کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
897950 | 915211 | 2012 | 12 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections](/preview/png/897950.png)
The Type II dilemma zone describes a segment of road on the approach to a signalized intersection where, if occupied by a motorist presented with the circular yellow indication, is likely to result in a motorist having difficulty deciding to stop at the stop line or proceed through the intersection. This phenomenon results in increased frequency of three failure conditions: rear-end collision at the stop line (excessive deceleration rates), the more severe right-angle crashes in the intersections, and left-turn head-on collisions (both resulting from incorrect estimates of clearance time). A more effective boundary definition for Type II dilemma zones could contribute to the safe design of signalized intersections. The prevailing approaches to dilemma zone delineation include the consideration of the vehicle’s travel time to the stop line or the driver’s likelihood of stopping at a particular distance from the stop line. The imprecision of the driver’s perception of speed and distance suggest that fuzzy logic may contribute to the identification of the Type II dilemma zone boundaries. A fuzzy logic (FL) model was constructed and validated from driver’s empirically observed behavior at high-speed signalized intersections. The research resulted in an increased understanding of the phenomenon which, when applied to the timing of signals and the placement of vehicle detection, can improve the overall safety of signalized intersections.
► Empirical driver behavior data was collected at 10 signalized intersection approaches.
► A fuzzy logic model for Type II dilemma zone driver behavior was constructed.
► The model was successfully validated against a field data and similar previous work.
► This model adds knowledge of driver behavior on high speed intersection approaches.
Journal: Transportation Research Part F: Traffic Psychology and Behaviour - Volume 15, Issue 2, March 2012, Pages 132–143