The traffic safety issue of freeway off-ramp has attracted much attention, to study the motion patterns of vehicle at freeway off-ramp, a trajectory clustering method based on similarity of driving behavior feature was proposed in this paper. Traffic video data was collected by an unmanned aerial vehicle and 472 vehicle driving trajectories composed of spatial position, longitudinal speed, lateral speed, speed, longitudinal acceleration, lateral acceleration, were extracted. Based on these parameters, DTW was used to build a similarity model to measure the similarity between vehicle trajectories and a trajectory clustering method was proposed based on DBSCAN clustering algorithm. Based on trajectory clustering results, different motion patterns including regular motion patterns of driving in one lane and changing lane to adjacent lane, improper lane changing motion patterns of vehicle crossing at least one lane and illegal motion pattern of overtaking at off-ramp, are extracted. Besides, representative trajectory of each clusters can be used to detect different trajectories and determine new abnormal trajectories.

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