Underground urban expressways are a possibility for solving many existing transportation-related problems, such as traffic congestion in high density areas and the division of neighborhoods due to elevated roadways. H...Underground urban expressways are a possibility for solving many existing transportation-related problems, such as traffic congestion in high density areas and the division of neighborhoods due to elevated roadways. However, they may also pose high risks regarding traffic safety. Therefore, it is important for a pre-analysis of traffic safety to be made. This paper describes recent efforts to develop a driving simulation system, MOVIC-T4, for traffic safety analysis of underground urban expressways. In order to develop a small portable simulator, a small-sized motion-base with two-degrees-of-freedom is used to duplicate acceleration cueing together with a head-mounted-display （HMD） for the visual system. An overview of this system is given and the reliability of driving data obtained from the experiments using MOVIC-T4 is discussed through a validation study using field driving data. The results of validation indicate that the perceived speed distance headway, and physiological data in the simulator show the almost same trend as that in the real world, but larger decelerations tend to be produced in the simulator.展开更多
In this paper, a mobile assistance-system is described which supports users in performing manual working tasks in the context of assembling complex products. The assistance system contains a head-worn display for the ...In this paper, a mobile assistance-system is described which supports users in performing manual working tasks in the context of assembling complex products. The assistance system contains a head-worn display for the visualization of information relevant for the workflow as well as a video camera to acquire the scene. This paper is focused on the interaction of the user with this system and describes work in progress and initial results from an industrial application scenario. We present image-based methods for robust recognition of static and dynamic hand gestures in realtime. These methods are used for an intuitive interaction with the assistance-system. The segmentation of the hand based on color information builds the basis of feature extraction for static and dynamic gestures. For the static gestures, the activation of particular sensitive regions in the camera image by the user’s hand is used for interaction. An HMM classifier is used to extract dynamic gestures depending on motion parameters determined based on the optical flow in the camera image.展开更多
基金Supported by Ministry of Land, Infrastructure and Transport, Japan Society of the Promotion of Science and Mitsui Sumitomo Insurance Welfare Foundation
文摘Underground urban expressways are a possibility for solving many existing transportation-related problems, such as traffic congestion in high density areas and the division of neighborhoods due to elevated roadways. However, they may also pose high risks regarding traffic safety. Therefore, it is important for a pre-analysis of traffic safety to be made. This paper describes recent efforts to develop a driving simulation system, MOVIC-T4, for traffic safety analysis of underground urban expressways. In order to develop a small portable simulator, a small-sized motion-base with two-degrees-of-freedom is used to duplicate acceleration cueing together with a head-mounted-display （HMD） for the visual system. An overview of this system is given and the reliability of driving data obtained from the experiments using MOVIC-T4 is discussed through a validation study using field driving data. The results of validation indicate that the perceived speed distance headway, and physiological data in the simulator show the almost same trend as that in the real world, but larger decelerations tend to be produced in the simulator.
文摘In this paper, a mobile assistance-system is described which supports users in performing manual working tasks in the context of assembling complex products. The assistance system contains a head-worn display for the visualization of information relevant for the workflow as well as a video camera to acquire the scene. This paper is focused on the interaction of the user with this system and describes work in progress and initial results from an industrial application scenario. We present image-based methods for robust recognition of static and dynamic hand gestures in realtime. These methods are used for an intuitive interaction with the assistance-system. The segmentation of the hand based on color information builds the basis of feature extraction for static and dynamic gestures. For the static gestures, the activation of particular sensitive regions in the camera image by the user’s hand is used for interaction. An HMM classifier is used to extract dynamic gestures depending on motion parameters determined based on the optical flow in the camera image.
