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An automated system for persistent real-time truck parking detection and information dissemination

机译:用于持续实时卡车停车检测和信息发布的自动化系统

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Tractor-trailer freight hauling has increased markedly within the United States over the past several years, resulting in higher truck volumes. commercial heavy vehicle drivers are required under federal Hours Of Services rules to rest and take breaks to mitigate driving while fatigued. Although there are many rest area facilities available to truck drivers, there is a lack of persistent timely information on truck parking availability. An automated real-time sensing system to directly detect and disseminate parking space occupancy from truck parking facilities is described in detail. The methodology and system architecture are presented in which robust, persistent, parking occupancy detection is achieved by extending Structure from Motion (SfM) techniques using a multiplicity of commercial, off-the-shelf cameras. The system architecture allows the approach to be scaled to a region-wide comprehensive truck parking information system for commercial heavy vehicle drivers and operators. Per parking space detection accuracy of 99% is achieved over continuous operation. Classification accuracy under diverse scene and parking behavior scenarios is discussed.
机译:在过去的几年中,牵引车的货运量在美国境内显着增加,导致卡车数量增加。联邦服务时间规则要求商用重型车辆驾驶员休息并休息,以减轻疲劳时的驾驶情况。尽管卡车司机可以使用许多休息区设施,但缺乏有关卡车停车位可用性的持续及时信息。详细描述了一种自动实时传感系统,该系统可直接检测并从卡车停车设施中散布停车位。提出了方法和系统架构,其中通过使用大量现成的摄像机扩展“运动结构”(SfM)技术来实现强大,持久的停车占用检测。该系统架构使该方法可以扩展到针对商用重型车辆驾驶员和操作员的区域范围的综合卡车停车信息系统。在连续运行中,每个停车位的检测精度达到99%。讨论了不同场景和停车行为场景下的分类精度。

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