In recent years, with the vigorous development of intelligent transportation systems, traffic control and traffic flow guidance have become popular issue of intelligent transportation systems (ITS). The key issue to achieve traffic control guidance is to realize real-time and accurate short-term traffic flow forecasting. And the accuracy and real-time of prediction directly impact traffic control and induced effect. Achieving an accurate prediction of urban road short-term traffic flow is the key of urban road traffic control and traffic guidance. Since the single prediction method for the current is of low precision, we proposed wavelet and support vector machine (SVM) method to predict new fusion; in order to avoid falling into local optimal problem in the process while learning SVM knowledge, we use the particle swarm optimization (PSO) to optimize the key parameters of SVM and in order to improve the prediction accuracy of short-term traffic flow.
Abstract. With the rapid development of economy and society, the city scale continues to expand while transportation is under great stress. Constructing the intelligent transportation system is an effective solution to improve the level of transportation management and decision support. Against the background of the applications of ITS, the paper investigates the construction processing and conversion based on OSM road-net data. It mainly explores the construction process, reconfiguration and fusion of OSM data which helps making the road}et data independent on the application system under the background of huge amounts of city calculations and realizing the aim of standardization in road-net data semantic. Additionally we still study several problems that probably occur during the construction and reconfiguration process of road-net data in order to avoid unreasonable data construction and to satisfy the demands of intelligent city administration for the reliability and stability of the basic data.
Abstract. With the rapid development of economy and society, Intelligent Transport Systems also known as the road traffic information communication system, based on systems engineering, electronics, communications, information, and other high-tech, and have penetrated into the new transportation system of aviation, shipping, rail transport sector. In this paper, there is the basic organizational framework for intelligent transportation, intelligent transportation network proposed model and its data storage structure, and the important influence on optimal path trajectory intelligent transportation planning. This paper analyze intersection road network in the distribution based on computer. Establish ITS can improve after the road network line capacity and service levels, improve environmental quality and improve energy efficiency. There are introduction and overview of the basic concepts of domestic and international development, and proposed disciplinary system model of intelligent transportation systems, and network services model hierarchical model, and a brief analysis a model of meaning. Finally, the system standardization issues and model of the role of standardization briefly introduced.
For existing path algorithms cannot achieve more continuous search, we propose the ASSA algorithms to let the travellers access to multiple points of interest in a trip. The ASSA algorithm has optimized the network structure, greatly reducing the amount of data access, and through temporal reasoning based on point of interest associated with regional to get the best travel route. The city POI data are classified based on the information and designed more than a point of interest rules under the access mechanism and its experimental verification. The results showed that: ASSA algorithm can improve computing performance by more than 16% and to avoid the emergence of non-optimal path compared to NS nearest algorithm and it can effectively meet the different points of interest rules under the access needs of travellers.
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