1. 广东岭南通股份有限公司,广东,广州,510000
2. 广东工业大学 自动化学院,广东,广州,510006
谢振东(1966–),教授级高级工程师,博士,主要研究方向为智能交通、交通大数据和一卡通系统. E-mail:275669497@qq.com
吴金成(1983–),硕士,工程师,主要研究方向为一卡通大数据和移动支付. E-mail:lingnanpass@163.com
网络首发:2018-01-09,
纸质出版:2018
移动端阅览
谢振东, 刘雪琴, 吴金成, 冷梦甜. 公交IC卡数据客流预测模型研究[J]. 广东工业大学学报, 2018, 35(1): 16-22.
Xie Zhen-dong, Liu Xue-qin, Wu Jin-cheng, et al. A Study of Passenger Flow Prediction Based on IC Card Data[J]. 2018, 35(1): 16-22.
谢振东, 刘雪琴, 吴金成, 冷梦甜. 公交IC卡数据客流预测模型研究[J]. 广东工业大学学报, 2018, 35(1): 16-22. DOI: 10.12052/gdutxb.170143.
Xie Zhen-dong, Liu Xue-qin, Wu Jin-cheng, et al. A Study of Passenger Flow Prediction Based on IC Card Data[J]. 2018, 35(1): 16-22. DOI: 10.12052/gdutxb.170143.
为解决我国大城市工作上下班高峰期公交线路客流不均衡的问题
提出以公交路线一卡通数据为研究对象
综合考虑天气类型、温度和风力多个因素对客流的影响
利用多元线性回归模型建立公交工作日高峰期各时间段客流模型. 最后通过一卡通大数据对模型进行了验证
证明多元线性回归模型能够准确且快速地预测高峰时间段的客流量
实现了通过公交线路客流预测缓解城市工作日高峰期出行拥堵的问题.
To solve the unbalanced bus passenger flow during weekday rush hours in China’s big cities
a multiple linear regression model is established by collecting the bus IC card data
weather data and line data
considering the weather types
temperature and wind factors which influence the passenger flow. The results show that the model can forecast
quickly and precisely
the bus weekday passenger flow in each peak period
which may provide the basis for reasonably scheduling bus passenger flow.
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XIE Z D, WU J C, LI Z M, et al . A study of construction and cultivation of big data capacity of enterprise[J ] . Journal of Guangdong University of Technology, 2017, 34(3): 110-114.
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ZHOU W, LU B C, DENG J, et al . Study on passenger flow forecasting based on genetic algorithm and wavelet neural network[J ] . Journal of Wuhan University of Technology(Science and Engineering), 2014, 38(5): 1148-1151.
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李振. 基于Hadoop平台的公交客流分析与预测研究[D]. 长春: 东北师范大学信息与软件工程学院, 2015: 1-48.
耿学贵. 基于IC卡的公交客流时间规律研究[D]. 昆明: 昆明理工大学交通工程学院, 2012: 1-93.
刘雪琴. 基于交通一卡大数据的公客流分析与预测[D]. 广州: 广东工业大学自动化学院, 2016: 1-82.
LI L B, KANG L W, WANG C. A method for determining the date of bus passenger flow survey based on weather impact analysis[J]. Transportation Technology, 2016(1): 149-152.
SUN H, ZHOU Y, FANG Z Q. Analysis of influencing factors of passenger traffic volume based on interpretative structural model[J]. Journal of Beijing Institute of Technology (SOCIAL SCIENCE EDITION), 2010, 12(1): 29-32.
LUO Q, HE L L, WANG X F. Data cleaning technology in data warehouse[J]. Computer Programming Skills and Maintenance, 2015(2): 61.
XIE Z D, WU J C, LIU X Q. Study on the characteristics of urban elderly travel behavior based on traffic card[J]. Golden Card Project, 2015(10): 18-20.
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