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In this paper, we propose a generic and unified content framework for cyber-physical Web, namely the Web incorporating physical objects without tag-based identifiers. The most important contribution of our framework is a novel cyber-physical-web page mechanism allowing for organizing a collection of related physical objects. We design a new lightweight XML-based markup language to describe real world objects, like HTML does digital objects in cyber world. In addition, our framework addresses a number of key issues in the development of cyber-physical Web. To improve the accuracy and efficiency of physical object identification, a sophisticated representation of physical objects is supported in our framework. Furthermore, a hybrid localization method is implemented to provide seamless positioning during the navigation of cyber-physical Web from outdoor space to indoor environment or vice versa. We also develop a cyber-physical Web browser prototype on the Android platform.

The vehicle position obtained from GPS and dead reckoning is wildly applied to car navigation systems. However, the estimated position has an undesirable error due to the unknown GPS noise. To solve this problem, previous papers presented a method called "map-matching" to correct the position error. In this paper, we proposes a fuzzy ranking map matching algorithm based on measure factor. Comparing with other four algorithms, our algorithm improves in strategies of the error region determination, the road grid index and auto-adapted fuzzy sorting. To be specific, the error rectangle is firstly replaced by the error ellipse to reduce geometrical operation. Secondly, the grid index is adopted to accelerate the speed of filtering candidate road. At last, the relativity function and fuzzy sorting method help to sort the membership degree and to decide the matching road section. For the experiments, we implement a vehicle navigation system of five kinds of vehicle running status to testify the robustness and efficiency of this algorithm. The result shows that 96.7% of the GPS points are matched. In comparison with other algorithms, this algorithm had highest accuracy, which is of importance for vehicle navigation.Index Terms-fuzzy set, measure fuzzy sorting, map matching, vehicle navigation system I.