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The tracking of objects for an autonomous vehicle requires sufficiently reliable data processing and association. In this paper, the signal data processing of sensed LIDAR and the multiple target track management algorithm of a maneuvering vehicle are presented. The algorithm is employed for 2D LIDAR sensor mounted in a moving vehicle and navigating in a high-way. The adaptive segmentation, feature creation from point cloud, data association and prediction modelling are the key features of track management. Initialization of the track has been developed based on constant velocity model hypothesis in order to facilitate target management in a high-way crowded environment. The multiple target tracking are associated with feature identification of the targets and also prediction modelling of moving occluded object. The prediction model of moving vehicles and pedestrians are the focus area of this research.