Left-turning vehicles from minor streets tend to generate hazards when merging into major streets at un-signalized T-intersections. However, the characteristics of such behavior have been studied relatively little. In this study, an eight-hour video was recorded at un-signalized T-intersections in Nanjing. Two kinds of data were collected from the video, including 1) vehicle trajectories, as well as the corresponding speed profiles and the time records; 2) vehicle yielding characteristics. Considering merging points, diverging points, and turning radius, vehicle trajectories were clustered into six groups. A binary logistic model was developed to evaluate how traffic flow characteristics affected the yielding behavior of left-turning vehicles. A multinomial logistic model was proposed to formulate the choices for six trajectory patterns. The binary logistic model indicated that vehicles would stop when meeting a platoon. The regression model results of the multinomial logistic model showed that high mainline speed encourages the abnormal trajectory patterns. It was found that well-designed object markers and islands in the T-intersection are able to reduce illegal driving behavior and improve safety.
Irregular Merging Behavior Investigation of Left-Turning Vehicles at Un-Signalized T-Intersections
17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China
CICTP 2017 ; 4541-4550
2018-01-18
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Analysis of the Trajectories of Left-turning Vehicles at Signalized Intersections
BASE | 2020
|Pedestrian conflicts and left-turning traffic at signalized intersections
British Library Conference Proceedings | 1995
|Transportation Research Record | 2014
|Transportation Research Record | 2012
|