Transportation Research Record, 1965, 121-129.

    Article  Google Scholar 

  • Ossen, S.J.L. (2008). Longitudinal Driving Behavior: Theory and Empirics, TRAIL Thesis Series PhD thesis, Delft, Delft University of Technology.

    Google Scholar 

  • Qin, L. and Smith, B.L. (2001). Characterization of Accident Capacity Reduction.University of Virginia.

    Google Scholar 

  • Schaap, N., Van Arem, B. and Van Der Horst, R. (2008). Drivers’ behavioural reactions to unexpected events. In Proceedings of 10th TRAIL Congress - TRAIL in Perspective, Rotterdam, the Netherlands.

    Google Scholar 

  • Sinha, P., Mohammed Hadi, P.E. and Amy Wang, E.I. (2007). Modeling reductions in freeway capacity due to incidents in microscopic simulation models. In Proceedings of 86th Annual Meeting of the Transportation Research Board, Washington D.C.

    Google Scholar 

  • Tampère, C.M.J. (2004). Human-kinetic Multiclass Traffic Flow Theory and Modelling, PhD Thesis thesis, Delft University of Technology.

    Google Scholar 

  • Thiemann, C., Kesting, A. and Treiber, M. (2008). Estimating acceleration and lane-changing dynamics based on NGSIM trajectory data. In Proceedings of the 87th Annual Meeting of the Transportation Research Board, Washington D.C.

    Google Scholar 

  • Toledo, T., Koutsopoulos, H.N. and Ahmed, K.I. (2007). Estimation of vehicle trajectories with locally weighted regression. In Proceedings of the 86th Annual Meeting of the Transportation Research Board, Washington D.C.

    Google Scholar 

  • Wu, N. (2002). A new approach for modeling of Fundamental Diagrams. Transportation Research Part A, 36(10), 867-884.

    Google Scholar 

Download references

Acknowledgments

This research was supported by the research program Next Generation Infrastructures, the Transport Research Centre Delft and the research program Tracing Congestion Dynamics – with Innovative Data to a Better Theory (sponsored by the Dutch Foundation of Scientific Research MaGW-NWO). The comments of the anonymous reviewers were also gratefully acknowledged.

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© 2009 Springer-Verlag US

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Knoop, V.L., van Zuylen, H.J., Hoogendoorn, S.P. (2009). Microscopic Traffic Behaviour near Incidents. In: Lam, W., Wong, S., Lo, H. (eds) Transportation and Traffic Theory 2009: Golden Jubilee. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0820-9_5

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