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For machine translations using a parallel corpus, it is effective to extract partial correspondences: pairs of phrases of the source language(SL) and target language(TL) in bilingual sentences. However, it is difficult to extract the partial correspondences correctly and efficiently in the data sparse corpus. In this paper, we propose a new learning method that extracts the partial correspondences...
In this paper, we propose a new framework to discriminate the initial maneuver of lane-crossing event from driver-correction event, which is the primary reason for false warnings of the lane departure prediction systems. The proposed algorithm validates the beginning episode of the trajectory of driving signals whether it will cause a lane crossing event or not, by employing driver behavior models...
This paper describes a method to generate vehicle trajectories of lane change paths for individual drivers. Although each driver has a consistent preferance in the lane change behavior, lane-changing time and vehicle trajectory are uncertain due to the presence of surrounding vehicles. To model this uncertainty, we propose a statistical driver model. We assume that a driver plans various vehicle trajectories...
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