Estimation of Vehicle Emission Models at Freeway Toll Plazas

Freeway transportation contributes to air pollution because of the release of pollutants during motor vehicle operations. In particular, toll plazas can create congestion, which leads to increased fuel consumption and emission rates as a result of speed reduction and frequent stop-and-go operations. Consequently, the primary objectives of this study were to compare the changes in speed, acceleration, delay time, and emission values measured at electronic toll collection (ETC) and manual toll collection (MTC) lanes by applying statistical methods; and to develop a model trees-based vehicle specific power (VSP) regression method to estimate emissions of CO, HC, NOₓ, and CO₂ for petrol and diesel vehicles at freeway toll plazas. Vehicle speed, acceleration, delay time, and emission data were collected at two freeway toll plazas in China. The results showed that there was significant difference between ETC and MTC, and petrol and diesel vehicles, indicating different toll collections and fuel types of vehicles had impacts on the vehicle dynamic behaviors and emissions at freeway toll plazas. Furthermore, to evaluate the proposed model trees’ performance, a polynomial regression method using linear, quadratic, and cubic terms of transient speed and acceleration was utilized for comparison. According to the results, the proposed method had more accurate and reliable estimation, which reduced mean absolute percentage error (MAPE) by 52.5%, root mean squared error (RMSE) by 55.0%, mean absolute error (MAE) by 54.4%, and increased R-squared from 0.714 to 0.833 compared with the values of the competing method. In addition, heat maps were applied in this study to better understand changes in vehicle emissions for different locations at freeway toll plazas.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality.
  • Authors:
    • Wang, Chao
    • Ye, Zhirui
    • Yan, Yu
    • Sun, Huaqiang
    • Gao, Liangpeng
    • Sun, Zhuoqun
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Pagination: 4p

Subject/Index Terms

Filing Info

  • Accession Number: 01661289
  • Record Type: Publication
  • Report/Paper Numbers: 18-02074
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 26 2018 1:45PM