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Technical paper | Open Access

A novel simulation framework for crowd transportations

Zhihui Li( )Hongbo Sun
School of Computer and Control Engineering, Yantai University, Yantai, China
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Abstract

Purpose

With the development of the modern economy, vehicles are no longer a luxury for people, which greatly facilitate people's daily life, but at the same time bring traffic congestion. How to relieve traffic congestion and improve its capacity is a hot research area. This paper aims to propose a new simulation framework for crowd transportations to ease traffic congestion.

Design/methodology/approach

This paper establishes related simulation models such as vehicles, traffic lights and advisers. Then the paper describes their relationships, gives their interaction mechanism and solidifies the above into a software implementation framework.

Findings

This paper proposes a simulation framework for crowd transportations.

Originality/value

In this framework, traffic lights are used as a control method to control the road network and road conditions are used as an Affecter to influence individual behavior. The vehicle passing rate is defined by the correlation between endowment and the start time of the traffic lights. In this framework, members are related, dynamically adjusted according to road conditions and dynamically optimized member decisions. The optimal path is dynamic and real-time adjustments are made for each step forward. It is different from the traditional optimal path in which there is only one fixed one and it is different from the macroscopic optimal path that does not exist.

References

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International Journal of Crowd Science
Pages 293-310

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Cite this article:
Li Z, Sun H. A novel simulation framework for crowd transportations. International Journal of Crowd Science, 2021, 5(3): 293-310. https://doi.org/10.1108/IJCS-07-2021-0019

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Received: 28 July 2021
Revised: 17 September 2021
Accepted: 17 September 2021
Published: 07 October 2021
© The author(s)

Zhihui Li and Hongbo Sun. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode