Identification and Classification of Spatiotemporal Traffic Congestion Based on Floating Car Data
ID:54 View Protection:ATTENDEE Updated Time:2021-12-15 13:01:11 Hits:364 Poster Presentation

Start Time:2021-12-17 08:17(Asia/Shanghai)

Duration:1min

Session:P1 Poster2020 » P1T1Track 1 Advanced Transportation Information and Control Engineering

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Abstract
Congestion identification is an important research issue in the field of transportation. How to clarify the congestion which is frequent and which is an incident has become the main problems. Therefore, the purpose of this study is to identify the spatiotemporal traffic congestion of expressway sections based on floating car data and to distinguish the frequent congestion from the occasional congestion. The method is to analyze the spatiotemporal diagram of expressway speed and to extract the features of congestion. According to the congestion frequency and historical average speed, the congestion is classified by the k-means clustering method. The Guangzhou Airport Expressway is as an application of this method. From the result, the spatiotemporal traffic congestion is clearly identified. Finally, the frequent, accidental and occasional congestions are distinguished in the diagram and the causes of congestion are analyzed. Traffic managers can give improving suggestions of road performance based on it.
Keywords
CICTP
Speaker
Xuedong Yan
Beijing Jiaotong University

Submission Author
xuedong yan Beijing Jiaotong University
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Important Date
  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
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