Drive quality analysis of lane change maneuvers for naturalistic driving studies

Analysis of naturalistic driving data provides a rich set of semantics which can be used to determine the driving characteristics that could lead to crashes and near-crashes. In this paper, we introduce “drive quality” analysis as part of the drive analysis process of naturalistic driving studies (NDSs) that we have previously introduced in [1]. In this first work on drive quality analysis for NDS data reduction, lane change maneuvers that are reduced from naturalistic driving data are further analyzed in a detailed manner in order to characterize them. Visual data from multiple perspectives and the data from in-vehicle sensors are used to characterize lane changes based on both the ego-vehicle kinematics and ego-vehicle surround dynamics. According to available literature on NDS and data reduction, this is the first work that presents an analysis of visual data from multiple perspectives to characterize and extract semantics related to ego-vehicle maneuvers in NDSs such as SHRP2.