Design of a GIS-based traffic congestion forecast information system
Traffic congestion can have different causes, amongst them predictable events like a higher amount of traffic volume due to the beginning of holidays, open air concerts, football matches, and similar events. Broadcasting congestion forecasts via traffic messages will inform road users of alternative travel routes and therefore they can anticipate, and perhaps avoid the congestion. The Austrian national public broadcaster (ORF) operates a free public Traffic Message Channel (TMC), broadcasting real-time traffic and weather information. Our study focuses on the possibility of including congestion forecasts in this TMC service. For the forecast model itself, we determine a correlation model between traffic volume, weather conditions, and number and dimension of the events. This is done by the evaluation of historical traffic census data, meteorological data, and broadcasted traffic messages. We assume that weather conditions have a high influence not only on travel speed but on traffic volume: Most outdoor events usually attract more people when the weather is pleasant. Different data types from different sources are to be included in such a system. In particular, the methods and models for specifying the geographic location of the data are very heterogeneous, including linear reference systems, WGS84-coordinates, place names, and street addresses. We specify a simple sequence of characters, derived from the URL concept of the World Wide Web, to identify the geographic location of the data. The concept and design of this “Geographic Uniform Resource Identifier” and its implementation in a GIS are revealed. The model found will be used for the development of a GIS-based congestion prediction tool both for the ORF TMC service and the integration into navigation systems and mobile devices.