Analysis of Merging Behavior Parameters Using NGSIM Data Sets

Abstract

A merging event involves three vehicles: the merging vehicle and the putative leading and following vehicles on the mainline. Understanding the interactions of the subject vehicle with the surrounding vehicles is fundamental to the study of the safety and modeling of merging behavior. This research studies the statistical properties of 8 lane changing parameters. These parameters describe the gaps, times to collision between vehicles and the merging vehicle’s speed. Visual angle parameters are first analyzed during the merging situation. The parameter values were extracted from the vehicle trajectory data in the NGSIM data sets. The results show that: (i) some of the parameters are highly correlated; (ii) visual angles are highly correlated with other parameters except the time-to-collisions; (iii) the visual angles are best described by the gamma distribution; (iv) the gaps are best described by the log-logistic distribution; (v) the times to collisions and speed are best described by the logistic distribution. The results can help promote temporal and spatial accuracy of merging behavior models.