Abstract
To mitigate roadway congestion, traffic management centers monitor freeway networks and provide traffic information. Not only traffic conditions but also vehicle emissions are used to measure and evaluate air quality, its impact and operational strategies. Using reidentification (REID) information, which is an inductive-loop-detector-based advanced traffic surveillance system, this study introduces real-time speed profile estimation (SPE) methodology for estimating microscopic freeway emissions. The methodology generates individual vehicular speed profiles using a parabolic function and genetically optimized 5th-order Fourier series. Also, Next Generation SIMulation (NGSIM) US101 data were used for model calibration. Results indicate that emissions can be estimated using the proposed method with less than 4 % error. The SPE, which is real-time, cost-efficient and accurate, is a very promising freeway emissions monitoring methodology.