Objective: Pedestrian violation is a major cause of traffic accidents involving pedestrians. The research objectives were to investigate the relationship between waiting duration and pedestrian violation and to provide a qualitative and quantitative analysis of the effects of human factors and external environmental factors on street-crossing behavior. Methods: Pedestrians’ street-crossing behavior was examined by modeling the waiting duration at signalized crosswalk. Pedestrian waiting duration was collected by video cameras and it was assigned as censored and uncensored data to distinguish between normal crossing and violating crossing. A nonparametric baseline duration model was introduced, and variables revealing personal characteristics, traffic conditions, and trip features were defined as covariates to describe the effects of internal and external factors. Results: Pedestrians’ crossing behaviors represented positive duration dependence that the longer the waiting time elapsed the more likely pedestrians would end the wait soon. The violation inclination of most pedestrians increased with the increasing waiting duration, but about 10 percent of pedestrians were at high risk of violation to cross the street. About half of pedestrians would still obey the traffic rules even after waiting for 50 s by the street. Human factors and the external environment played an important role in street-crossing behavior, especially for factors that involved pedestrians’ subjective willingness. Conclusions: The street-crossing behavior of pedestrians was time dependent. Pedestrians behave differently under the effects of various factors. Pedestrian safety interventions that aim at reducing pedestrian injuries may need to consider these effects. The pedestrians’ behavioral modifications, such as enhancing the safety awareness, might be the most efficient means to reducing the likelihood of pedestrian violation, though environmental modifications also worked well in improving pedestrian safety.

SUMMARY: In this paper, we develop a macro traffic flow model with consideration of varying road conditions. Our analytical and numerical results illustrate that good road condition can enhance the speed and flow of uniform traffic flow whereas bad road condition will reduce the speed and flow. The numerical results also show that good road condition can smooth shock wave and improve the stability of traffic flow whereas bad road condition will lead to steeper shock wave and reduce the stability of traffic flow. Our results are also qualitatively accordant with empirical results, which implies that the proposed model can qualitatively describe the effects of road conditions on traffic flow. These results can guide traffic engineers to improve the road quality in traffic engineering. Copyright © 2012 John Wiley & Sons, Ltd.