For having better and up to date traffic information access, spatio-temporal GIS for transportation (TGIS-T) needs to interact with the intelligent transport systems (ITS). Advanced traffic management systems (ATMS) is one of the components of the ITS and predicts traffic congestion and provides real time traffic information and optimal control strategies for freeways and arterials. ATMS needs automatic acquisition of traffic information such as traffic volume using different detectors. In fact, the ideal condition for ATMS is the one in which all urban intersections are equipped with these detectors, however, it would not be possible in short time. So, the urban intersection degree of importance recognition in order to consider the priority as well as planning for detectors installation is one of the main traffic control designers' challenges. In this paper, an approach has been proposed and implemented to measure each intersection degree of importance, considering the impact of other network intersections using GIS capabilities, dynamic traffic modeling and space syntax theory. Tests of each intersection degree of importance for a part of North-West of Tehran urban traffic network are conducted and the results verified the efficiency of the proposed method and support our strategy.

TGIS-T, ATMS, Space Syntax theory, Network analysis