Context-aware Computing And Its Applications In Intelligent Transportation

With the continuous development of the times, the hardware and software for road traffic building facilities have been gradually improved, and because of the types of transport become more and more, urban transport development faces enormous challenges, economic and social tool for people to use increased frequency of travel, also increases the range of travel, transportation, and transportation to people with to facilitate it also brings the corresponding problems, traffic jams are also highlighted apparent. The development of the ITS (Intelligent Transportation System) is supported to be more effectively to improve the utilization of transportation. Intelligent transportation systems is been used of more advanced science and technology for transportation integration process, these technologies include a number of areas, such as sensor technology, artificial intelligence, data communications technology, operations research, information technology, automatic control theory, computer technology, electronic control technology and so on. The travelers can make for their own choices by understanding the traffic environment and road conditions adequately and accurately through the real-time traffic information which intelligent transportation systems collected, and traffic management department can also make timely guidance and governance with the data collected by monitoring systems traffic in pervasive environment.The navigation in intelligent transportation system is mainly used to solve the problem that the user choice the travel path when traveling, how to choose a reasonable and efficient travel route for people has always been the primary. The optimal path selection has always been the most important part of the city traffic navigation system. Most of the shortest path uses the Dijkstra algorithm which given the weight of edge in the practical application. But there are some shortcomings by this way. Through much studies shows that:the edges in the path of the weight is not an effective Reflect the real-time road information, and travel route in the shortest time, while the weight is the key factor, it will affect the accuracy of the real-time navigation because of the static weight. In this paper, sensors collect real-time information on traffic road and Dijkstra algorithm is used to generate the edge weights, so that the navigation system can calculate the shortest path more accurately and intelligently.In this paper, the field of urban transport has been ontology modeling. The main purpose of modeling is to install the sensors on the road collecting roads, including congestion levels and road conditions; the collected data is passed to the server context modeling which Ontology has been in used. Intelligent transportation system is based on the original by adding context-aware module, the new module's main function is to increase the physical sensor through the platform to collect the relevant data required, to integrate these data and formal, making a variety of data services to upper layer Accurate, real-time, effective information and better guide the user travel, making navigation more intelligent and humane.