Abstract.With the continuous development of data mining technology, to apply the data mining techniques to transportation sector will provide service to transportation scientifically and reasonably. In intelligent transportation, the analysis of traffic flow data is very important, how to analyze the traffic data intelligently is more difficult problem, so using a new data mining techniques to replace the traditional data analysis and interpretation methods is very necessary and meaningful, clustering algorithm is the collection of physical or abstracting objects into groups of similar objects from the multiple classes of processes. This paper describes all kinds of the data mining clustering algorithms, clustering algorithm is proposed in the method of dealing with traffic flow data, and applied to the actual traffic data processing, and finally the clustering algorithm is applied to each of highway toll station Various types of car traffic volume data analysis.
Reversible lanes constitute an important solutions for sustainable transportation, with the aim to solve the practical problem of reversible lane optimization of urban road networks constrained by adjustment time. Considering the relationship between the number of lanes and the capacity of sections, a mixed-integer bilevel programming model of reversible lane optimization constrained by adjustment time is constructed in order to minimize the total travel time of the system. The results show that the model can effectively obtain the optimal strategy for any number of reversible sections subject to adjustment time constraints. With the increase of the number of reversible sections that can be optimized within the adjustment time, the cumulative reduced system time increases monotonically and the road network optimization effect improves, but as a whole, the optimization effect of the newly added reversible sections in each stage shows a decreasing trend. When the number of reversible sections that can be optimized within the adjustment time reaches a certain number, increasing the number of reversible sections will have a limited further effect on the overall system. For the reversible lane optimization problem of urban road networks, only efficient reversible sections need to be optimized to achieve a good optimization effect.
With the progress of social economy and the rapid development of transportation industry, in the face of the rapid growth of urban road traffic data, this paper puts forward the design scheme of intelligent traffic analysis system based on Hadoop. In this paper, HBase distributed database is used to store urban road static RDF data, hive data warehouse is used to store urban road traffic data, and MapReduce programming model is used to store massive and heterogeneous urban road traffic data The urban road traffic data are analyzed, and the whole scheme is verified by the prototype system.
Based on analytical and simulation methods, this paper discusses the path choice behavior of mixed traffic flow with autonomous vehicles, advanced traveler information systems (ATIS) vehicles and ordinary vehicles, aiming to promote the development of autonomous vehicles. Firstly, a bi-level programming model of mixed traffic flow assignments constrained by link capacity is established to minimize travel time. Subsequently, the algorithm based on the incremental allocation method and method of successive averages is proposed to solve the model. Through a numerical example, the road network capacity under different modes is obtained, the impact of market penetration on travel time is analyzed, and the state and characteristics of single equilibrium flow and mixed equilibrium flow are explored. Analysis results show that the road network can be maximized based on saving travel time when all vehicles are autonomous, especially when the autonomous lane is adopted. The travel time can be shortened by increasing the market penetration of autonomous vehicles and ATIS vehicles, while the former is more effective. However, the popularization of autonomous vehicles cannot be realized in the short term; the market penetration of autonomous vehicles and ATIS vehicles can be set to 0.2 and 0.6, respectively, during the introduction period.
Intelligent transportation integrated access system can significantly improve the security of computer network systems, while trusted computing technology can effectively enhance the credibility and safety of the terminal, and then construct a trusted network connection. Based on computing technology, this thesis proposes to establish a credible integrated access network, and implement network access control on the remote access equipment, thereby enhancing the safety of the integrated access system. The results show that, through the transmission technology of credible chain proposed in this paper, and remote proof technology basing on device identity and security policies can establish a credible integrated access system, thus effectively improving the security of Beijing intelligent transportation systems.
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