摘要: |
Transportation has proven one of the most stubborn challenges in reducing carbon emissions. Vehicle Specific Power (VSP) is the most advanced concept to reflect a vehicle operation impact on emission; however, data for calculating VSP is currently dependent upon the limited samples of testing vehicles equipped with on-board or portable emission measurement system. Dual loops (in-pavement sensors) are widely utilized in collecting continuous traffic data and their outputs could be utilized as a rich data source for calculating VSP. Most existing loop models for measuring speeds and vehicle classifications have been proved accurate against light traffic, but they are not reliable under other traffic conditions like synchronized or stop-and-go congestion. Fortunately, recent studies ("OTC vehicle classification" project) have resulted in positive solutions to ensure the accuracy of loop models leading to the technical promise for developing VSP-based models of estimating micro-level emissions under various traffic operations by using dual-loop data. This project will develop a framework to integrate the improved dual-loop models with VSP-based models into a procedure for estimating emission impact of traffic flow operation over dual-loop monitoring stations in highways. Remote sensing method will be used to monitor CO and CO2 at the "OTC vehicle classification" project site. Meanwhile, VEVID-based approach will be applied to calibrate dual-loop models for generating accurate fleet distributions. Global Positioning System (GPS) Travel Loggers will be employed to check the traffic patterns and relevant VSP profile along the selected section of the highway. The results will be adapted for use in the classroom. |