With the development of drone technology and oblique photogrammetry technology, the acquisition of oblique photogrammetry models and basemap becomes more and more convenient and quickly. The increase in the number of ...With the development of drone technology and oblique photogrammetry technology, the acquisition of oblique photogrammetry models and basemap becomes more and more convenient and quickly. The increase in the number of basemap leads to excessively redundant basemap tiles requests in 3D GIS when loading oblique photogrammetry models, which slows down the system. Aiming at improving the speed of running system, this paper proposes a dynamic strategy for loading basemap tiles. Different from existing 3D GIS which loading oblique photogrammetry models and basemap tiles inde-pendently, this strategy dynamically loads basemap tiles depending on different height of view and the range of loaded oblique photogrammetry models. We achieve dynamic loading of basemap tiles by predetermining whether the basemap tiles will be covered by the oblique photogrammetry models. The experimental results show that this strategy can greatly reduce the num-ber of redundant requests from the client to the server while ensuring the user’s visual requirements for the oblique photogrammetric model.展开更多
为了量化不同驾驶次任务下驾驶人视觉负荷特征,基于驾驶模拟平台搭建各类型次任务加载下的高速公路跟车场景,招募46名被试开展试验。采集驾驶人注视、扫视及瞳孔直径等眼动指标,对比不同驾驶次任务下视觉特征变化规律。基于因子分析方...为了量化不同驾驶次任务下驾驶人视觉负荷特征,基于驾驶模拟平台搭建各类型次任务加载下的高速公路跟车场景,招募46名被试开展试验。采集驾驶人注视、扫视及瞳孔直径等眼动指标,对比不同驾驶次任务下视觉特征变化规律。基于因子分析方法构建驾驶人视觉负荷评价模型,量化不同次任务下的视觉负荷。在视觉负荷量化的基础上,引入变异系数,采用K均值聚类算法将驾驶人视觉负荷分为低、中、高稳定型类别。并通过相关性分析,探究次任务下驾驶人视觉负荷与行车安全的关系。结果表明,执行快速串行视觉呈现(Rapid Serial Visual Presentation, RSVP)任务使驾驶人扫视速度和扫视幅度显著增加,单次注视持续时间显著下降。但驾驶人通过增加注视频次,弥补了总注视持续时长的下降,即采取小幅快速搜索方式补偿了视觉信息的获取。执行延迟数字召回任务(1-Back)占用驾驶人认知资源,导致视觉搜索出现弱化。驾驶人不仅减少了对非前方道路区域的关注,且扫视频率和注视持续时长占比均显著下降。视觉负荷量化模型结果显示,RSVP手机操作次任务下相比正常驾驶视觉负荷平均上升了22.29%,执行1-Back数字记忆次任务时视觉负荷平均下降了8.93%。不同驾驶人视觉负荷存在明显个体差异,64.2%的被试视觉负荷可以保持高稳定性。驾驶人视觉负荷与车速指标虽不相关,但与车头间距、车头时距和时间裕度等安全替代指标具有显著负相关,表明次任务加载下视觉负荷过高会导致驾驶绩效下降,影响行车安全。展开更多
文摘With the development of drone technology and oblique photogrammetry technology, the acquisition of oblique photogrammetry models and basemap becomes more and more convenient and quickly. The increase in the number of basemap leads to excessively redundant basemap tiles requests in 3D GIS when loading oblique photogrammetry models, which slows down the system. Aiming at improving the speed of running system, this paper proposes a dynamic strategy for loading basemap tiles. Different from existing 3D GIS which loading oblique photogrammetry models and basemap tiles inde-pendently, this strategy dynamically loads basemap tiles depending on different height of view and the range of loaded oblique photogrammetry models. We achieve dynamic loading of basemap tiles by predetermining whether the basemap tiles will be covered by the oblique photogrammetry models. The experimental results show that this strategy can greatly reduce the num-ber of redundant requests from the client to the server while ensuring the user’s visual requirements for the oblique photogrammetric model.
文摘为了量化不同驾驶次任务下驾驶人视觉负荷特征,基于驾驶模拟平台搭建各类型次任务加载下的高速公路跟车场景,招募46名被试开展试验。采集驾驶人注视、扫视及瞳孔直径等眼动指标,对比不同驾驶次任务下视觉特征变化规律。基于因子分析方法构建驾驶人视觉负荷评价模型,量化不同次任务下的视觉负荷。在视觉负荷量化的基础上,引入变异系数,采用K均值聚类算法将驾驶人视觉负荷分为低、中、高稳定型类别。并通过相关性分析,探究次任务下驾驶人视觉负荷与行车安全的关系。结果表明,执行快速串行视觉呈现(Rapid Serial Visual Presentation, RSVP)任务使驾驶人扫视速度和扫视幅度显著增加,单次注视持续时间显著下降。但驾驶人通过增加注视频次,弥补了总注视持续时长的下降,即采取小幅快速搜索方式补偿了视觉信息的获取。执行延迟数字召回任务(1-Back)占用驾驶人认知资源,导致视觉搜索出现弱化。驾驶人不仅减少了对非前方道路区域的关注,且扫视频率和注视持续时长占比均显著下降。视觉负荷量化模型结果显示,RSVP手机操作次任务下相比正常驾驶视觉负荷平均上升了22.29%,执行1-Back数字记忆次任务时视觉负荷平均下降了8.93%。不同驾驶人视觉负荷存在明显个体差异,64.2%的被试视觉负荷可以保持高稳定性。驾驶人视觉负荷与车速指标虽不相关,但与车头间距、车头时距和时间裕度等安全替代指标具有显著负相关,表明次任务加载下视觉负荷过高会导致驾驶绩效下降,影响行车安全。
