Modeling the Factors Affecting Bus Stop Dwell Time Use of Automatic Passenger Counting, Automatic Fare Counting, and Automatic Vehicle Location Data

被引:61
|
作者
Milkovits, Martin N. [1 ]
机构
[1] MIT, Cambridge, MA 02139 USA
关键词
D O I
10.3141/2072-13
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Dwell time at bus stops represents a significant portion of bus operating time and contributes to its variability. Although dwell time is highly correlated with the number of passengers boarding and alighting, there are also secondary factors such as crowding, fare type, and bus design that may affect it. These secondary factors may strongly influence the effectiveness of different strategies used to improve service. Automatic data collection systems provide a plethora of data, but they require preprocessing to combine records from different collection systems to control for measurement error and to determine the significant factors influencing dwell time. Using data from the automatic passenger counting, automatic fare counting, and automatic vehicle location systems installed on Chicago Transit Authority buses, the paper develops and implements preprocessing techniques, estimates a dwell time model, and analyzes the impact of the secondary factors. Smart media farecards are estimated to have a 1.5-s faster transaction time than magnetic strip tickets, but only in uncrowded situations. When the number of onboard passengers exceeds the seating capacity, there is no statistically significant difference between the fare media types.
引用
收藏
页码:125 / 130
页数:6
相关论文
共 50 条
  • [1] Measuring Bus Stop Dwell Time and Time Lost Serving Stop with London iBus Automatic Vehicle Location Data
    Robinson, Steve
    [J]. TRANSPORTATION RESEARCH RECORD, 2013, (2352) : 68 - 75
  • [2] Automatic passenger counting and vehicle load monitoring
    Pinna, Ivano
    Dalla Chiara, Bruno
    Deflorio, Francesco
    [J]. Ingegneria Ferroviaria, 2010, 65 (02): : 101 - 138
  • [3] THE USE OF AUTOMATIC PASSENGER COUNTING DATA TO VERIFY SCHEDULE ADHERENCE
    MARTIN, HA
    STEANE, AH
    MAUCERI, VC
    [J]. LECTURE NOTES IN ECONOMICS AND MATHEMATICAL SYSTEMS, 1992, 386 : 245 - 258
  • [4] Rethinking bus punctuality by integrating Automatic Vehicle Location data and passenger patterns
    Barabino, Benedetto
    Di Francesco, Massimo
    Mozzoni, Sara
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2015, 75 : 84 - 95
  • [5] A two-stage method for bus passenger load prediction using automatic passenger counting data
    Wang, Pengfei
    Chen, Xuewu
    Chen, Jingxu
    Hua, Mingzhuang
    Pu, Ziyuan
    [J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2021, 15 (02) : 248 - 260
  • [6] Characteristics Analysis of Bus Stop Failure Using Automatic Vehicle Location Data
    Li, Rui
    Xue, Xin
    Wang, Hua
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2020, 2020 (2020)
  • [7] Automated Quality Assurance Methodology for Archived Transit Data from Automatic Vehicle Location and Passenger Counting Systems
    Saavedra, Marian
    Hellinga, Bruce
    Casello, Jeffrey
    [J]. TRANSPORTATION RESEARCH RECORD, 2011, (2256) : 130 - 141
  • [8] AUTOMATIC PASSENGER COUNTING DATA - BETTER SCHEDULES IMPROVE ON-TIME PERFORMANCE
    KOFFMAN, J
    [J]. LECTURE NOTES IN ECONOMICS AND MATHEMATICAL SYSTEMS, 1992, 386 : 259 - 282
  • [9] An Offline Framework for Handling Automatic Passenger Counting Raw Data
    Barabino, Benedetto
    Di Francesco, Massimo
    Mozzoni, Sara
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 15 (06) : 2443 - 2456
  • [10] Automatic passenger counting system for bus based on RGB-D video
    Li, Feng
    Yang, Fuwei
    Liang, Haiwei
    Yang, Wenming
    [J]. PROCEEDINGS OF THE 2ND ANNUAL INTERNATIONAL CONFERENCE ON ELECTRONICS, ELECTRICAL ENGINEERING AND INFORMATION SCIENCE (EEEIS 2016), 2016, 117 : 209 - 220