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The paper describes a video detection method for two-wheeled vehicles appearing especially in the small-medium cities. The multi Gaussian mixture model is used to build the background and foreground. The single threshold method is efficiently used in shadow removal. Then Gaussian smooth filter processing and morphological image processing are used to filter out the noises in the foreground. The target...
The thesis mainly analyzed deeply the research on the design of anti-collision warning system, according to the latest research focus in domestic and foreign countries, put forward a comprehensive and safety anti-collision warning system, which includes rear-end collision system and side collision warning system. According to the newest research results and actual needs of system, this paper had established...
The paper built an urban road network model through analysis of urban traffic flow characteristics. The minimizing total travel time of vehicle in the road network was taken as control target, and the dynamic path model was built. The ant colony algorithm was used to find out the optimum path from start point to destination by collecting the real-time traffic information of the road network. Then...
Traffic assignment is one of the primary steps in urban transportation planning process and the theoretical basis for program design in modern transportation planning. This paper based on the network users of the travel time at least as the goal, and took the Matlab simulation software as operation platform, applied Genetic algorithm to the traffic equilibrium distribution model, and then realized...
Study optimization of traffic flow accuracy detection problem. For moving targets' speed and external environment are the main factors of influencing traffic flow detection. It is easy to cause undetection and misjudgment of traffic flow detection. In order to overcome traditional frame differencing method and background differencing's inadequation when using singlely, an intelligent traffic detection...
This paper introduces the current research actuality. To the question of traditional BP neural network's low convergence rate and easily get into minimum, low recognition rate, low efficiency and such problems, so we bring the chaos thoughts to the particle swarm optimization algorithm. Considering the chaos researching with strong local search ability and strong ability of meticulous search, we use...
According to the problems of traffic flow on road, traffic status evaluation parameters and road running state, and because of relationship among road traffic flow parameters, the paper evaluates road traffic condition with AHP approach. First building evaluation levels of hierarchical structure, then giving all levels calculation formula, thus determining various index weights, next working out evaluation...
According to routine public transit network evaluation problem of the city, the data envelopment analysis is used to study it. On the basis of establishing a hierarchical structure to the evaluation index, the city public transit network evaluation model using virtual decision unit of data envelopment analysis method is established and verified with examples. Through the case analysis, the data envelopment...
Analysis and forecasting for short-term traffic flow have become a critical problem in intelligent transportation system (ITS). This paper introduces the basic theory and features of General Regression Neural Network (GRNN) and its advantages. A forecasting model based on GRNN is built for short-term traffic flow time series at urban road section in 10-minutes interval. In order to get ideal forecasting...
This paper focuses on traffic flow forecasting which is an essential component in traffic control or route guidance system. A combination forecasting model called GM-GRNN based on GM(1, 1) and GRNN is built for short-term traffic flow time series. The basic theory and features of General Regression Neural Network (GRNN) and its advantages are introduced. The weight of combination model is determined...
This paper proposes a transit-priority signal control method for urban intersection using fuzzy neural techniques. In order to reduce the delay of buses and passengers, a changeable-phase-order method is proposed. The phase with more passengers is preferential to be selected as the next phase by the end of current phase. The green increase time of current phase is inferred by a fuzzy controller which...
According to the traffic flow features of urban intersections, a multi-phase adaptive control algorithm is given. The structure of network and program of realizing fuzzy control based on improved multi-layer BP neural networks are obtained. Results of simulation research show that with the abilities of learning and generation, the fuzzy neural controller can cope with the fast changing of arriving...
Traditional shortest path algorithm didn't consider the condition of road network, such as no left-turn. This paper restructured the topology of network chart considering the complex traffic regulations, in order to rebuild the model of urban traffic network, and proposed a new optimal path algorithm adapted for urban traffic guidance system based on Dijkstra algorithm. At last, we used Visual Basic...
Based on the inherent characteristic of link cost function, a dynamic traffic assignment model with simple and standard structure and satisfying the flow propagation constraint is formulated for general road network. Then, for many-to-one road network, using the optimal control theory approach, the necessary and sufficient conditions for optimal assignment solution are presented and the equivalence...
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