Travel time prediction under mixed traffic conditions using RFID and bluetooth sensors

被引:0
|
作者
Jayan A. [1 ]
Anusha S.P. [1 ]
机构
[1] Department of Civil Engineering, College of Engineering Trivandrum, Bus Bay, Ambady Nagar, Thiruvananthapuram, Kerala
来源
Anusha, Sasidharan Premakumari (anushanair@gmail.com) | 1600年 / Budapest University of Technology and Economics卷 / 48期
关键词
ARIMA modeling; Bluetooth; ITS; Mixed traffic; RFID; Travel time prediction;
D O I
10.3311/PPTR.13779
中图分类号
学科分类号
摘要
Travel time information is an integral part in various ITS applications such as Advanced Traveler Information System, Advanced Traffic Management Systems etc. Travel time data can be collected manually or by using advanced sensors. In this study, suitability of Bluetooth and RFID (Radio Frequency Identifier) sensors for data collection under mixed traffic conditions as prevailing in India is explored. Reliability analysis was carried out using Cumulative Frequency Diagrams (CFDs) and buffer time index along with evaluation of penetration rate and match rate of RFID and Bluetooth sensors. Further, travel time of cars for a subsequent week was predicted using the travel time data obtained from RFID sensors for the present week as input in ARIMA modeling method. For predicting the travel time of different vehicle categories, relationships were framed between travel time of different vehicle categories and travel time of cars determined from RFID sensors. The stream travel time was then determined considering the travel time of all vehicle categories. The R-Square and MAPE values were used as performance measure for checking the accuracy of the developed models and were closer to one and lower respectively, indicating the suitability of the RFID sensors for travel time prediction under mixed traffic conditions. The developed estimation schemes can be used as part of travel time information applications in real time Intelligent Transportation System (ITS) implementations. © 2020 Budapest University of Technology and Economics. All rights reserved.
引用
收藏
页码:276 / 289
页数:13
相关论文
共 50 条
  • [1] Investigation of the Use of Bluetooth Sensors for travel Time Studies under Indian Conditions
    Mathew, Jijo K.
    Devi, Lelitha, V
    Bullock, Darcy M.
    Sharma, Anuj
    INTERNATIONAL CONFERENCE ON TRANSPORTATION PLANNING AND IMPLEMENTATION METHODOLOGIES FOR DEVELOPING COUNTRIES (11TH TPMDC) SELECTED PROCEEDINGS, 2016, 17 : 213 - 222
  • [2] Dynamical systems approach for travel time prediction in intermediate section under mixed traffic conditions
    Anusha, S. P.
    Vanajakshi, Lelitha
    Subramanian, Shankar C.
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 27 (05) : 553 - 572
  • [3] Use of Toll Transaction Data for Travel Time Prediction on National Highways Under Mixed Traffic Conditions
    Bari, Chintaman Santosh
    Jhaveri, Parth
    Sharma, Satyendra Kumar
    Gupta, Shubham
    Dhamaniya, Ashish
    Lecture Notes in Civil Engineering, 2024, 377 : 575 - 594
  • [4] Bluetooth as a traffic sensor for stream travel time estimation under Bogazici Bosporus conditions in Turkey
    ilker Erkan
    Hasan Hastemoglu
    Journal of Modern Transportation, 2016, (03) : 207 - 214
  • [5] Bluetooth as a traffic sensor for stream travel time estimation under Bogazici Bosporus conditions in Turkey
    Erkan İ.
    Hastemoglu H.
    Journal of Modern Transportation, 2016, 24 (3): : 207 - 214
  • [6] TRAVEL TIME FOR CAR STREAM ON A BUS STOP UNDER MIXED TRAFFIC CONDITIONS
    Jiang, Yue
    ICIM 2010: PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT, 2010, : 447 - 450
  • [7] Optimal number and location of Bluetooth sensors considering stochastic travel time prediction
    Park, Hyoshin
    Haghani, Ali
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2015, 55 : 203 - 216
  • [8] Travel Time Prediction using Machine Learning and Weather Impact on Traffic Conditions
    Deb, Bilash
    Khan, Salehin Rahman
    Hasan, Khandker Tanvir
    Khan, Ashikul Haque
    Alam, Md Ashraful
    2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2019,
  • [9] Particle Filter for Reliable Bus Travel Time Prediction Under Indian Traffic Conditions
    B. Dhivyabharathi
    B. Anil Kumar
    Lelitha Vanajakshi
    Manoj Panda
    Transportation in Developing Economies, 2017, 3 (2)
  • [10] Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses
    Vanajakshi, L.
    Subramanian, S. C.
    Sivanandan, R.
    IET INTELLIGENT TRANSPORT SYSTEMS, 2009, 3 (01) : 1 - 9