This paper investigates an efficiency of signal control methodology, which mainly focuses on dealing with the traffic congestion problem in those key congested links and is applicable to be implemented in a hierarchic...
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This paper investigates an efficiency of signal control methodology, which mainly focuses on dealing with the traffic congestion problem in those key congested links and is applicable to be implemented in a hierarchical control structure in large-scale heterogeneous urban traffic networks. In this methodology, an algorithm for finding the most congested path is presented firstly, and the urban traffic flow is modeled by using a simplified macroscopic modeling framework. Then the problem of network-wide signal control is formulated as a linear programming problem that aims at minimizing the number of vehicles(or densities) in congested links so as to improve the mobility of the network and mitigate the traffic congestion. For the application of this method in real time, the multi-variables optimization problem including constraints is embedded in a model-based dynamic control procedure. Finally, different traffic demand scenarios are designed and four evaluation criteria are applied to measure the performance of the proposed method in a hypothetical road network. Compared with the fixed-time control strategy, the simulation results show that it is an effective and feasible way to regulate the traffic flow and mitigate the congestion in large-scale urban networks.
A stabilized Distributed MPC for large scale system is proposed and its designation is given in this paper for improving the global performance of closed-loop system. To make the performance of closed-loop system more...
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Cutting Stock Problems (CSP) arise in many production industries where large stock sheets must be cut into smaller pieces. An irregular-shaped nesting approach for two-dimensional cutting stock problem is constructed ...
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Cutting Stock Problems (CSP) arise in many production industries where large stock sheets must be cut into smaller pieces. An irregular-shaped nesting approach for two-dimensional cutting stock problem is constructed in this research. We present a heuristic based on Particle Swarm Optimization Algorithm (PSO) for irregular-shaped two-dimensional cutting stock problem, where PSO is utilized to search optimal solution. Furthermore, the proposed approach combines a grid approximation method with Bottom-Left-Fill heuristic placement strategy to allocate irregular items. We evaluate the proposed approach using 15 revised benchmark problems available from the EURO Special Interest Group on Cutting and Packing. The performance illustrates the effectiveness and efficiency of our approach in solving irregular cutting stock problems.
Crowded scene analysis is becoming increasingly popular in computer vision field. In this paper, we propose a novel approach to analyze motion patterns by clustering the hybrid generative-discriminative feature maps u...
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ISBN:
(纸本)9781479923427
Crowded scene analysis is becoming increasingly popular in computer vision field. In this paper, we propose a novel approach to analyze motion patterns by clustering the hybrid generative-discriminative feature maps using unsupervised hierarchical clustering algorithm. The hybrid generative-discriminative feature maps are derived by posterior divergence based on the tracklets which are captured by tracking dense points with three effective rules. The feature maps effectively associate low-level features with the semantical motion patterns by exploiting the hidden information in crowded scenes. Motion pattern analyzing is implemented in a completely unsupervised way and the feature maps are clustered automatically through hierarchical clustering algorithm building on the basis of graphic model. The experiment results precisely reveal the distributions of motion patterns in current crowded videos and demonstrate the effectiveness of our approach.
作者：
Jianyu LinDepartment of Automation
Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China
The paper investigates the problem of the asymptotical stability and stabilization of uncertain large-scale fractional order interconnected *** the basis of the stability criterion of fractional order system,sufficien...
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ISBN:
(纸本)9781479900305
The paper investigates the problem of the asymptotical stability and stabilization of uncertain large-scale fractional order interconnected *** the basis of the stability criterion of fractional order system,sufficient conditions are firstly derived for the asymptotical stability of fractional order large-scale interconnected system with norm-bounded uncertainties. Then,sufficient conditions on robust stabilization of large-scale fractional order interconnected system with norm-bounded uncertainties are established based on a complex Lyapunov inequality described in the form of ***,decentralized stabilization state feedback controllers are *** example is used to illustrate the effectiveness of the proposed method.
We study an opinion formation model with the coevolution of network structures and opinions. The links formed among the agents are based on the popularity of the nodes and the similarity of their opinions, and in retu...
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ISBN:
(纸本)9789881563835
We study an opinion formation model with the coevolution of network structures and opinions. The links formed among the agents are based on the popularity of the nodes and the similarity of their opinions, and in return, opinions change in response to the network structure. We find that the pursuit of popularity accelerates the convergence, while the pursuit of similarity slows down the convergence. In addition, the whole group convergence more quickly with a larger number of neighbors. We also investigate neighbor-preserving strategies, and find that maintaining a nonzero number of neighbors could lead to faster convergence.
An intelligent wheelchair JiaoLong with multi-mode is developed for the handicapped and the *** is designed of two manipulate modes according to the user's disability and the environments for *** on the dynamic lo...
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An intelligent wheelchair JiaoLong with multi-mode is developed for the handicapped and the *** is designed of two manipulate modes according to the user's disability and the environments for *** on the dynamic localizability matrix,an improved particle filter localization algorithm is proposed in this *** results of experiments show the practicability of the system design and the effectiveness provided by the improved localization method.
This paper generalizes the concept of the depth-independent interaction matrix, developed for point and line features in our early work, to generalized image features. We derive the conditions under which the depth-in...
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In this paper, we deal with the problem of pursuing a mobile target by multiple robots in indoor environments embedded with robotic networks. The target is vigilant and its speed can be arbitrarily fast while the spee...
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In this paper, we deal with the problem of pursuing a mobile target by multiple robots in indoor environments embedded with robotic networks. The target is vigilant and its speed can be arbitrarily fast while the speeds of pursuers are limited. Our object in this paper is to design effective pursuit strategies for the robots to track and finally capture the target. By using concepts of tree decomposition from graph theory, we establish an upper bound of the pursuer number that can guarantee successful capture of the mobile target. We then propose a pursuit algorithm, namely, tree-width based graph searching (TWGS), based on the theoretical analysis. Furthermore, we demonstrate the performance of the algorithm for two indoor environments by numerical simulations, which show that TWGS is efficient and the pursuer number given by the theoretical analysis is rather tight.
作者：
Ya-Nan WangJian-Bo SuDepartment of Automation
Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China 200240 China
Considering the face image is approximate symmetry, we proposed a measurement factor to quantify the symmetrical characteristic of face images. Firstly we transform the face image into even-odd face images using parit...
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Considering the face image is approximate symmetry, we proposed a measurement factor to quantify the symmetrical characteristic of face images. Firstly we transform the face image into even-odd face images using parity decomposition method. LBP features extracted in even images to construct training sets. Then we apply Adaboost training algorithm to structure a strong classifier. Experiment proved that this method can overcome environment disturbance, and effectively improve the recognition rate.
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