Skip to main content
SpringerLink
Log in

Path decision modelling for passengers in the urban rail transit hub under the guidance of traffic signs

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Traffic signs plays an important role in pedestrian path guidance in the urban rail transit hub. However, the existing traffic signs within urban rail transit hubs are more or less deployed rigidly, which cannot fully consider the relationship between the layout and visual information about passengers’ decisions. Therefore, this paper analyses the influence of traffic signs on the path selection behavior of pedestrians, and construct the MAKLINK diagram to study the impact of traffic signs on pedestrians’ proceeding decisions by a simulation technique. With the MAKLINK diagram, the path plan under the guidance of traffic signs is formulated. Then, the optimal pedestrian path on the MAKLINK diagram considering the effect of traffic signs is optimized via the Ant Colony Algorithm. An empirical study at Beijing South Railway Station is conducted. The findings reflect that traffic signs within urban rail transit hub could effectively take effect to the path selection behavior of large-volume passengers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Balakhontceva M, Karbovskii V, Rybokonenko D, Boukhanovsky A (2015) Multi-agent simulation of passenger evacuation considering ship motions. Procedia Comput Sci 66:140–149

    Article  Google Scholar 

  • Espelosín J, Acosta L, Alonso D (2013) Path planning approach based on flock dynamics of moving particles. Appl Soft Comput 13(4):2159–2170

    Article  Google Scholar 

  • Hoogendoorn SP, Bovy PHL (2000) Gas-kunatic modeling and simulation of pedestrian flows Transp Res Rec 1710:28–36

    Article  Google Scholar 

  • Kheiri F (2016) Pedestrian circulation simulation based on ant colony system in site analysis. J Build Eng 7:312–319

    Article  Google Scholar 

  • Kok VJ, Lim MK, Chan CS (2016) Crowd behavior analysis: a review where physics meets biology. Neurocomputing 177:342–362

    Article  Google Scholar 

  • Li B, Jin Q, Guo H (2013) Research on psychological characteristics of passengers in terminal and some related measures. Procedia 96:993–1000

    Google Scholar 

  • Li J, Fu S, He H, Jia H, Li Y, Guo Y (2015) Simulating large-scale pedestrian movement using CA and event driven model: methodology and case study. Phys A 437:304–321

    Article  Google Scholar 

  • Liu M, Zheng X, Cheng Y (2011) Determining the effective distance of emergency evacuation signs. Fire Saf J 46(6):364–369

    Article  Google Scholar 

  • Mohanta JC, Parhi DR, Patel SK (2011) Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation. Comput Electr Eng 37(6):1058–1070

    Article  Google Scholar 

  • Nassar K (2011) Sign visibility for pedestrians assessed with agent based simulation. Transp Res Rec 2264:18–26

    Article  Google Scholar 

  • Read GJM, Salmon PM, Lenné MG, Stanton NA (2016) Walking the line: understanding pedestrian behaviour and risk at rail level crossings with cognitive work analysis. Appl Ergon A 53:209–227

    Article  Google Scholar 

  • Schadschneider A, Chowdhury D, Nishinari K (2011) Pedestrian dynamics, stochastic transport in complex systems, Chap 11. Elsevier, Amsterdam, pp 407–460

    Book  MATH  Google Scholar 

  • Shiwakoti N, Sarvi M (2013) Understanding pedestrian crowd panic: a review on model organisms approach. J Transp Geogr 26:12–17

    Article  Google Scholar 

  • Shiwakoti N, Gong Y, Shi X, Ye Z (2015) Examining influence of merging architectural features on pedestrian crowd movement. Saf Sci 75:15–22

    Article  Google Scholar 

  • Skinderowicz R (2016) The GPU-based parallel ant colony system. J Parallel Distrib Comput 98:48–60

    Article  Google Scholar 

  • Tan GZ, He H, Sloman A (2007) Ant colony system algorithm for real-time globally optimal path planning of mobile robots. Acta Autom Sin 33(3):279–285

    Article  MATH  Google Scholar 

  • Tissera PC, Printista AM, Luque E (2012) A hybrid simulation model to test behaviour designs in an emergency evacuation. Procedia Comput Sci 9:266–275

    Article  Google Scholar 

  • Wang S, Lv W, Song W (2015) Behavior of ants escaping from a single-exit room. PLoS ONE 10(6):e0131784

    Article  Google Scholar 

  • Zhang L, Liu M, Wu X, AbouRizk SM (2016) Simulation-based route planning for pedestrian evacuation in metro stations: a case study. Autom Constr 71:430–442

    Article  Google Scholar 

  • Zheng X, Zhong T, Liu M (2009) Modeling crowd evacuation of a building based on seven methodological approaches. Build Environ 44(3):437–445

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Beijing Engineering Research Center of Urban Transport Infrastructure Construction, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China

    Zhihong Li

  2. School of Transportation, Beijing Jiaotong University, Beijing, 100044, China

    Zhihong Li

  3. Department of Urban Planning, Xiamen University, Xiamen, 361005, China

    Wangtu Ato Xu

Authors
  1. Zhihong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wangtu Ato Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wangtu Ato Xu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Z., Xu, W.A. Path decision modelling for passengers in the urban rail transit hub under the guidance of traffic signs. J Ambient Intell Human Comput 10, 365–372 (2019). https://doi.org/10.1007/s12652-017-0544-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-017-0544-y

Keywords

Search

Navigation