IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v14y2018i2p1550147718755637.html
   My bibliography  Save this article

Vehicle trajectory reconstruction from automatic license plate reader data

Author

Listed:
  • Haiyang Yu
  • Shuai Yang
  • Zhihai Wu
  • Xiaolei Ma

Abstract

Using perception data to excavate vehicle travel information has been a popular area of study. In order to learn the vehicle travel characteristics in the city of Ruian, we developed a common methodology for structuring travelers’ complete information using the travel time threshold to recognize a single trip based on the automatic license plate reader data and built a trajectory reconstruction model integrated into the technique for order preference by similarity to an ideal solution and depth-first search to manage the vehicles’ incomplete records phenomenon. In order to increase the practicability of the model, we introduced two speed indicators associated with actual data and verified the model’s reliability through experiments. Our results show that the method would be affected by the number of missing records. The model and results of this work will allow us to further study vehicles’ commuting characteristics and explore hot trajectories.

Suggested Citation

  • Haiyang Yu & Shuai Yang & Zhihai Wu & Xiaolei Ma, 2018. "Vehicle trajectory reconstruction from automatic license plate reader data," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:2:p:1550147718755637
    DOI: 10.1177/1550147718755637
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147718755637
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147718755637?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    2. Xiaolei Ma & Haiyang Yu & Yunpeng Wang & Yinhai Wang, 2015. "Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    3. Baozhen Yao & Bin Yu & Ping Hu & Junjie Gao & Mingheng Zhang, 2016. "An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot," Annals of Operations Research, Springer, vol. 242(2), pages 303-320, July.
    4. Yu, Bin & Zhu, Hanbing & Cai, Wanjun & Ma, Ning & Kuang, Qiji & Yao, Baozhen, 2013. "Two-phase optimization approach to transit hub location – the case of Dalian," Journal of Transport Geography, Elsevier, vol. 33(C), pages 62-71.
    5. Peng, Zixuan & Shan, Wenxuan & Guan, Feng & Yu, Bin, 2016. "Stable vessel-cargo matching in dry bulk shipping market with price game mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 76-94.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Yinpu & An, Chengchuan & Ou, Jishun & Lu, Zhenbo & Xia, Jingxin, 2022. "A general dynamic sequential learning framework for vehicle trajectory reconstruction using automatic vehicle location or identification data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    2. Yixian Chen & Zhaocheng He, 2020. "Vehicle Identity Recovery for Automatic Number Plate Recognition Data via Heterogeneous Network Embedding," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    3. Wenhao Li & Chengkun Liu & Tao Wang & Yanjie Ji, 2024. "An innovative supervised learning structure for trajectory reconstruction of sparse LPR data," Transportation, Springer, vol. 51(1), pages 73-97, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baozhen Yao & Qianqian Yan & Mengjie Zhang & Yunong Yang, 2017. "Improved artificial bee colony algorithm for vehicle routing problem with time windows," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-18, September.
    2. L. Zhang & Y. P. Wang & J. Sun & B. Yu, 2019. "The sightseeing bus schedule optimization under Park and Ride System in tourist attractions," Annals of Operations Research, Springer, vol. 273(1), pages 587-605, February.
    3. Zixuan Peng & Wenxuan Shan & Peng Jia & Bin Yu & Yonglei Jiang & Baozhen Yao, 2020. "Stable ride-sharing matching for the commuters with payment design," Transportation, Springer, vol. 47(1), pages 1-21, February.
    4. Gong, Manlin & Hu, Yucong & Chen, Zhiwei & Li, Xiaopeng, 2021. "Transfer-based customized modular bus system design with passenger-route assignment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
    6. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    7. Sahar Validi & Arijit Bhattacharya & P. J. Byrne, 2020. "Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model," Annals of Operations Research, Springer, vol. 290(1), pages 191-222, July.
    8. Varga, Levente & Tóth, Géza & Néda, Zoltán, 2017. "An improved radiation model and its applicability for understanding commuting patterns in Hungary," MPRA Paper 76806, University Library of Munich, Germany.
    9. Sgrignoli, Paolo & Metulini, Rodolfo & Schiavo, Stefano & Riccaboni, Massimo, 2015. "The relation between global migration and trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 245-260.
    10. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    11. Luo, Xiaohu & Caron, Justin & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "Interprovincial migration and the stringency of energy policy in China," Energy Economics, Elsevier, vol. 58(C), pages 164-173.
    12. Thompson, C.A. & Saxberg, K. & Lega, J. & Tong, D. & Brown, H.E., 2019. "A cumulative gravity model for inter-urban spatial interaction at different scales," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    13. Animesh Gain & Vahid Mojtahed & Claudio Biscaro & Stefano Balbi & Carlo Giupponi, 2015. "An integrated approach of flood risk assessment in the eastern part of Dhaka City," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1499-1530, December.
    14. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    15. S. Bacci & B. Bertaccini, 2021. "Assessment of the University Reputation Through the Analysis of the Student Mobility," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 363-388, August.
    16. Lei, Xinyue & Chen, Junlan & Zhu, Zhenjun & Guo, Xiucheng & Liu, Pei & Jiang, Xiaohong, 2022. "How to locate urban–rural transit hubs from the viewpoint of county integration?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    17. Alejandro Llorente & Manuel Garcia-Herranz & Manuel Cebrian & Esteban Moro, 2015. "Social Media Fingerprints of Unemployment," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    18. Krzysztof Cebrat & Maciej Sobczyński, 2016. "Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-11, December.
    19. Gabriel S Zamudio & Manlio F Márquez & Marco V José, 2020. "Anticipation of ventricular tachyarrhythmias by a novel mathematical method: Further insights towards an early warning system in implantable cardioverter defibrillators," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-10, October.
    20. Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 148-164.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:14:y:2018:i:2:p:1550147718755637. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.