IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i21p8959-d436180.html
   My bibliography  Save this article

A Model Tree-Based Vehicle Emission Model at Freeway Toll Plazas

Author

Listed:
  • Yueru Xu

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
    School of Transportation, Southeast University, Nanjing 210096, China)

  • Chao Wang

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
    School of Transportation, Southeast University, Nanjing 210096, China)

  • Yuan Zheng

    (School of Transportation, Southeast University, Nanjing 210096, China
    Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Hong Kong, China)

  • Zhuoqun Sun

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
    School of Transportation, Southeast University, Nanjing 210096, China)

  • Zhirui Ye

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
    School of Transportation, Southeast University, Nanjing 210096, China)

Abstract

With the increased concern over sustainable development, many efforts have been made to alleviate air quality deterioration. Freeway toll plazas can cause serious pollution, due to the increased emissions caused by stop-and-go operations. Different toll collections and different fuel types obviously influence the vehicle emissions at freeway toll plazas. Therefore, this paper proposes a model tree-based vehicle emission model by considering these factors. On-road emissions data and vehicle operation data were obtained from two different freeway toll plazas. The statistical analysis indicates that different methods of toll collection and fuel types have significant impacts on vehicle emissions at freeway toll plazas. The performance of the proposed model was compared with a polynomial regression method. Based on the results, the mean absolute percentage error (MAPE), root mean squared error (RMSE), and mean absolute error (MAE) of the proposed model were all smaller, while the R -squared value increased from 0.714 to 0.833. Finally, the variations of vehicle emissions at different locations of freeway toll plazas were calculated and shown in heat maps. The results of this study can help better estimate the vehicle emissions and give advice to the development of electronic toll collection (ETC) lanes and relevant policies at freeway toll plazas.

