Abnormal driving behaviour is one of the leading cause of terrible traffic accidents endangering human life. Therefore, study on driving behaviour surveillance has become essential to traffic security and public manag...
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Abnormal driving behaviour is one of the leading cause of terrible traffic accidents endangering human life. Therefore, study on driving behaviour surveillance has become essential to traffic security and public management. In this paper, we conduct this promising research and employ a two stream CNN framework for video-based driving behaviour recognition, in which spatial stream CNN captures appearance information from still frames, whilst temporal stream CNN captures motion information with pre-computed optical flow displacement between a few adjacent video frames. We investigate different spatial-temporal fusion strategies to combine the intra frame static clues and inter frame dynamic clues for final behaviour recognition. So as to validate the effectiveness of the designed spatial-temporal deep learning based model, we create a simulated driving behaviour dataset, containing 1237 videos with 6 different driving behavior for recognition. Experiment result shows that our proposed method obtains noticeable performance improvements compared to the existing methods.
This paper focuses on the problem of multi-dimensional Taylor network (MTN)-based adaptive tracking control for a class of nonlinear systems with input constraints. As preliminaries, the saturation is first presented ...
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This paper focuses on the problem of multi-dimensional Taylor network (MTN)-based adaptive tracking control for a class of nonlinear systems with input constraints. As preliminaries, the saturation is first presented by a smooth function, and then a novel MTN-backstepping-based adaptive control method is designed on the basis of the Lyapunov stability theory. It is shown that the proposed control method can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to an arbitrarily small neighborhood around the origin. Finally, one example is given to illustrate the effectiveness of the proposed design approach.
This paper studies the design of a distributed sensor scheduling policy for a sensor network, in which each dynamical target can only be measured by partial sensors due to the restriction of sensor resources while eac...
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This paper studies the design of a distributed sensor scheduling policy for a sensor network, in which each dynamical target can only be measured by partial sensors due to the restriction of sensor resources while each sensor requires to monitor all targets. Consensus Kalman filtering algorithm and stochastic scheduling strategy are applied. Firstly, a necessary condition of the observation probabilities of the targets, which can guarantee the boundedness of the expected covariance of the network, is provided. Secondly, the marginal utility of the expected covariance with respect to the observation probability is proved. Then, an algorithm is proposed to compute the optimal probabilities, which requires less complex calculations. Numerical simulations are conducted to demonstrate the performance of the proposed algorithms.
Optimal feedback design of dynamical systems is a significant topic in automatic control community and information *** for nonlinear systems,optimal control design always leads to coping with the nonlinear Hamilton-Ja...
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Optimal feedback design of dynamical systems is a significant topic in automatic control community and information *** for nonlinear systems,optimal control design always leads to coping with the nonlinear Hamilton-Jacobi-Bellman ***,it is intractable to acquire the analytic solution of the nonlinear Hamilton-JacobiBellman equation for general nonlinear systems.
In order to enhance the stable operation of the multi-energy complementary microgrid for wind, solar, and diesel storage, reduce operating costs, and solve the problems of large randomness, low accuracy, and slow conv...
In order to enhance the stable operation of the multi-energy complementary microgrid for wind, solar, and diesel storage, reduce operating costs, and solve the problems of large randomness, low accuracy, and slow convergence of traditional microgrid optimization multi-objective decision-making, a differential evolution based on the entropy weight method to determine the weight is proposed. Firstly, we establish a microgrid integrated energy model from the perspectives of system operation stability, economy and environmental protection; combined with the Pareto optimal solution set, multi-objectives are weighted according to the entropy weight method, and the multi-objective optimization problem is transformed into single-objective optimization The problem is to avoid artificial setting of weight factors; the calculation example shows that this method is more economical and reasonable in optimization results, and provides an economic, reliable and environmentally friendly microgrid configuration strategy for users to increase power capacity.
In order to adapt to the complex disaster environment, this paper considers the system design of hexapod search and rescue robot. Such hexapod robot is suitable to different kinds of roads and obstacle, which can avoi...
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The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectiona...
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The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectional two-lane model. The dynamic characteristics of the model with periodic boundary are investigated by Monte Carlo simulation, simple mean field, and cluster mean field methods, respectively. By simulations, phase separations are observed in the system with some values of model parameters. When the phase separation does not occur, cluster mean field results are in good agreement with simulation results. According to the cluster mean field analysis and simulations, a conjecture about the condition that the phase separation happens is proposed. Based on the conjecture, the phase boundary distinguishing phase separation state and homogeneous state is determined, and a corresponding phase diagram is drawn. The conjecture is validated through observing directly the spatiotemporal diagram and investigating the coarsening process of the system by simulation, and a possible mechanism causing the phase separation is also discussed. These outcomes maybe contribute to understand deeply transport systems including the congestion and efficiency of the transport, and enrich explorations of nonequilibrium state systems.
This paper focuses on the problem of multi-dimensional Taylor network(MTN)-based adaptive tracking control for a class of nonlinear systems with input *** preliminaries,the saturation is first presented by a smooth fu...
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This paper focuses on the problem of multi-dimensional Taylor network(MTN)-based adaptive tracking control for a class of nonlinear systems with input *** preliminaries,the saturation is first presented by a smooth function,and then a novel MTN-backstepping-based adaptive control method is designed on the basis of the Lyapunov stability *** is shown that the proposed control method can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to an arbitrarily small neighborhood around the ***,one example is given to illustrate the effectiveness of the proposed design approach.
In this paper, we present the design of the multi-dimensional Taylor network(MTN) optimal controller in the flight control of cruise missile. The MTN optimal control, which combines the classical architecture of feedb...
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In this paper, we present the design of the multi-dimensional Taylor network(MTN) optimal controller in the flight control of cruise missile. The MTN optimal control, which combines the classical architecture of feedback control system and the new controller structure, it is not only suitable for the analysis of the stability of the closed-loop system, but also for the control of nonlinear systems with mechanism known or unknown models. Firstly, this paper will briefly introduce the theoretical basis of the MTN optimal control. Secondly, the characteristics of the missile mathematical model and the theory of missile control will be explained, accompanied with the design of controller. Finally, the feasibility of the method is validated through numerical simulation of the PID controller, PIDNN controller and the MTN optimal controller. The results show that the MTN optimal controller has the best control effect of them.
The colored traveling salesman problem(CTSP) is a generalization of the well-known multiple traveling salesman problem(MTSP). In CTSP, each city has one to multiple colors, allowing a salesman in the same color to vis...
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ISBN:
(纸本)9781538629185
The colored traveling salesman problem(CTSP) is a generalization of the well-known multiple traveling salesman problem(MTSP). In CTSP, each city has one to multiple colors, allowing a salesman in the same color to visit exactly once. This work presents a dynamic CTSP(DCTSP) in which the weights of edges among the cities change over time. To solve the DCTSP, we propose a variable neighborhood search(VNS) algorithm with a direct-route encoding and random initialization. The VNS is initialized by greedy operations at two stages and an appropriate population immigrant scheme is used in it to perform the population search in the dynamic environment. Extensive experiments are conducted to test the effectiveness of the greedy initialization and the immigrant scheme with the best population. The results show that the enhanced VNS can track the environment changes of DCTSP more rapidly and effectively.
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