Velocity-repulsion model for pedestrian dynamics based on a multi-state modelling framework

Abstract

In this work, we proposed a multi-state modelling framework that transforms the pedestrian simulation problem into the design of five modules, namely pedestrian state, environmental information, movement action, action function, and state transition rules. Based on the framework, a velocity-repulsion model is constructed with the feature that the faster a pedestrian walks, the greater distance he will keep from others. The model sets several states with different velocity and repulsion parameter couples for pedestrians who take action based on the current state and adjust the velocity and repulsion distance by updating the state. Simulation works are performed for validation. The simulated velocity-density and flow-width relations fit well with experimental data. Two characteristic forms of velocity-headway relations for acceleration and deceleration are revealed in the simulation and confirmed in the experimental data. Self-organisation phenomena of the bottleneck scenarios are reproduced.

KEYWORDS:

• Pedestrian dynamics
• multi-state modelling framework
• velocity-repulsion model
• velocity-density relation
• velocity-headway relation
• flow-width relations
• self-organisation phenomena

Acknowledgment

The authors deeply acknowledge the support from the National Natural Science Foundation of China (Nos. 71871189, 72104205), the Science and Technology Development Funds of Sichuan Province (No.2020YFS0291), the National Key Research and Development Program of China (No. 2017YFC0804900), and Fundamental Research Funds for the Central Universities (2682020CX45, 2682019CX13). At last, the great gratitude should go to the reviewers for their careful work. The supportive reminders and inspiring suggestions from them helped improve this paper a lot.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 71871189, 72104205]; Science and Technology Development Funds of Sichuan Province [grant number 2020YFS0291]; National Key Research and Development Program of China [grant number 2017YFC0804900]; Fundamental Research Funds for the Central Universities [grant number 2682019CX13, 2682020CX45].