Heterogeneous Pedestrian Simulation in Commercial Complexes: When Attractive Potential Meets Social Force

Commercial complex is a compositional scenario that involves pedestrians with different travel purposes such as commuting, shopping and business. Simulation of pedestrian behavior in a commercial complex is difficult due to the heterogeneity of pedestrians and different attractions from various kinds of shops. Inspired from the law of universal gravitation and the pedestrian dynamics theory, we propose an attractive potential based social force framework for pedestrian simulation in commercial complexes. Our framework consists of an attractive potential model and an attractive potential based social force model. The former model evaluates the attractive force of different types of shops towards heterogeneous pedestrians, by associating the attributes of pedestrians with the types of shops. The latter model effectively evaluates the travel direction of pedestrians by incorporating the attractive force with the social force model via a synthesis force criterion. We conduct the simulation experiment based on 600 groups of pedestrian tracking data collected in the China World Mall, Beijing, a typical commercial complex. The simulation results show that the model can effectively simulate not only the trajectory of real pedestrians, but also the behavior of entering shops. Our research significantly improves the authenticity of pedestrian simulation and provides support for travel behavior modeling of heterogeneous pedestrians in the commercial complex.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-02-28
DOI
https://doi.org/10.1109/tits.2025.3543613
Citations
1
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
1.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heterogeneous Pedestrian Simulation in Commercial Complexes: When Attractive Potential Meets Social Force

Jingxuan Peng, Shaofan Wang, Zhonghua Wei, Fujiyama Taku et al.
1 citations
IEEE Transactions on Intelligent Transportation Systems
Evacuation and Crowd Dynamics
1.15
article

Heterogeneous Pedestrian Simulation in Commercial Complexes: When Attractive Potential Meets Social Force

Jingxuan Peng, Shaofan Wang, Zhonghua Wei, Fujiyama Taku, Yanyan Chen, Yongxing Li, Shihao Wang
article en
1 citations

Abstract

Commercial complex is a compositional scenario that involves pedestrians with different travel purposes such as commuting, shopping and business. Simulation of pedestrian behavior in a commercial complex is difficult due to the heterogeneity of pedestrians and different attractions from various kinds of shops. Inspired from the law of universal gravitation and the pedestrian dynamics theory, we propose an attractive potential based social force framework for pedestrian simulation in commercial complexes. Our framework consists of an attractive potential model and an attractive potential based social force model. The former model evaluates the attractive force of different types of shops towards heterogeneous pedestrians, by associating the attributes of pedestrians with the types of shops. The latter model effectively evaluates the travel direction of pedestrians by incorporating the attractive force with the social force model via a synthesis force criterion. We conduct the simulation experiment based on 600 groups of pedestrian tracking data collected in the China World Mall, Beijing, a typical commercial complex. The simulation results show that the model can effectively simulate not only the trajectory of real pedestrians, but also the behavior of entering shops. Our research significantly improves the authenticity of pedestrian simulation and provides support for travel behavior modeling of heterogeneous pedestrians in the commercial complex.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(4)
Beijing University of Technology (CN), University College London (GB)
National Natural Science Foundation of China, Natural Science Foundation of Chongqing
Openalex Percentile: Top 26%
Evacuation and Crowd Dynamics
1.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.