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.
Highlights
With the degradation of the environment, sustainable development has drawn wide attention around the world [1,2,3]
electronic toll collection (ETC) contributes to the reduced congestion in toll plazas, and has been proven in previous studies as an promising approach that contributes to reduced fuel consumption and vehicle emissions compared to manual toll collection (MTC), due to the mitigation of congestion and stop-and-go operations [17]
Regression models are most commonly used in vehicle emission estimation and prediction studies, due to their superior performance and ability to integrate with the Geographic Information System (GIS)
Summary
With the degradation of the environment, sustainable development has drawn wide attention around the world [1,2,3]. Vehicles at freeway toll plazas can emit more emissions and generate more air pollution due to the stop-and-go or slow-and-go behaviors of vehicles [11,12,13]. An increasing number of studies pay attention to the urgent problem of vehicle emissions at freeway toll plazas [14]. ETC contributes to the reduced congestion in toll plazas, and has been proven in previous studies as an promising approach that contributes to reduced fuel consumption and vehicle emissions compared to MTC, due to the mitigation of congestion and stop-and-go operations [17]. ETC enables freeway management agencies to collect freeway traffic data, including the number and type of vehicles, travel route, time and speed, and vehicle numbers equipped with the ETC transponders [9]
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