The primary objective of this study is to quantitatively evaluate the impacts of driver population heterogeneity on capacity and traffic performance at basic roadway segments. Drivers were classified as two categories including novice drivers and experienced drivers, and they mainly differs in driving experience. On-road experiments were conducted for measuring the car-following data associated with the test drivers. Based on a nonlinear optimization procedure, the improved intelligent driver model was calibrated by minimizing the deviation between the observed driving trajectories and the simulated dynamics. Capacity and traffic performance were analyzed with respect to different driver population compositions by using the calibrated simulation model. The simulation results revealed that the mixture rate of novice drivers can result in capacity reduction and poor traffic performance. Specifically, the reduction rate of capacity may reached up to 28%, and most of other key measures representing traffic performance characteristics also significantly deteriorated.
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