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Expressway Vehicle Arrival Time Estimation Algorithm Based on Electronic Toll Collection Data

Author

Listed:
  • Shukun Lai

    (School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China)

  • Hongke Xu

    (School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China)

  • Yongyu Luo

    (Fujian Provincial Expressway Information Technology Co., Ltd., Fuzhou 350001, China)

  • Fumin Zou

    (Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350108, China)

  • Zerong Hu

    (Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350108, China)

  • Huan Zhong

    (Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350108, China)

Abstract

Precise travel time prediction benefits travelers and traffic managers by enabling anticipation of future roadway conditions, thus aiding in pre-trip planning and the development of traffic control strategies. This approach contributes to reducing travel time and alleviating traffic congestion issues. To achieve real-time state perception of vehicles on expressways, we propose an algorithm to estimate the arrival time of vehicles in the next segment using Electronic Toll Collection (ETC) data. Firstly, the characteristics of ETC data and GPS data are meticulously described. We devise algorithms for data cleaning and fusion, subsequently segmenting the vehicle journey into multiple sub-segments. In the following step, feature vectors are constructed from the fused data to detect service areas and analyze the expressway segment characteristics, vehicle traits, and the influence of service areas. Finally, an algorithm utilizing LightGBM is introduced for estimating the arrival time of vehicles at various segments, corroborated by empirical tests using authentic traffic data. The M A E of the algorithm is recorded as 20.1 s, with an R M S E of 32.6 s, affirming its efficacy. The method proposed in this paper can help optimize transportation systems for improving efficiency, alleviating congestion, reducing emissions, and enhancing safety.

Suggested Citation

  • Shukun Lai & Hongke Xu & Yongyu Luo & Fumin Zou & Zerong Hu & Huan Zhong, 2024. "Expressway Vehicle Arrival Time Estimation Algorithm Based on Electronic Toll Collection Data," Sustainability, MDPI, vol. 16(13), pages 1-30, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5581-:d:1425600
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    References listed on IDEAS

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    1. Gurmesh Sihag & Manoranjan Parida & Praveen Kumar, 2022. "Travel Time Prediction for Traveler Information System in Heterogeneous Disordered Traffic Conditions Using GPS Trajectories," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
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