Shared Space Modeling Based on Social Forces and Distance Potential Field

  • Bani Anvari
  • Winnie Daamen
  • Victor L. Knoop
  • Serge P. Hoogendoorn
  • Michael G. H. Bell
Conference paper


Urban design is moving towards space sharing in order to increase the community texture and safety of street surroundings. However, there is a need for a simulation tool capable of representing future shared space schemes to help judging the designs under which shared space design is a suitable alternative to traditional street designs. This paper presents a microscopic mathematical model that is used a traffic simulation tool capable to represent main behaviors of pedestrians and cars in any shared space layout. This is achieved by generating a route map which helps agents to find the shortest path towards their target destinations on the strategic level. On the operational level, the Social Force Model (SFM) is used and extended for a mixed traffic to produce feasible trajectories. The trajectory results are presented to give a face-validation of the functionality of the shared space simulation model.


Shared space Social force model Flood fill algorithm 



The authors would like to thank NEARCTIS for the financial support of this study under grant number 224272.


  1. 1.
    C. Boenisch and T. Kretz. Simulation of Pedestrians Crossing a Street. In Traffic and Granular Flow ’09, 2009.Google Scholar
  2. 2.
    M. Chraibi and A. Seyfried. Generalized Centrifugal-Force Model for Pedestrian Dynamics. Physical Review E, 82:046111, 2010.CrossRefGoogle Scholar
  3. 3.
    DfT. Shared Space. Technical report, TSO, October 2011.Google Scholar
  4. 4.
    E.W. Dijkstra. A Note on Two Problems in Connexion with Graphs. Numerische Mathematik, 1:269–271, 1959.CrossRefMATHMathSciNetGoogle Scholar
  5. 5.
    R.S. Franca, M.G.B. Marietto, W.R. Santana, and G. Kobayashi. An Agent-Based Simulation Model for Pedestrian Unidirectional Movement. In Second International Conference on the Applications of Digital Information and Web Technologies, 2009.Google Scholar
  6. 6.
    D. Helbing. A Mathematical Model for the Behaviour of Pedestrians. Behavioral Science, 36:298–310, 1991.CrossRefGoogle Scholar
  7. 7.
    D. Helbing, I. Farkas, and T. Vicsek. Simulating Dynamical Features of Escape Panic. Nature, 407:487–490, 2000.CrossRefGoogle Scholar
  8. 8.
    D. Helbing, R. Jiang, and M. Treiber. Analytical Investigation of Oscillations in Intersecting Flows of Pedestrian and Vehicle Traffic. Physical Review E, 72:0461301–04613010, 2005.CrossRefGoogle Scholar
  9. 9.
    D Helbing and B Tilch. Generalized Force Model of Traffic Dynamics. Physical Review E, 58:133–138, 1999.Google Scholar
  10. 10.
    M.M. Ishaque and R.B. Noland. Trade-offs between Vehicular and Pedestrian Traffic using Micro-Simulation Methods. Transport Polcy 14, 124:124–138, 2007.Google Scholar
  11. 11.
    R. Jiang and Q.S. Wu. Interaction between Vehicle and Pedestrians in a Narrow Channel. Physica A, 364:239–246, 2006.CrossRefGoogle Scholar
  12. 12.
    T. Kretz, C. Bonisch, and P. Vortisch. Comparison of Various Methods for the Calculation of the Distance Potential Field. Pedestrian and Evacuation Dynamics, 2008.Google Scholar
  13. 13.
    M. Moussaid, D. Helbing, S. Garnier, A. Johansson, M. Combe, and G. Theraulaz. Experimental Study of the Behavioural Mechanisms Underlying Self-Organization in Human Crowds. Proceedings of the Royal Society B, 276:2755–2762, 2009.CrossRefGoogle Scholar
  14. 14.
    R. Schönauer, M. Stubenschrott, W. Huang, C. Rudloff, and M. Fellendorf. Modeling Concepts for Mixed Traffic: Steps towards a Microscopic Simulation Tool for Shared Space Zones. In TRB 2012 Annual Meeting, 2012.Google Scholar
  15. 15.
    A. Seyfried, B. Steffen, W. Klingsch, and M. Boltes. The Fundamental Diagram of Pedestrian Movement Revisited. Statistical Mechanics: Theory and Experiment, 10:P10002, 2005.CrossRefGoogle Scholar
  16. 16.
    Z. Zainuddin and M. Shuaib. Incorporating Decision Making Capability into the Social Force Model in Unidirectional Flow. Research Journal of Applied Science 5, 6:388–393, 2010.Google Scholar
  17. 17.
    H.M. Zhang and T. Kim. A Car-following Theory for Multiphase Vehicular Traffic Flow. Transport Research Part B, 39:385–399, 2005.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bani Anvari
    • 1
  • Winnie Daamen
    • 2
  • Victor L. Knoop
    • 2
  • Serge P. Hoogendoorn
    • 2
  • Michael G. H. Bell
    • 1
  1. 1.Department of Civil and Environmental Engineering, Centre for Transport StudiesImperial College LondonLondonUK
  2. 2.Transport & PlanningDelft University of TechnologyDelftThe Netherlands

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