Modeling And Application Of CO₂ Emissions From Mixed Traffic Flow At Urban Road Signal Intersections

The formulation of carbon dioxide peaking and carbon neutral strategies poses a serious challenge to carbon emission reduction in the transportation industry,and CO₂ emissions from motor vehicles have become one of the important sources of CO₂ emissions in Chinese cities.As the throat of urban road network,signal intersections,with frequent vehicle acceleration,deceleration and idling,will generate more energy consumption and emissions.Existing signal intersection studies only consider fuel vehicle emissions,and with the rapid development of electric vehicles,there exists a state of mixed traffic both fuel vehicles and electric vehicles at intersections for quite a long time in the future,and it is important to study the carbon emissions of mixed traffic flow at urban road signal intersections for accurate calculation and simulation.In this study,two intersections both Qixing Road and Lijiang Road,and Zhongshan Middle Road and Jiefang West Road were selected as the measurement sites.The traffic operation parameters such as traffic flow,vehicle model ratio,signal timing,average stopping delay at the intersection,and environmental parameters such as temperature,relative humidity,wind speed,and CO₂ concentration were collected and analyzed on site from July 12,2022 to July 17,2022.The results show that the main vehicle types at urban road signal intersections in Guilin are small electric vehicles and small fuel cars,accounting for 18.36%and 75.53%respectively,and the mixing ratio of electric vehicles to fuel vehicles is 1:4.The CO₂ concentration in the air at the intersections is closely related to the traffic flow,and the CO₂ concentration difference between the entrance measured point and the reference point at the intersections increases with the increase of traffic flow.In order to clarify the relationship between the traffic flow and the change of CO₂ concentration in the air at the intersection,a linearly fitted was applied to clarify the relationship between the traffic flow at different time periods and the CO₂ concentration difference between the intersection and the reference measurement point.The linear fitting coefficient R² was 0.712,which was a good fit of the model.Based on vehicle specific power theory and mechanical equilibrium principle,the CO₂emission estimation models of fuel and electric vehicles at signal intersections are established respectively.The CO₂ emission models of mixed traffic flow at signal intersections of urban roads are founded by combining the mixing ratio of fuel and electric vehicles.The VISSIM simulation model is established based on the field measurement data of the signal intersection,and the variables of the simulation model are calibrated to obtain the vehicle operation parameters of the intersection,and the CO₂ emission of the intersection of Qixing Road and Lijiang Road is calculated by combining the CO₂ model of mixed traffic of fuel and electric vehicles,and the results show that the average carbon emission of small fuel vehicles is 78.99g/vehicle,the average emission of medium fuel vehicles is 161.74g/vehicle,237.06g/vehicle for large fuel vehicles,15.45g/vehicle for small electric vehicles,and 46.36g/vehicle for large electric vehicles.In order to calculate CO₂ emissions at the intersection,different mixing ratios of fuel and electric vehicles were set and VISSM simulation and mixing carbon emission model were utilized.The results show that for every0.2 increase in the proportion of electric vehicles in mixed traffic,the average CO₂ emissions at signal intersections are reduced by about 16.25%.Under the same traffic scenario electric vehicles emit 80.25%less CO₂ than fuel vehicles,which mean increasing the proportion of electric vehicles contributes to intersection CO₂ emission reduction.Through the correlation analysis of the field measured data at the intersection of Qixing Road and Lijiang Road,the main factors affecting the CO₂ concentration at the intersection were determined,and the prediction model of CO₂ concentration at the mixed intersection was established and optimized.The prediction model of CO₂ concentration at the intersection of Zhongshan Middle Road and Jiefang West Road was validated by using the measured data,and the results showed that the average of the relative error percentage between the predicted value of the prediction model and the actual value measured in the field was 4.33%,and the confidence of the regression model was high.The research results are beneficial to traffic planning and the formulation of intersection traffic control strategy optimization with the aim of reducing carbon dioxide emission and lay a foundation for accurate calculation and simulation of carbon emissions at mixed intersections.