Volume 24 Issue 4
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2024  >  24(4): 228-242
ZHANG Min, LIU Kai, ZHANG Chi, XI Sheng-yu, NIE Yu-han. Operating speed prediction models of trucks at interchange ramps based on high-frequency GPS data[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 228-242. doi: 10.19818/j.cnki.1671-1637.2024.04.017
Citation: ZHANG Min, LIU Kai, ZHANG Chi, XI Sheng-yu, NIE Yu-han. Operating speed prediction models of trucks at interchange ramps based on high-frequency GPS data[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 228-242. doi: 10.19818/j.cnki.1671-1637.2024.04.017
shu

Operating speed prediction models of trucks at interchange ramps based on high-frequency GPS data

doi: 10.19818/j.cnki.1671-1637.2024.04.017
  • 1.

    School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    Shenzhen Port Group Co., Ltd., Shenzhen 518083, Guangdong, China

  • 3.

    School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

Natural Science Basic Research Project of Shaanxi Province 2023-JC-YB-391

National Key Research and Development Program of China 2020YFC1512005

Science and Technology Project of Sichuan Province 2022YFG0048

Key Research and Development Program of Shanxi Province 202102020101014

More Information
  • Author Bio:

    ZHANG Min(1981-), female, associate professor, PhD, minzhang@chd.edu.cn

    ZHANG Chi(1981-), male, professor, PhD, zhangchi@chd.edu.cn

  • Received Date: 2024-01-22
    Available Online: 2024-09-26
  • Publish Date: 2024-08-28
    Abstract
  • To clarify the operating speed rules for trucks at interchange ramps, operating speed models for trucks on interchange ramps were constructed based on the analysis of the measured high-frequency GPS data of trucks from the mainline to the end of the ramp on an expressway. Through the analysis of the measured speeds of trucks, the characteristic points of the truck operating speeds at the ramp were determined, and correlation analysis was carried out for design elements that might be related to the speed at the characteristic points. Multiple operating speed models for trucks at characteristic points were established by using all subsets regression methods. By comparing the Akaike information criterion, mallows's Cp statistic, and model test values of different models, the parameters of the independent variables were determined, and prediction models for truck operating speed at various locations were developed, including the small nose point of interchanges, the midpoint of the ramp curve, and the merging nose of the ramps and the connecting lines. These models were validated by using data from four ramps. Research results show that the small nose point of interchanges, the midpoint of the ramp curve, and the merging nose of the ramps and the connection lines can be considered as the characteristic points of truck operating speed at ramps. The radius of the ramp curve, the gradient rate of the exit, and the operating speed of the diversion point have significant effects on the operating speed at the small nose point. The radius, the distance from the midpoint to the merging nose of the ramp, and the operating speed at the small nose point have significant effects on the operating speed at the midpoint of the ramp curve. The longitudinal slope in the first half of the midpoint, the curvature of the curve, and the operating speed at the midpoint have significant effects on the operating speed at the merging nose. The correlation coefficients of the operating speed prediction models at the three characteristic points are 0.988, 0.993, and 0.990, respectively. The mean absolute percentage errors between the predicted and measured values are less than 10%, which meet the requirements of model accuracy.

     

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