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It has been widely shown that pedestrians’ level of frustration grows with the increase of pedestrian delay, and may cause pedestrians to violate the signals. However, for agencies seeking to use multimodal signal performances for signal operations, the pedestrian delay is not always readily available. To tackle this issue, this study proposed a finite mixture modeling method to estimate pedestrian delay using high-resolution event-based data collected from the smart sensors. The proposed method was used to estimate pedestrian delay at four signalized intersections on a major arterial corridor in Pima County, Arizona. The results showed the proposed method was able to capture and track the actual pedestrian delay fluctuations during the day at all the study intersections with average errors of 10 s and 13 s for mean-absolute-error and root-mean-square-error, respectively. In addition, the proposed model was …