The performances of a well-known GHR car-following model was investigated by using numerical simulations in describing the acceleration and deceleration process induced by the motion of a leading car. It is shown that...
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The performances of a well-known GHR car-following model was investigated by using numerical simulations in describing the acceleration and deceleration process induced by the motion of a leading car. It is shown that in GHR model vehicle is allowed to run arbitrarily close together if their speed are identical,and it waves aside even though the separation is larger than its desired distance. Based on these investigations, a modified GHR model which features a new nonlinear term which attempts to adjust the inter-vehicle spacing to a certain desired value was proposed accordingly to overcome these deficiencies. In addition, the analysis of the additive nonlinear term and steady-state flow of the new model were studied to prove its rationality.
The performances of a well-known GHR car-following model was investigated by using numerical simulations in describing the acceleration and deceleration process induced by the motion of a leading car. It is shown that...
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The performances of a well-known GHR car-following model was investigated by using numerical simulations in describing the acceleration and deceleration process induced by the motion of a leading car. It is shown that in GHR model vehicle is allowed to run arbitrarily close together if their speed are identical , and it waves aside even though the separation is larger than its desired distance. Based on these investigations, a modified GHR model which features a new nonlinear term which attempts to adjust the inter-vehicle spacing to a certain desired value was proposed accordingly to overcome these deficiencies. In addition, the analysis of the additive nonlinear term and steady-state flow of the new model were studied to prove its rationality.
By introducing the velocity difference between the preceding car and the car before the preceding one into the optimal velocity model (OVM), we present an extended dynamical model which takes into account the next-nea...
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By introducing the velocity difference between the preceding car and the car before the preceding one into the optimal velocity model (OVM), we present an extended dynamical model which takes into account the next-nearest-neighbor interaction. The stability condition of this model is derived by considering a small perturbation around the uniform flow solution with finding that traffic congestion is suppressed efficiently by incorporating the effect of new consideration. Then we investigate the property of the model using numerical methods. The results indicate that the next-nearest-neighbor interaction has important impacts on the coexisting flow, the relation between flow and density, and the propagation speed of small disturbance (PSSD). In addition, we have a try to further enhance the stability of traffic flow by introducing the relative velocity of an arbitrary number of cars in front, but the analysis of linear stability shows it is poor for our purpose
In this paper descriptive visual features based on integral invariants are proposed to solve the global localization of indoor mobile robots. These descriptive features are locally extracted by applying a set of non-l...
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ISBN:
(纸本)3540302913
In this paper descriptive visual features based on integral invariants are proposed to solve the global localization of indoor mobile robots. These descriptive features are locally extracted by applying a set of non-linear kernel functions around a set ofinterest points in the image. To investigate the approach thoroughly, we use a set of images taken by re-assigning the robot position many times near a set of reference locations. Also, the presence of illumination variations is encountered many times inthe images. Compared to a well-known approach, our approach has better localization rate with moderate computational overhead.
Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the l...
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Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the localization problem. In this paper, we assume that each node in a WSN has the capability of distance measurement and present a location computation technique called linear intersection for node localization. We also propose an applied localization model using linear intersection and do some concerned experiments to estimate the location computation algorithm.
DSP/FPGA-based parallel architecture oriented to real-time imageprocessing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnecti...
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In image database retrieval there are many classical similarity measures that can be used to find the target image, these measures are mostly belong to geometry model from the point of view of the data model, while li...
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In image database retrieval there are many classical similarity measures that can be used to find the target image, these measures are mostly belong to geometry model from the point of view of the data model, while little attention has been devoted to the studies on methods based on probability density distribution. In this paper we experimental investigate some probabilistic similarity measures, present two methods for design of the similarity function of two mixture Gaussian distributions, on the basis of the nearest neighbor rule and K nearest neighbor rule respectively. An experimental study was conducted to examine and evaluate the measures for application to image databases, and the experiment results show that the methods based on K nearest neighbor rule achieve better performance.
Using real world images, two hierarchical graph-based segmentation methods are evaluated with respect to segmentations produced by humans. Global and local consistency measures do not show big differences between the ...
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Using real world images, two hierarchical graph-based segmentation methods are evaluated with respect to segmentations produced by humans. Global and local consistency measures do not show big differences between the two representative methods although human visual inspection of the results show advantages for one method. To a certain extent this subjective impression is captured by the new criteria of 'region size variation'
Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexin...
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Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalable, and well suited for VLSI implementation.
The purpose of image fusion is to combine information from several different source images to one image, which becomes reliable and much easier to be comprehended by people. Based on analyzing the relations of average...
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The purpose of image fusion is to combine information from several different source images to one image, which becomes reliable and much easier to be comprehended by people. Based on analyzing the relations of average and standard deviation of the two or more source images, a new strategy to improve image fusion effect and a new evaluation measure named RAS (the ratio between average and standard deviation) are proposed in this paper. We apply wavelet transform to decompose an image into low-frequency sub-image and high-frequency sub-images and apply different fusion rules respectively to low-frequency sub-image and high-frequency sub-images. According to subjective evaluation and objective criteria, such as entropy, root mean square error (RMSE), peak-to-peak signal-to-noise ratio (PSNR),RAS, the proposed strategy is very effective and universal to some extent for fusing a class of images whose average and standard deviation are approximately equal respectively through extensive experiments.
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