Suggested Citation

  • Yueru Xu & Chao Wang & Yuan Zheng & Zhuoqun Sun & Zhirui Ye, 2020. "A Model Tree-Based Vehicle Emission Model at Freeway Toll Plazas," Sustainability, MDPI, vol. 12(21), pages 1-15, October.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:8959-:d:436180
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/21/8959/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/21/8959/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lumbreras, J. & Valdés, M. & Borge, R. & Rodriguez, M.E., 2008. "Assessment of vehicle emissions projections in Madrid (Spain) from 2004 to 2012 considering several control strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 646-658, May.
    2. Omer Saud Azeez & Biswajeet Pradhan & Helmi Z. M. Shafri, 2018. "Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS," Sustainability, MDPI, vol. 10(10), pages 1-18, September.
    3. Jiancheng Weng & Ru Wang & Mengjia Wang & Jian Rong, 2015. "Fuel Consumption and Vehicle Emission Models for Evaluating Environmental Impacts of the ETC System," Sustainability, MDPI, vol. 7(7), pages 1-16, July.
    4. Tseng, Po-Hsing & Lin, Dung-Ying & Chien, Steven, 2014. "Investigating the impact of highway electronic toll collection to the external cost: A case study in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 265-272.
    5. Yu, Qian & Li, Tiezhu & Li, Hu, 2016. "Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving," Applied Energy, Elsevier, vol. 161(C), pages 101-111.
    6. Chao Wang & Zhuoqun Sun & Zhirui Ye, 2020. "On-Road Bus Emission Comparison for Diverse Locations and Fuel Types in Real-World Operation Conditions," Sustainability, MDPI, vol. 12(5), pages 1-14, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ioannis-Dimosthenis Ramandanis & Ioannis Politis & Socrates Basbas, 2020. "Assessing the Environmental and Economic Footprint of Electronic Toll Collection Lanes: A Simulation Study," Sustainability, MDPI, vol. 12(22), pages 1-25, November.
    2. Seo, Youngguk & Kim, Seong-Min, 2013. "Estimation of greenhouse gas emissions from road traffic: A case study in Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 777-787.
    3. Xiaowei Song & Yongpei Hao, 2019. "Vehicular Emission Inventory and Reduction Scenario Analysis in the Yangtze River Delta, China," IJERPH, MDPI, vol. 16(23), pages 1-21, November.
    4. Marina Milenković & Miloš Nikolić & Draženko Glavić, 2022. "Optimization of toll road lane operation: Serbian case study," Operational Research, Springer, vol. 22(5), pages 5297-5322, November.
    5. Xiaonian Shan & Xiaohong Chen & Wenjian Jia & Jianhong Ye, 2019. "Evaluating Urban Bus Emission Characteristics Based on Localized MOVES Using Sparse GPS Data in Shanghai, China," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    6. Xiaowei Song & Yongpei Hao & Xiaodong Zhu, 2019. "Air Pollutant Emissions from Vehicles and Their Abatement Scenarios: A Case Study of Chengdu-Chongqing Urban Agglomeration, China," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    7. Gia-Shie Liu & Kuo-Ping Lin, 2020. "The Online Distribution System of Inventory-Routing Problem with Simultaneous Deliveries and Returns Concerning CO 2 Emission Cost," Mathematics, MDPI, vol. 8(6), pages 1-27, June.
    8. Jochem, Patrick & Doll, Claus & Fichtner, Wolf, 2016. "External costs of electric vehicles," MPRA Paper 91602, University Library of Munich, Germany.
    9. Wu, Tian & Han, Xiao & Zheng, M. Mocarlo & Ou, Xunmin & Sun, Hongbo & Zhang, Xiong, 2020. "Impact factors of the real-world fuel consumption rate of light duty vehicles in China," Energy, Elsevier, vol. 190(C).
    10. Rajaeifar, Mohammad Ali & Tabatabaei, Meisam & Aghbashlo, Mortaza & Nizami, Abdul-Sattar & Heidrich, Oliver, 2019. "Emissions from urban bus fleets running on biodiesel blends under real-world operating conditions: Implications for designing future case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 276-292.
    11. Feng Mao & Zhiheng Li & Kai Zhang, 2021. "A Comparison of Carbon Dioxide Emissions between Battery Electric Buses and Conventional Diesel Buses," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
    12. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    13. Ahmed Abdulkareem Ahmed Adulaimi & Biswajeet Pradhan & Subrata Chakraborty & Abdullah Alamri, 2021. "Traffic Noise Modelling Using Land Use Regression Model Based on Machine Learning, Statistical Regression and GIS," Energies, MDPI, vol. 14(16), pages 1-19, August.
    14. Xianwang Li & Zhongxiang Huang & Saihu Liu & Jinxin Wu & Yuxiang Zhang, 2023. "Short-Term Subway Passenger Flow Prediction Based on Time Series Adaptive Decomposition and Multi-Model Combination (IVMD-SE-MSSA)," Sustainability, MDPI, vol. 15(10), pages 1-30, May.
    15. Miroslaw Smieszek & Vasyl Mateichyk & Magdalena Dobrzanska & Pawel Dobrzanski & Ganna Weigang, 2021. "The Impact of the Pandemic on Vehicle Traffic and Roadside Environmental Pollution: Rzeszow City as a Case Study," Energies, MDPI, vol. 14(14), pages 1-20, July.
    16. Shen, Yu & de Abreu e Silva, João & Martínez, Luis Miguel, 2014. "Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006," Journal of Transport Geography, Elsevier, vol. 41(C), pages 184-196.
    17. Sui, Yi & Zhang, Haoran & Shang, Wenlong & Sun, Rencheng & Wang, Changying & Ji, Jun & Song, Xuan & Shao, Fengjing, 2020. "Mining urban sustainable performance: Spatio-temporal emission potential changes of urban transit buses in post-COVID-19 future," Applied Energy, Elsevier, vol. 280(C).
    18. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2021. "Effects of passenger load, road grade, and congestion level on real-world fuel consumption and emissions from compressed natural gas and diesel urban buses," Applied Energy, Elsevier, vol. 282(PB).
    19. Pérez, Javier & de Andrés, Juan Manuel & Borge, Rafael & de la Paz, David & Lumbreras, Julio & Rodríguez, Encarnación, 2019. "Vehicle fleet characterization study in the city of Madrid and its application as a support tool in urban transport and air quality policy development," Transport Policy, Elsevier, vol. 74(C), pages 114-126.
    20. Nur Faseeha Suhaimi & Juliana Jalaludin & Suhaili Abu Bakar, 2021. "The Influence of Traffic-Related Air Pollution (TRAP) in Primary Schools and Residential Proximity to Traffic Sources on Histone H3 Level in Selected Malaysian Children," IJERPH, MDPI, vol. 18(15), pages 1-19, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:8959-:d:436180. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.