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[IEEE 2019 21st International Middle East Power Systems Conference (MEPCON) - Cairo, Egypt (2019.12.17-2019.12.19)] 2019 21st International Middle East Power Systems Conference (MEPCON) - Performance of a Single-Stage Buck-Boost Inverter Fed from a Photovoltaic Source Under Different Meteorological Conditions
摘要： Autonomous vehicle traf?c information systems are an important research direction for next-generation traf?c information systems. Existing centralized traf?c information systems involve a large initial investment and high operating costs. Furthermore, they suffer from the following problems: the need to communicate large amounts of data, requiring a longer time for road network coverage, unsteady transmission, and the need for an automatic generation and update method for road network congestion information in a large-scale urban road network. To overcome these problems, this paper proposes an intelligent vehicular traf?c information system (IVTIS) based on a vehicular ad hoc network (VANET). This system employs a local road network and rapid dissemination model (IVTIS-LNFRN) of congestion information based on link nodes for a large-scale urban road network, and it constructs the corresponding system models. We then use traf?c simulation software to evaluate the feasibility of the IVTIS. In particular, we investigate the collection, diffusion, and dissemination of congestion information and the automatic generation and update effect of road network congestion information. Furthermore, we analyze the dissemination effect of different traf?c in?ow volumes, information packet loss rates, and different rates of IVTIS vehicles. The simulation results show that the proposed system has good autonomy and overall performance in terms of the real-time collection and rapid dissemination of congestion information in a large-scale urban road network.
关键词： intelligent transportation system (ITS),Ad hoc,traf?c information systems,traf?c information,intelligent vehicle systems & telematics
更新于2025-09-19 17:13:59
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Flexible Iridium Oxide based pH sensor Integrated with Inductively Coupled Wireless Transmission System for Wearable Applications
摘要： Autonomous vehicle traffic information systems are an important research direction for next-generation traffic information systems. Existing centralized traffic information systems involve a large initial investment and high operating costs. Furthermore, they suffer from the following problems: the need to communicate large amounts of data, requiring a longer time for road network coverage, unsteady transmission, and the need for an automatic generation and update method for road network congestion information in a large-scale urban road network. To overcome these problems, this paper proposes an intelligent vehicular traffic information system (IVTIS) based on a vehicular ad hoc network (VANET). This system employs a local road network and rapid dissemination model (IVTIS-LNFRN) of congestion information based on link nodes for a large-scale urban road network, and it constructs the corresponding system models. We then use traffic simulation software to evaluate the feasibility of the IVTIS. In particular, we investigate the collection, diffusion, and dissemination of congestion information and the automatic generation and update effect of road network congestion information. Furthermore, we analyze the dissemination effect of different traffic inflow volumes, information packet loss rates, and different rates of IVTIS vehicles. The simulation results show that the proposed system has good autonomy and overall performance in terms of the real-time collection and rapid dissemination of congestion information in a large-scale urban road network.
关键词： traffic information,Ad hoc,intelligent vehicle systems & telematics,intelligent transportation system (ITS),traffic information systems
更新于2025-09-19 17:13:59
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Pixels and 3-D Points Alignment Method for the Fusion of Camera and LiDAR Data
摘要： The fusion of light detection and ranging (LiDAR) and camera data is a promising approach to improve the environmental perception and recognition for intelligent vehicles because of the combination of depth and color information. One of the dif?culties in achieving the fusion is the accurate alignment of the 3-D points with the image pixels. Current methods of data alignment involve the steps of estimating the camera intrinsic parameters and developing a transformation matrix between the camera and LiDAR frame. The drawback of these methods is the accumulation of errors during the calculation of the camera intrinsic parameters and the transformation matrix. In order to improve the data alignment accuracy, we propose a novel algorithm that directly calculates the alignment between the 3-D points and the pixels without the need for camera parameters and calibration of the coordinate transformation matrix. We call the proposed method the pixel and 3-D point alignment (PPA) method. The alignment procedure is achieved by using the extracted corresponding points. First, we calculate a linear alignment matrix without considering the image distortion; and second, we optimize the parameters using the maximum likelihood estimation to consider the camera distortion. Simulation and experimental results indicate that the PPA method is able to align the 3-D points in LiDAR frame with the pixels in image frame with higher accuracy and increased robustness against noise in calibration process than comparable state-of-the-art methods.
关键词： intelligent vehicle,sensor fusion.,calibration,camera and light detection and ranging (LiDAR),Autonomous driving
更新于2025-09-04 15:30:14