This study investigated the pedestrians crossing behavior at signalized intersections. Results showed that male pedestrians are more likely to involve in red light running violation and distractions behaviors than females. A Bayesian binary logit (BL) model was developed to identify how factors affected the probability of pedestrians red light violations at signalized intersection. Results show that age, gender, group size, cell phone use, pedestrian signal type, pedestrian volume, and pedestrian signal green ratio are statistically significant in the model. Furthermore, odds ratio (OR) techniques are used to quantitatively analyze the impacts of the interesting factors on pedestrian red light running rates.
Investigation of pedestrians crossing behavior at signalized intersections in China
2017-08-01
438047 byte
Conference paper
Electronic Resource
English
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