Pedestrian Simulation in Transit Stations Using Agent-Based Analysis

The research discusses experiential outcome in the application of crowd simulation technology to analyze the pedestrian circulation in public spaces to facilitate design and planning decisions. The paper describes how to connect spatial design with agent-based simulation (ABS) for various design and planning scenarios. It describes the process of visualizing and representing pedestrian movement, as well as pathfinding and crowd behavior study. An ABS consists of a large number of agents, which are controlled by simple localized rules to interact with each other within a virtual environment, thereby formulating a bottom-up system. The concept of the ABS has been widely used in computer science, biology, and social science to simulate swarm intelligence, dynamic social behavior, and fire evacuation. The simulation consists of interacting agents which can create various complexities. This paper describes research on using local interactions to generate passenger flow analysis. An ABS is used to optimize the pedestrian flow and construct the micro-level complexity within a simulated environment. The authors focus on how agent-driven emergent patterns can evolve during the simulation in response to various design iterations. The research extends to the agents’ interactions driven by a set of rules and external environment. Their research method includes data collection, quantitative analysis, and crowd simulation on two train stations and surrounding areas in Sihui train station in Beijing, and Xuzhou, China. By proposing a mix-use program with the local public transportation system, the new development is integrated with the existing urban infrastructure and public space. Through the multi-agent simulation, the authors evaluate the crowd flow, total travel time, density, and public accessibility. Based on the result of ABS, they discussed whether various space design methods can improve pedestrian flow efficiency and passenger experience, as well as shortening transfer time, and reducing congestion.

• Record URL:
  https://doi.org/10.1007/s40864-017-0053-5
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/21996679
• Supplemental Notes:
  • © 2017 Ming Tang and Yingdong Hu.
• Authors:
  • Tang, Ming
  • 0000-0001-7284-856X
  • Hu, Yingdong
• Publication Date: 2017-3

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References;
• Pagination: pp 54-60
• Serial:
  • Urban Rail Transit
  • Volume: 3
  • Issue Number: 1
  • Publisher: Springer Publishing
  • ISSN: 2199-6679
  • Serial URL: http://link.springer.com/journal/40864

Subject/Index Terms

• TRT Terms: Crowds; Pedestrian flow; Pedestrians; Rail transit stations; Simulation; Walking
• Uncontrolled Terms: Agent based models
• Geographic Terms: Beijing (China); Xuzhou (China)
• Subject Areas: Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01635765
• Record Type: Publication
• Files: TRIS
• Created Date: May 19 2017 1:57PM