The positioning accuracy of a short-haul target-locating system,the inverse-GPS(IGPS) ,was analyzed in detail. The relationship between IGPS and the positioning error was discussed. The multiplicative error minimal bo...
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The positioning accuracy of a short-haul target-locating system,the inverse-GPS(IGPS) ,was analyzed in detail. The relationship between IGPS and the positioning error was discussed. The multiplicative error minimal bound of the geometric dilution of precision (GDOP) about the four-base-station IGPS was also investigated. In order to clarify the practical implementation of IGPS,the multiplicative and additive error factors which affect the positioning accuracy and theoretical estimation of positioning accuracy were presented. By analyzing the experiments of locating a target's position in virtual three-dimensional areas,the positioning performance of IGPS was illustrated. The results show that the multiplicative and additive error factors should be eliminated in IGPS to improve the positioning accuracy.
Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important ...
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Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus, computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper, a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions.
With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the intelligent Transportation systems (ITS) research. The Cellular Aut...
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With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the intelligent Transportation systems (ITS) research. The Cellular Automata (CA) and the Multi-Agent System (MAS) modeling are two typical methods for the traffic microsimulation. However, the computing burden for the microsimulation and the optimization based on it is usually very heavy. In recent years the Graphics Processing Units (GPUs) have been applied successfully in many areas for parallel computing. Compared with the traditional CPU cluster, GPU has an obvious advantage of low cost of hardware and electricity consumption. In this paper we build an MAS model for a road network of four signalized intersections and we use a Genetic Algorithm (GA) to optimize the traffic signal timing with the objective of maximizing the number of the vehicles leaving the network in a given period of time. Both the simulation and the optimization are accelerated by GPU and a speedup by a factor of 195 is obtained. In the future we will extend the work to large scale road networks.
New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded dri...
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New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded drift is ***,a dynamic synchronization algorithm based on consensus control strategy,namely fast averaging synchronization algorithm (FASA),is presented to find the solutions to the synchronization *** FASA,each node computes the logical clock value based on its value of hardware clock and message *** goal is to synchronize all the nodes' logical clocks as closely as ***,the convergence rate of FASA is analyzed that proves it is related to the bound by a nondecreasing function of the uncertainty in message delay and network ***,FASA's convergence rate is proven by means of the robust optimal ***,several practical applications for FASA,especially the application to inverse global positioning system (IGPS) base station network are ***,numerical simulation results demonstrate the correctness and efficiency of the proposed *** FASA with traditional clock synchronization algorithms (CSAs),the convergence rate of the proposed algorithm converges faster than that of the CSAs evidently.
This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image...
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This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.
An adaptive fuzzy observer for nonlinear magnetic levitation system with uncertain friction coefficient is proposed. First, a T-S fuzzy model of the nonlinear magnetic levitation system is proposed. An observer is giv...
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An adaptive fuzzy observer for nonlinear magnetic levitation system with uncertain friction coefficient is proposed. First, a T-S fuzzy model of the nonlinear magnetic levitation system is proposed. An observer is given by LMI method and the Lyapunov method. Through adding an auxiliary variable, it relaxes the constraint of the design of observer. The proposed approach is a more relaxed condition than others. Simulation results show the effectiveness of this approach. The results show that the position of magnetic levitation system is estimated effectively with unknown friction coefficient. There is some reference value for a kind of nonlinear systems with unknown parameter.
The fault diagnosis for a class of widely used digital parallel output optical encoder were focused. After definition of the optical encoder, the main features of the optical encoder's output data were analyzed. A...
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The fault diagnosis for a class of widely used digital parallel output optical encoder were focused. After definition of the optical encoder, the main features of the optical encoder's output data were analyzed. A fault diagnosis method which did not rely on the system model where optical encoder used was proposed. The changes of optical encoder's output data were analyzed. Then, the inherent characteristics were calculated. The fuzzy logic was utilized to determine the fault type and locate the fault location. Theoretical analysis and experimental results show that this method can diagnose and isolate optical encoder fault accurately without disassembly.
A new method is proposed, through combining the algorithm of orthogonal discriminant linear local tangent space alignment (ODLLTSA) and the support vector machine (SVM), to improve the accuracy of recognizing door pla...
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A new method is proposed, through combining the algorithm of orthogonal discriminant linear local tangent space alignment (ODLLTSA) and the support vector machine (SVM), to improve the accuracy of recognizing door plate numbers. The feature of door plate characters is first extracted by the ODLLTSA and then this extracted feature is used to train the SVM classifier. Finally, the new plate characters are classified by the trained SVM. Using the algorithm, a high recognition rate can be achieved. Experimental results show that this method is effective and robust in the real applications.
A simulation system scenario design method was proposed for the space-based information simulation system supporting anti-earthquake rescue. This method is based on the conceptual models of the mission space method in...
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A simulation system scenario design method was proposed for the space-based information simulation system supporting anti-earthquake rescue. This method is based on the conceptual models of the mission space method including the formal description of simulation aim, scale, static data, dynamic data set and simulation play. A simulation scenario creator was developed to realize these functions and prove the usability of these models.
Wireless sensor networks consist of a large number of sensor nodes that have low power and limited transmission range and can be used in various scenario. The nodes can be deployed in the long and narrow region, such ...
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Wireless sensor networks consist of a large number of sensor nodes that have low power and limited transmission range and can be used in various scenario. The nodes can be deployed in the long and narrow region, such as road, bridge, tunnel and pipeline, to get some interesting information. The linear topology of these network application is different other application and have special feature, such as multi-hop, long delay, long distance and low reliability. This paper introduces the concept of linear wireless sensor networks and discusses the classification of topology and key issue of this network. The application of the linear wireless sensor network, such as road, bridge, tunnel and pipeline is presented. The research challenges are discussed at last in this paper.
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