地球信息科学理论与方法

基于MAS的虚拟公共交通环境建模与模拟分析

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  • 1. 首都师范大学三维信息获取与应用教育部重点实验室, 北京100048;
    2. 北京城市学院科技与产业发展部, 北京100083;
    3. 北京市交通信息中心, 北京100161
罗来平(1982-),男,博士后,副研究员,研究方向为交通地理、空间数据挖掘。E-mail:lyleping@163.com

收稿日期: 2014-08-06

  修回日期: 2014-11-01

  网络出版日期: 2015-05-10

基金资助

首都文化研究院重点项目(118135303900/001)。

Modeling and Simulation Analysis of Virtual Public Transportation Environment Based on MAS

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  • 1. Key Lab of 3D Information Acquisition and Application of MOE, Capital Normal University, Beijing 100048, China;
    2. Technology Promotion Institute, Beijing City University, Beijing 100083, China;
    3. Beijing Transportation Information Center, Beijing 100161, China

Received date: 2014-08-06

  Revised date: 2014-11-01

  Online published: 2015-05-10

摘要

针对目前公共交通模型很少关注乘客行为和人车相互作用的问题,提出了虚拟公共交通环境的概念及其构成要素的矢量表达,进而采用Multi-agent System 方法构建了车辆Agent 和乘客Agent 行为模型;并提出了公共交通运行中的车辆、乘客之间相互作用,以及时空变化的模拟算法,实现了虚拟公共交通环境原型系统。最后,设计了7 条道路、8 条公交线路、30 个公交站点和1 万次出行的小型公交环境作为实例验证,结果产生了车辆1428 次,上下车刷卡30 436 人次。通过分析总出行时间分布和对比不同发车间隔下乘客平均等待时间,发现了总出行时间分布与输入的出行需求数据相一致,且缩短发车间隔情况下各站点乘客的平均等待时间明显随之缩短。同时,通过原型系统分析了公交车辆的运行情况和乘客公交出行行为。结果表明,本文所提出的模型和算法能有效地模拟公共交通环境,便于交通管理者和科研工作者观察、处理和分析公共交通环境中所产生的数据。

本文引用格式

罗来平, 张晶, 李佑钢, 胡兴林, 孟田田 . 基于MAS的虚拟公共交通环境建模与模拟分析[J]. 地球信息科学学报, 2015 , 17(5) : 583 -589 . DOI: 10.3724/SP.J.1047.2015.00583

Abstract

To solve the problems about public transportation models in which the passenger behaviors and their interactions with public transportation are rarely concerned, a concept of virtual public transportation environment and the vector representation of its elements is proposed. Meanwhile, a transportation agent model and a passenger behavior agent model were built with the MAS method. Furthermore, an algorithm was proposed to simulate transportations, passengers, and the temporal and spatial variations in public transportation operation. Then, a prototype system of virtual public transport environment was implemented. In the end, a small-scale public transport environment, which was composed by7 roads, 8 bus routes, 31bus stops and 10 000 rides, was designed as the experiment environment. It produced 1428 bus runs and 30 436 passengers'swiping card data of getting on and off buses. The experimental data was analyzed while comparing with the average passenger waiting time under different departure intervals. The results show that the total travel time distribution is consistent with the input data, and the average waiting time is reduced if reducing the departure intervals of buses. It proves that the above models can effectively simulate public transportation environments. As a result, the traffic managers and researches could benefit from the prototype system and models, and it is helpful for them to make rational decisions.

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