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The signalized intersection system often exhibits severe nonlinear and time-varying characteristic due to the random fluctuation of traffic demand or some special event, therefore, it cannot be adequately controlled with some traditional ways. The traditional reinforcement learning was extended to the fuzzy pattern with defining the fuzzy reinforcement(More)
On account of the random fluctuation of traffic demands or some special events, the signalized intersection system often exhibits severe nonlinear and time-varying behavior and therefore cannot be adequately controlled with some conventional means. A stochastic traffic signal control scheme, based on reinforcement learning, is introduced in the traffic(More)
In evolutionary multi-objective optimization, balancing convergence and diversity remains a challenge and especially for many-objective (three or more objectives) optimization problems (MaOPs). To improve convergence and diversity for MaOPs, we propose a new approach: clustering-ranking evolutionary algorithm (crEA), where the two procedures (clustering and(More)
A prediction model for short-time traffic flow series is proposed in this paper. At first, estimation of the largest Lyapunov exponent is implemented by applying small data sets method so as to validate that chaos exists in traffic flow series. Then, through properly choosing the delay time and the embedding dimension using mutual information and false(More)
A distributed approach to Reinforcement Learning in tasks of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application, is formulated as a distributed reinforcement learning problem. The DRL approach was implemented via a multi-agent control architecture where the decision agent was assigned to each(More)
Using the idea of digital image's information sharing, a new hiding approach for multi-image fusion based on NURBS curve is presented. The approach makes use of a k-order non-uniform rational B-spline curve with weights to hide information of one image into information of n images. These hiding schemes have more fusion parameters to act as the private keys,(More)
Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter(More)
Traffic flow on roads is a non-linear, stochastic phenomenon, with complex interactions between vehicles. This paper discussed the dynamic nature of urban intersections, and presents a novel traffic flow evolution model at a time scale and of a level of detail suitable for on-line estimation, simulation and control. The intersection is considered as(More)
This paper describes a scale evaluation method using nonsubsampled contourlet transform and its application in pavement image enhancement for crack detection. Crack in some scales is much more visible than in others, so a method for scale evaluation is given, and different gains are delivered to each scale for enhancement after scale evaluation. In the(More)