Central to efficient highway management and navigation systems is an accurate inventory of physical road attributes and properties. Development of such an inventory has been simplified by the advent of automated data collection utilizing vehicles equipped with the capability of geographical positioning by satellite and the support of intelligent geographical systems. Experience has shown that in the urban environment, attribute capture by video and post survey processing supported the addition of 7,500 attribute items per day into an adequately referenced highway network management database. The potential information content of the data is extensive, not only to the highway manager, but to driver information system providers, and other data users, assuming adequate flexible extraction, analysis, and exploitation tools are available. These tools should enable the user to query the database both through a geographical user interface and via alphanumeric textual queries to meet differing user requirements. This paper will describe a set of proven tools developed using artificial intelligence methods for extraction and analysis of data for highway management purposes. Examples include tools for management of street lighting and signing installations, pavement condition monitoring, of the integration of these and other highway data management tools, and the future potential of configuring the data for use in traffic telematics.
