摘要
针对持续型大型活动具有持续时间长、客流集散时间分散、影响范围广、客流波动明显等特点,其客流规模受天气、环境、节假日、出行方式等多种因素影响的特点.本研究以第九届中国国际园林博览会客流为研究对象,获取活动期间客流数据,基于最小显著性差异分析法分析了园博会期间客流特征的相关影响因素,分析表明,天气和节假日为影响客流规模的主要因素,人们更倾向于选择天气状况良好的节假日出行.相比于工作日,周末和节假日客流平均增幅最高超过200%,客流规模平均增长30%.而在雨天、高温等异常天气条件时,入园客流将大幅下降,客流规模下降20%~50%.自办活动的举办并未对客流造成明显影响.
Lasting large-scale events have the characteristics of long duration and wide range of influences.Meanwhile,they will be affected by weather,environment,holiday and other factors.It is important to reveal influence factors and the influence mechanism to the passenger flow for the transportation operations for lasting large-scale events.Based on the passenger flow of the 9th China International Garden Expo,this study collected the vehicle load coefficient through the field car-following investigation.After observing the passenger flow,the study acquired the passenger flow data for six months.The paper analyzed the characteristics of trip mode and passenger arrival and departure,as well as the influence factors of passenger flow scale.The analysis showed that weather and holidays are the main influence factors on the passenger flow scale.People prefer to travel in good weather or holidays.Compared to the working day,the passenger flow increase about 200%on weekends and holiday,and the passenger volume growth is 30%on average.But under the rain,high temperature and other abnormal weather conditions,the passenger flow will reduce about 20%~50%.Other non-large-scale activities did not appear to have obvious influence on the passenger flow.
作者
钱慧敏
李静
张琳
杨子帆
张建强
汪坤
QIAN Huimin;LI Jing;ZHANG Lin;YANG Zifan;ZHANG Jianqiang;WANG Kun(Beijing Municipal Transportation Operations Coordination Center,Beijing 100073,China;Beijing Key Laboratory of Integrated Traffic Operation Monitoring and Service,Beijing 100161;Institute of Public Safety Research,Department of Engineering Physics,Tsinghua University,Beijing,100084;Beijing Institute of Transportation Engineering,Beijing,100070)
出处
《交通工程》
2020年第1期60-65,共6页
Journal of Transportation Engineering
基金
国家自然科学基金青年科学基金项目(71804083)
关键词
大型活动
客流分布特征
客流预测
交通管理
special events
passenger flow distribution
passenger forecast
traffic management
