RESUMEN
Despite awareness campaigns and legal consequences, speeding is a significant cause of road accidents and fatalities globally. To combat this issue, understanding the impact of a driver's visual surroundings is crucial in designing roadways that discourage speeding. This study investigates the influence of visual surroundings on drivers in 15 US cities using 3,407,253 driver view images from Lytx, covering 4,264 miles of roadways. By segmenting and analyzing these images along with vehicle-related variables, the study examines factors affecting speeding behavior. After filtering the images, to ensure an accurate representation of the driver's view, 1,340,035 driver view images were used for analysis. Statistical models, including hurdle beta and bivariate probit models with random driver effects as well as Machine Learning's eXtreme Gradient Boosting (XGBoost), were employed to estimate speeding behavior. The results indicate that factors within the driver's visual environment, weather conditions, and driver heterogeneity significantly impact speeding. Speeding behavior also varies across geographic locations, even within the same city, suggesting a connection between local context and speeding. The study highlights the importance of the driver's environment, showing that more open spaces encourage speeding, while areas with trees and buildings are associated with reduced speeding. Notably, this research differs from previous studies by utilizing real-time data from dash cameras, providing a dynamic and accurate representation of the driver's visual surroundings. This approach enhances the reliability of the findings and empowers transportation engineers and planners to make informed decisions when designing roadways and implementing interventions to address effectively excessive speeding. In addition to examining speeding behavior, the study also analyzes time-headway, a key factor affecting safety and risky driver behavior, to explore its relationship with speeding. The findings offer valuable insights into the factors influencing speeding and the driver's visual environment. These insights can inform efforts to create environments that discourage speeding (and close car following) and ultimately reduce severe accidents caused by excessive speed (and tailgating).
Asunto(s)
Conducción de Automóvil , Humanos , Accidentes de Tránsito/prevención & control , Reproducibilidad de los Resultados , Asunción de Riesgos , CiudadesRESUMEN
Police departments use body-worn cameras (body cams) and dashboard cameras (dash cams) to monitor the activity of police officers in the field. Video from these cameras informs review of police conduct in disputed circumstances, often with the goal of determining an officer's intent. Eight experiments (N = 2,119) reveal that body cam video of an incident results in lower observer judgments of intentionality than dash cam video of the same incident, an effect documented with both scripted videos and real police videos. This effect was due, in part, to variation in the visual salience of the focal actor: the body cam wearer is typically less visually salient when depicted in body versus dash cam video, which corresponds with lower observer intentionality judgments. In showing how visual salience of the focal actor may introduce unique effects on observer judgment, this research establishes an empirical platform that may inform public policy regarding surveillance of police conduct.