Advertisement

Investigating Private Cars Idling Behavior in Urban Areas

  • Lu Xing
  • Jie HeEmail author
  • Chen Zhang
  • Ziyang Liu
  • Hao Zhang
Conference paper
  • 18 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 617)

Abstract

The rapid mechanization in China results in excessive adverse effects recently, such as traffic congestion and air pollution. Affected by the negative effects, an increasing number of citizens decide to use their private cars only at a certain time, which leads to the urban private cars idling (UPCI) phenomenon. In order to investigate the UPCI behavior and its influence factors, this paper, taking Nanjing city in China as a case study, conducted a detailed survey including 279 private car owners. A logistic regression model was developed to investigate the impact factors related with UPCI. The result of regression indicated that the number of children in a family was an impeding factor which caused the fewer UPCI behaviors. The smaller job-housing distances and independence on vehicles, however, aggravated the UPCI phenomenon. The results of this study are beneficial to understand the UPCI behavior, and provide useful information for the effective urban transportation demand management (TDM) and necessary guidance for urban private car purchase and usage.

Keywords

Urban private car Idle Travel behavior Transportation demand management 

Notes

Acknowledgements

The author would like to thank the Fundamental Research Funds for the Central Universities and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX17-0148). Also thanks National Natural Science Foundation of China (Grant No. 51778141 and 71601046). Their assistance is gratefully acknowledged.

References

  1. 1.
    National Bureau of Statistic of China (2016) Annual report from National Bureau of Statistics of China (2005–2015). China Statistics PressGoogle Scholar
  2. 2.
    National Ministry of Public Security Transportation Bureau of China (2016) 2015 National Transportation Annual ReportGoogle Scholar
  3. 3.
    Beijing Traffic Development Research Center (2016) 2015 Beijing transportation development annual reportGoogle Scholar
  4. 4.
    Paul A (2013) Eisenstein of the Detroit Bureau, MSNBC, Americans drive less even as economy rebounds. Accessed Sept 1 2013Google Scholar
  5. 5.
    Ye J, Chen X, Zhang H (2013) Reducing the reliance on automobiles: Portland multi-modal transportation system development. Urban Transp China 1:10–17Google Scholar
  6. 6.
    Tuttle B (2013) What happens when we reach ‘Peak Car’? Time Magazine. Accessed Sep 1 2013Google Scholar
  7. 7.
    Nanjing Ministry of Public Security Transportation Bureau (2016) 2015 Nanjing transportation development annual reportGoogle Scholar
  8. 8.
    Zhang WT, Dong W (2004) SPSS statistical analysis basics tutorial. Higher Education Press, BeijingGoogle Scholar
  9. 9.
    Hu Z, Liu Q (2003) Research on logistic regression and independent variables preparation in questionnaire. J Zhongnan Univ Econ Law 5:128–132Google Scholar
  10. 10.
    Wu ZQ, Wang Y, Li W (2014) Matters need attention when using logistic regression analysis. Chin Circ J 29(3):24Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Lu Xing
    • 1
  • Jie He
    • 1
    Email author
  • Chen Zhang
    • 1
  • Ziyang Liu
    • 1
  • Hao Zhang
    • 1
  1. 1.School of TransportationSoutheast UniversityNanjingPeople’s Republic of China

Personalised recommendations