基于自主学习智能体模型的枢纽站流线仿真及其组织优化

doi:10.3969/j.issn.1007-7375.2023.05.016

工业工程 ›› 2023, Vol. 26 ›› Issue (5): 139-148.doi: 10.3969/j.issn.1007-7375.2023.05.016

基于自主学习智能体模型的枢纽站流线仿真及其组织优化

傅惠, 姚奕鹏, 陈赛飞

广东工业大学机电工程学院，广东广州 510000

收稿日期:2022-10-30 发布日期:2023-10-25
通讯作者: 陈赛飞(1994-),女,浙江省人,博士,主要研究方向为智能交通系统、多模式交通流控制与优化、系统仿真与建模等。Email:gdutsfchen@163.com E-mail:gdutsfchen@163.com
作者简介:傅惠(1981-),男,湖北省人,教授,博士,主要研究方向为智能交通系统、调度优化、大数据、系统仿真与建模等
基金资助:
广州市科技计划资助项目 (2023A03J0939)

A Passenger Flow Simulation and Organization Optimization of Hub Stations Based on Self-learning Agent Model

FU Hui, YAO Yipeng, CHEN Saifei

School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China

Received:2022-10-30 Published:2023-10-25

摘要/Abstract

摘要： 为了保证枢纽站内旅客在给定流线上顺畅流动，枢纽站场通过调整站内的设施部署方案、建筑结构设计和旅客服务流程设计，以减少旅客流线冲突，提高旅客通行效率，实现枢纽站内的客流组织优化。从枢纽站的旅客流线组织优化工作出发，构建支持细致描述旅客行为的智能体仿真框架；基于仿真框架搭建枢纽站场流线仿真模型，再根据实际数据验证枢纽站场流线仿真模型的可靠性；结合枢纽站场流线仿真，构建枢纽站的流线组织优化方案。结果表明，构建的智能体模型及其方法可以支撑枢纽站内的行人流线仿真，以较低的误差模拟行人在设施内的运动行为；通过设施优化方案能够节省广州南站入站流线的多余设施能力。

关键词: 仿真框架, 枢纽站场, 流线仿真模型, 组织优化

Abstract: In order to guarantee free passenger flows in a hub station with a given flow line, the station can adjust the facility deployment, design building structures and passenger service processes, to reduce the conflicts, so as to improve the efficiency of passenger flows and make an optimization of passenger flow organization. This paper first establishes an agent-based simulation framework to describe detailed passenger behavior in a hub station from the optimization and organization of passenger flows. Then, a passenger flow simulation for hub stations is developed based on the proposed framework, and the reliability of the proposed simulation is verified by combining real data. Finally, the optimization strategy of passenger flow organization is generated by applying the proposed simulation. Results show that the proposed agent model and its method can support the simulation of passenger flow within a hub station and simulate the movement behaviour of passengers in facilities with relatively small errors. The facility optimization strategy can save the redundant facility capacity of the inbound flow line in Guangzhou South Railway Station.

Key words: simulation framework, hub station, pedestrian flow simulation, organizational optimization

中图分类号:

U291.1

傅惠, 姚奕鹏, 陈赛飞. 基于自主学习智能体模型的枢纽站流线仿真及其组织优化[J]. 工业工程, 2023, 26(5): 139-148.

FU Hui, YAO Yipeng, CHEN Saifei. A Passenger Flow Simulation and Organization Optimization of Hub Stations Based on Self-learning Agent Model[J]. Industrial Engineering Journal, 2023, 26(5): 139-148.

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基于自主学习智能体模型的枢纽站流线仿真及其组织优化

A Passenger Flow Simulation and Organization Optimization of Hub Stations Based on Self-learning Agent Model

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