Vehicle Lane Merge Visual Benchmark

2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)(2020)

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摘要
Automated driving is regarded as the most promising technology for improving road safety in the future. In this context, connected vehicles have an important role regarding their ability to perform cooperative maneuvers for challenging traffic situations. We propose a benchmark for automated cooperative maneuvers. The targeted cooperative maneuver is the vehicle lane merge where a vehicle on the acceleration lane merges into the traffic of a motorway. The benchmark enables the evaluation of vehicle localization approaches as well as the study of cooperative maneuvers. It consists of temporally synchronized multi-view video streams, highly accurate camera calibration, and ground truth vehicle descriptions, including position, heading, speed, and shape. For benchmark generation, the lane merge maneuver is performed by human drivers on a test track, resulting in 85 lane merge data sets with various traffic situations and video recording conditions.
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关键词
ground truth vehicle descriptions,traffic situations,vehicle lane merge visual benchmark,automated driving,road safety,connected vehicles,acceleration lane,vehicle localization,synchronized multiview video streams,motorway,camera calibration
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