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The Forecast of Total Induced Traffic Volume in the Building Project

—Taking Changchun City Automobile Trade Logistics Park as an Example
  • Liu Yang
  • Wang Jinling
  • Bian Shuai
  • Xing Yan
  • Bai Zhu
  • Zhang Siqi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 503)

Abstract

In this paper, we take the example of Changchun City automobile trade logistics park. Based on the design parameters of the project plan given by the design department, we forecast the occurrence quantity of daily peak hours of induced travel in the different functional areas of the building project, attractive quantity of working day morning peak hours, occurrence quantity of rest day evening peak hours, and attractive quantity of rest day evening peak hours, considering the construction area of different functional areas, per unit area residents travel rate, peak hours to increase the number of trips, and other factors. Through analysis and calculation, induced traffic demand can be obtained in the peak hours of building projects. The early peak in the n years is 13,440 (person-time/h). The evening peak in the n year is 13,357 (person-time/h). The early peak in the n+5 year is 15,380 (person-time/h). The evening peak in the n +5 year is 15,472 (person-time/h). The traffic volume in the n year early peak is 2766 (veh/h). The traffic volume in the n year evening peak is 2853 (veh/h). The traffic volume in the n+5 year early peak is 3685 (veh/h). In this paper, the prediction of induced traffic volume of Changchun Kuancheng automobile trade logistics park can provide database for traffic planning and design. It also can effectively avoid the emergence of traffic congestion so as to meet the needs of road traffic in the coming years.

Keywords

Induced traffic volume Residents travel rate Demand forecast New project 

Notes

Acknowledgements

This work is supported by China Postdoctoral Science Foundation (No. 2016M601373). The project of Shenyang Social Sciences Association (SYSK2017-08-05).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Liu Yang
    • 1
  • Wang Jinling
    • 1
  • Bian Shuai
    • 1
  • Xing Yan
    • 1
  • Bai Zhu
    • 1
  • Zhang Siqi
    • 1
  1. 1.School of Transportation EngineeringShenyang Jianzhu UniversityShenyangChina

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