Signalized intersections next to each other spatially on the same arterial share some unobservable information such as traffic flow and roadway characteristics, thus this study is to investigate the impact of access management techniques on crash counts at signalized intersections where the unobservable information is considered by developing panel data crash count data models based on crash data from 300 signalized intersections in Southern Nevada. Panel data random-effect model was selected to take into account the unobserved factors for each unique arterial. It was showed that Negative Binomial regression models were better able to reflect the dispersion in the crash data. Therefore, the random-effect negative binomial model (RENB) was applied to investigate the relationship between crash occurrence and access management techniques. The results showed that five variables significantly affected the safety at signalized intersections. The average length of corner clearance had negative impact on intersection crash occurrence while the total traffic flow in all directions, land use types, the number of lanes for minor streets and posted speed limit on minor streets were positively related to crashes at signalized intersections.
展开▼
