Impacts of enforcement cameras on pedestrians' risk perception and drivers' behaviors at non-signalized crosswalks.

INTRODUCTION

Pedestrians are more vulnerable to traffic crashes than other road users, particularly at non-signalized crosswalks. Safety measures (such as law enforcement cameras) can be implemented to regulate road users' behavior and traffic safety. This study evaluates the effects of such cameras on pedestrian-vehicle conflicts by investigating different interaction patterns of pedestrian risk perception and driving style.

DATA

Field investigations were conducted at four non-signalized crosswalks. Video data were collected using unmanned aerial vehicles and roadside cameras.

METHOD

Two-step cluster analysis and k-means cluster analysis were employed to classify the pedestrian's behavior and driving style, respectively. Surrogate safety measures were adopted to measure the pedestrian-vehicle conflicts.

RESULTS AND CONCLUSIONS

The results suggest that the implementation of cameras would decrease both the actual and perceived risks of pedestrians, while the heterogeneity between the actual and perceived risk is more obvious at camera sites. They also indicate that the cameras have a positive influence on reducing drivers' aggressiveness and conflict severity. In terms of pedestrian-vehicle interaction patterns, the most severe conflicts occur when the pedestrian perceived risk level is low and the driving style is aggressive. Such dangerous interactions are observed more frequently at camera sites. In contrast, a safer interaction pattern is associated with a moderate driving style and cautious crossing behavior, which is more frequently observed at comparison sites. However, regardless of which interaction pattern is observed, the conflict severity is found to be lower at camera sites, indicating the effectiveness of the cameras.

PRACTICAL APPLICATIONS

Supplementary facilities, such as warning signs, flash lights, and speed control measures, should be implemented to maintain the effectiveness of the law enforcement cameras.