An analysis of pedestrian walking behavior using gait parameters is presented; it uses automated video analysis to collect pedestrian data at a signalized intersection in Nanjing, China. Two aspects of microscopic pedestrian behavior are considered: First, the walking mechanism represented by pedestrian gait parameters. Second, the non-conforming crossing behavior of pedestrians. The effect of various pedestrian related attributes are investigated. The results show high accuracy in automatically detecting pedestrian violations, with an 85.2% correct detection rate. The walking speed and gait parameters for spatial violators are found to be significantly higher compared to non-violators. It is also found that pedestrians who enter the crosswalk during the late stage of the green pedestrian phase often adopt higher walking speed. The gait analysis shows that males tend to have a higher walking speed, walk ratio and longer step length than females. Single pedestrians are found to have higher speed and step frequency compared to pedestrians in groups. The presence of bikes on crosswalks significantly decreases the pedestrian walking speed, step length and frequency, leading to more gait variability. Such results are useful for many future applications such as calibration of simulation models and violation detection.

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Automated analysis of pedestrian walking behaviour at a signalised intersection in China

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