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Experimental-Numerical Study of Indexation of Scenic Road Vertical Alignment in China

Author(s): ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2021
Page(s): 1-11
DOI: 10.1155/2021/6610534
Abstract:

The vertical alignment design method of road in scenic spots does not evolve enough along the vehicle’s rapid variation. Values of the maximum longitudinal slope (MLS) and longest slope length (LSL) applicable to scenic roads used by the environmental-friendly vehicle (EFV) are not provided. To compensate for this shortage, a multibody vehicle dynamic model in uphill traving is built, providing the static equilibrium state and dynamic balancing process of a typical vehicle. MLS and LSL values in scenic roads are obtained based on this model through numerical simulation, considering typical EFV, maximum velocity loss (MVL), and ideal velocity loss (IVL). Field experiments for verifying the results are also carried out in Huashan Mountain, Cuihua Mountain National Park, and Taiping Forest Park, using two EFV types. MLS and LSL values in scenic roads applicable to EFV obtained in this research vary from 7.8% to 10.2% and 200 to 955 m, respectively, and both are larger than the corresponding values in current criteria. According to verification results, relative errors of climbing velocity vary from 0.0104 to 0.0205, showing the dynamic model’s accuracy and further proving the practicality of MLS and LSL values obtained. The results obtained in this research lay a foundation for establishing the scenic-road vertical alignment design method.

Copyright: © 2021 Ronghua Wang et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10602073
  • Published on:
    17/04/2021
  • Last updated on:
    02/06/2021
 
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