Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data

被引:11
|
作者
Zhao, De [1 ,2 ,3 ]
Ong, Ghim Ping [4 ]
Wang, Wei [1 ,2 ,3 ]
Zhou, Wei [1 ,2 ,3 ]
机构
[1] Southeast Univ, Jiangsu Key Lab Urban ITS, Nanjing 210096, Peoples R China
[2] Southeast Univ, Jiangsu Prov Collaborat Innovat Ctr Modern Urban, Nanjing 210096, Peoples R China
[3] Southeast Univ, Sch Transportat, Nanjing 210096, Peoples R China
[4] Natl Univ Singapore, Dept Civil & Environm Engn, Singapore 117576, Singapore
基金
中国国家自然科学基金;
关键词
public bicycle; negative binomial regression; trip distribution; trip duration; smart card; road traffic engineering; SHARING SYSTEM; BIKE STATIONS; IMPACT; PATTERNS; WEATHER; CHOICE; SCHEME;
D O I
10.3390/su13020500
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A reliable estimation of public bicycle trip characteristics, especially trip distribution and duration, can help decision-makers plan for the relevant transport infrastructures and assist operators in addressing issues related to bicycle imbalance. Past research studies have attempted to understand the relationship between public bicycle trip generation, trip attraction and factors such as built environment, weather, population density, etc. However, these studies typically did not include trip distribution, duration, and detailed information on the built environment. This paper aims to estimate public bicycle daily trip characteristics, i.e., trip generation, trip attraction, trip distribution, and duration using points of interest and smart card data from Nanjing, China. Negative binomial regression models were developed to examine the effect of built environment on public bicycle usage. Totally fifteen types of points of interest (POIs) data are investigated and factors such as residence, employment, entertainment, and metro station are found to be statistically significant. The results showed that 300 m buffer POIs of residence, employment, entertainment, restaurant, bus stop, metro station, amenity, and school have significantly positive effects on public bicycle generation and attraction, while, counterintuitively, 300 m buffer POIs of shopping, parks, attractions, sports, and hospital have significantly negative effects. Specifically, an increase of 1% in the trip distance leads to a 2.36% decrease in the origin-destination (OD) trips or a 0.54% increase of the trip duration. We also found that a 1% increase in the number of other nearby stations can help reduce 0.19% of the OD trips. The results from this paper can offer useful insights to operators in better estimating public bicycle usage and providing reliable services that can improve ridership.
引用
收藏
页码:1 / 13
页数:13
相关论文
共 50 条
  • [31] The Built Environment and Public Health.
    van Loon, Joshua R.
    [J]. JOURNAL OF PLANNING EDUCATION AND RESEARCH, 2013, 33 (04) : 491 - 492
  • [32] Effect of the built environment on public health
    Tulbentci, Tugsad
    Cetintas, Muhammed Fatih
    [J]. INTERNATIONAL JOURNAL OF ADVANCED AND APPLIED SCIENCES, 2018, 5 (12): : 67 - 71
  • [33] Exploring multi-scale spatial relationship between built environment and public bicycle ridership: A case study in Nanjing
    Lyu, Cheng
    Wu, Xinhua
    Liu, Yang
    Yang, Xun
    Liu, Zhiyuan
    [J]. JOURNAL OF TRANSPORT AND LAND USE, 2020, 13 (01) : 447 - 467
  • [34] Data politics in the built environment
    Karvonen, Andrew
    Hargreaves, Tom
    [J]. BUILDINGS & CITIES, 2023, 4 (01): : 920 - 926
  • [35] An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis
    Zhao, De
    Wang, Wei
    Ong, Ghim Ping
    Ji, Yanjie
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2018,
  • [36] ESTIMATING THE HOURLY VARIABILITY OF BICYCLE TRIP PATERNS AND CHARACTERISTISC FROM AUTOMATIC BICYCLE COUNTERS: CASE STUDY IN PRAGUE, CZECH REPUBLIC
    Jirsa, Vojtech
    Susilo, Yusak O.
    [J]. PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON TRAFFIC AND TRANSPORT ENGINEERING (ICTTE), 2016, : 769 - 776
  • [37] Estimating bicycle parking demand with limited data availability
    Pfaffenbichler, Paul Christian
    Brezina, Tadej
    [J]. PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-ENGINEERING SUSTAINABILITY, 2016, 169 (02) : 76 - 84
  • [38] Fluctuation characteristics of airflow in built environment
    Department of Building Science, Tsinghua University, Beijing 100084, China
    [J]. Huagong Xuebao, 2006, SUPPL. (8-14):
  • [39] Explaining subjective perceptions of public spaces as a function of the built environment: A massive data approach
    Rossetti, Tomas
    Lobel, Hans
    Rocco, Victor
    Hurtubia, Ricardo
    [J]. LANDSCAPE AND URBAN PLANNING, 2019, 181 : 169 - 178
  • [40] How does our natural and built environment affect the use of bicycle sharing?
    Mateo-Babiano, Iderlina
    Bean, Richard
    Corcoran, Jonathan
    Pojani, Dorina
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2016, 94 : 295 - 307