Volume 39 Issue 1
Feb.  2021
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Article Contents
HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016
Citation: HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

doi: 10.3963/j.jssn.1674-4861.2021.01.016
  • Received Date: 2020-09-26
  • Publish Date: 2021-02-28
  • A capacity model is developed to study freeway merging areas of a novel mixed traffic with human-driven vehicles and connected automated vehicles equipped with cooperative adaptive cruise control. The interaction mechanism of factors, such as road traffic characteristics, road structure, and mainline traffic state before the merge, is considered. The probability and statistics theory is used to analyze coupling relationships between penetration rate and platoon length. Furthermore, based on the gap acceptance theory, reduction effects of ramp merging traffic on the capacity of the merging area is analyzed. The capacity model of freeway merging areas with partially connected automated traffic is established to quantitatively describe how the capacity changes with the penetration rate and platoon length of connected automated vehicles under various road conditions. The parameters of road traffic characteristics, road structure, and part of the traffic state before the ramp merge are calibrated according to the actual traffic condition, which improves versatility and transferability of the model. A Vissim simulation platform with an embedded vehicle dynamics module is developed to evaluate the model. The results show that the accuracy of the model is generally over 80%. The model performed well under various penetration rates and platoon lengths of connected automated vehicles.

     

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