Detection and Tracking of Road Barrier Based on Radar and Vision Sensor Fusion

• Published in: Journal of sensors Vol. 2016; no. 2016; pp. 1 - 8
• Main Authors: Kim, Taeryun, Song, Bongsob
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2016; Hindawi Limited
• Subjects: Algorithms; Automobile industry; Barriers; Cameras; Drivers; Kalman filters; Mean square errors; Radar; Roads; Sensors; Tracking; Vehicles; United States > US
• ISSN: 1687-725X; 1687-7268
• DOI: 10.1155/2016/1963450

The detection and tracking algorithms of road barrier including tunnel and guardrail are proposed to enhance performance and reliability for driver assistance systems. Although the road barrier is one of the key features to determine a safe drivable area, it may be recognized incorrectly due to performance degradation of commercial sensors such as radar and monocular camera. Two frequent cases among many challenging problems are considered with the commercial sensors. The first case is that few tracks of radar to road barrier are detected due to material type of road barrier. The second one is inaccuracy of relative lateral position by radar, thus resulting in large variance of distance between a vehicle and road barrier. To overcome the problems, the detection and estimation algorithms of tracks corresponding to road barrier are proposed. Then, the tracking algorithm based on a probabilistic data association filter (PDAF) is used to reduce variation of lateral distance between vehicle and road barrier. Finally, the proposed algorithms are validated via field test data and their performance is compared with that of road barrier measured by lidar.