Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much infor...Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much information a pedestrian can perceive,thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit.Besides,the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed.By integrating game theory into a cellular automata simulation framework,the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper.A systematic analysis of the key factors influencing pedestrian evacuation is conducted,including visual radius and choice firmness of a pedestrian,initial crowd distribution of the room,exit layout as well as exit width.It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering,which is adverse to evacuation.The longer the pedestrian's visual radius,the earlier the pedestrian can determine his/her final selection of the exit.Compared with the scenario where the pedestrians are randomly distributed,pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits.Furthermore,the exit layout and exit width also have a certain influence on pedestrian evacuation process.The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.展开更多
To overcome the shortcomings of the traditional passive ranging technology based on image, such as poor ranging accuracy, low reliability and complex system, a new visual passive ranging method based on re-entrant coa...To overcome the shortcomings of the traditional passive ranging technology based on image, such as poor ranging accuracy, low reliability and complex system, a new visual passive ranging method based on re-entrant coaxial optical path is presented. The target image is obtained using double cameras with coaxial optical path. Since there is imaging optical path difference between the cameras, the images are different. In comparison of the image differences, the target range could be reversed. The principle of the ranging method and the ranging model are described. The relationship among parameters in the ranging process is analyzed quantitatively. Meanwhile,the system composition and technical realization scheme are also presented. Also, the principle of the method is verified by the equivalent experiment. The experimental results show that the design scheme is correct and feasible with good robustness. Generally, the ranging error is less than 10% with good convergence. The optical path is designed in a re-entrant mode to reduce the volume and weight of the system. Through the coaxial design,the visual passive range of the targets with any posture can be obtained in real time. The system can be widely used in electro-optical countermeasure and concealed photoelectric detection.展开更多
为提高移动机器人的跟随精度,对深度相机(RGB-D相机)测距进行研究,提出一种基于MRSD(Mask R-CNN and S2R-DepthNet)的移动机器人跟随系统。引入实例分割算法(Mask R-CNN)获取行人的前景掩膜;以掩膜为指导从深度图像中获取准确的行人区...为提高移动机器人的跟随精度,对深度相机(RGB-D相机)测距进行研究,提出一种基于MRSD(Mask R-CNN and S2R-DepthNet)的移动机器人跟随系统。引入实例分割算法(Mask R-CNN)获取行人的前景掩膜;以掩膜为指导从深度图像中获取准确的行人区域深度像素,引入深度估计算法(S2R-DepthNet)从彩色图像中推理深度图像以替换深度传感器引起的无效深度像素,提高测距的精度;建立基于Sage-Husa自适应滤波(SHAKF)的测距模型,提高量测信息异常情况下的测距鲁棒性,实现稳定跟随。实验结果表明,该方法能以设定距离准确跟随前方行人。展开更多
基金the National Natural Science Foundation of China(Grant No.71904116)the Fund from the Shanghai Municipal Commission of Science and Technology,China(Grant Nos.19DZ1209600 and 18DZ1201500)。
文摘Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much information a pedestrian can perceive,thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit.Besides,the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed.By integrating game theory into a cellular automata simulation framework,the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper.A systematic analysis of the key factors influencing pedestrian evacuation is conducted,including visual radius and choice firmness of a pedestrian,initial crowd distribution of the room,exit layout as well as exit width.It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering,which is adverse to evacuation.The longer the pedestrian's visual radius,the earlier the pedestrian can determine his/her final selection of the exit.Compared with the scenario where the pedestrians are randomly distributed,pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits.Furthermore,the exit layout and exit width also have a certain influence on pedestrian evacuation process.The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.
基金Supported by the National Basic Research Program of China under Grant No 2014CB340102
文摘To overcome the shortcomings of the traditional passive ranging technology based on image, such as poor ranging accuracy, low reliability and complex system, a new visual passive ranging method based on re-entrant coaxial optical path is presented. The target image is obtained using double cameras with coaxial optical path. Since there is imaging optical path difference between the cameras, the images are different. In comparison of the image differences, the target range could be reversed. The principle of the ranging method and the ranging model are described. The relationship among parameters in the ranging process is analyzed quantitatively. Meanwhile,the system composition and technical realization scheme are also presented. Also, the principle of the method is verified by the equivalent experiment. The experimental results show that the design scheme is correct and feasible with good robustness. Generally, the ranging error is less than 10% with good convergence. The optical path is designed in a re-entrant mode to reduce the volume and weight of the system. Through the coaxial design,the visual passive range of the targets with any posture can be obtained in real time. The system can be widely used in electro-optical countermeasure and concealed photoelectric detection.
文摘为提高移动机器人的跟随精度,对深度相机(RGB-D相机)测距进行研究,提出一种基于MRSD(Mask R-CNN and S2R-DepthNet)的移动机器人跟随系统。引入实例分割算法(Mask R-CNN)获取行人的前景掩膜;以掩膜为指导从深度图像中获取准确的行人区域深度像素,引入深度估计算法(S2R-DepthNet)从彩色图像中推理深度图像以替换深度传感器引起的无效深度像素,提高测距的精度;建立基于Sage-Husa自适应滤波(SHAKF)的测距模型,提高量测信息异常情况下的测距鲁棒性,实现稳定跟随。实验结果表明,该方法能以设定距离准确跟随前方行人。
