[1]LI Yinghong,HAO Xiaoqing.Intelligent analysis of passenger flow state in an integrated transport hub[J].CAAI Transactions on Intelligent Systems,2014,9(6):677-684.[doi:10.3969/j.issn.1673-4785.201308035]
Copy

Intelligent analysis of passenger flow state in an integrated transport hub

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 9 Number of periods: 2014 6 Page number: 677-684 Column: 学术论文—智能系统 Public date: 2014-12-25
Title:
Intelligent analysis of passenger flow state in an integrated transport hub
Author(s):
LI Yinghong;  HAO Xiaoqing
NCUT-Beijing Key Laboratory of Urban Intelligent Traffic Control, North China University of Technology, Beijing 100144, China
Keywords:
traffic engineering; passenger flow congestion index; fuzzy evaluation; running state of passenger flow; integrated transport hub; intelligent analysis; traffic flow
CLC:
TP18;U491.1
DOI:
10.3969/j.issn.1673-4785.201308035
Abstract:
An integrated transport hub undertakes hundreds of thousands of traffic flow every day. In order to meet the need of directing, operation, management and pre-arranged planning, it is important to figure out the running state of passenger flow inside the hub. In this paper, it is proposed to use a new indicator to judge the running state of passenger flow: passenger flow congestion index. A compressive fuzzy evaluation model of the state of passenger flow inside the hinge is setup based on the characteristics that are able to reflect the condition of passenger flow. This includes density of passenger, passenger flow rate per width. The passenger flow congestion index is also determined from this model. Through the simulation and analysis of the state of passenger flow of an actual transport hub, the proposed passenger flow congestion index used in the fuzzy evaluation model reflected the actual state of passenger flow and corresponded with real conditions. The evaluation criteria of the passenger flow state in the transport hub proposed in this paper is concise and clear, which means that it might also be a valuable reference for the travellers and transport hub managers.
References:
[1] 王会会.综合客运交通枢纽内部客流拥堵机理研究[D]. 北京: 北京交通大学, 2011: 23-25.WANG Huihui. Passenger congestion mechanism analysis in comprehensive passenger transportation terminal [D]. Beijing: Beijing Jiaotong University, 2011: 23-25.
[2] 房霄虹,周磊山,周勃.基于可排序DEA的城市综合交通枢纽评价方法研究[J].交通运输系统工程与信息, 2008, 8(2): 108-113.FANG Xiaohong, ZHOU Leishan, ZHOU Bo. Evaluation method of city comprehensive transportation hub based on permutable DEA model[J]. Journal of Transportation Systems Engineering and Information Technoloy, 2008, 8(2): 108-113.
[3] 马莉.城市轨道交通枢纽乘客交通流状态分析与评价[D]. 北京:北京交通大学,2009:15-25.MA Li. Analysis and evaluation of passenger flow operation state in urban railway transit hub[D]. Beijing: Beijing Jiaotong University, 2009: 15-25.
[4] 於毅.城市道路交通状态判别方法研究[D]. 北京:北京交通大学, 2007: 15-17.YU Yi. Research on the identification method of urban road traffic conditions[D]. Beijing: Beijing Jiaotong University, 2007 : 15-17.
[5] 杨兆升,张茂雷.基于模糊综合评判的道路交通状态分析模型[J].公路交通科技, 2010, 27(9): 121-126.YANG Zhaosheng, ZHANG Maolei. A model for road traffic state analys based on fuzzy comprehensive evaluation[J]. Journal of Highway and Transportation Research and Development, 2010, 27 (9): 121-126.
[6] 孙超.城市道路交通状态评价分析研究[D]. 广州:华南理工大学, 2010: 25-31.SUN Chao. Research on urban traffic network state evaluation and analysis[D]. Guangzhou: South China University of Technology, 2010: 25-31.
[7] 陈艳艳,李平普,张广厚,等.综合交通枢纽客流拥挤实时评价方法[J].公路交通科技, 2012, 29: 75-80.CHEN Yanyan, LI Pingpu, ZHANG Guanghou, et al. Real-ime evaluation method of passenger crowding in integrated transport hub[J]. Journal of Highway and Transportation Research and Development, 2012, 29: 75-80.
Similar References:

Memo

-

Last Update: 2015-06-16

Copyright © CAAI Transactions on Intelligent Systems