An Individualized Travel Information System for Optimizing Mode and Route Choice behavior of Commuters

Urban sprawl and the increasing mobility demand cause serious problems for the transport systems of urban areas, in particular during peak hours. Accidents or roadwork sites worsen the situation for transport users. New technical developments in the field of satellite based localization systems interacting with intermodal and interoperable online recognition of the actual traffic situation make it possible to transmit customized information for transport users who wish to optimize their mobility behavior. On behalf of the Austrian Federal Ministry for Transport, Innovation and Technology, the research project PROVET focused on the basic conditions for an individualized transport information system (ITIS). Based on the user´s mobility profile and with the help of GPS data, ITIS should be able to determine the most likely mode, route, and destination of a transport user in real-time. By comparing this information with the actual traffic situation, possible delays on the predicted route can be identified and better (intermodal) alternatives can be suggested during a trip or even prior to the beginning of the trip. PROVET mainly focused on the technical feasibility of collecting mobility data to predict the mode and the route but also on the requirements users might have in regard to the system. Based on a test sample, algorithms were developed by using logistic regressions which achieved a detection rate of about 80%. In order to identify alternatives which offered maximum benefit for the user a discrete choice model with known class approach was calibrated, taking variables such as travel time, travel costs, gender specific aspects, or basic requirements for certain modes into account. It showed that the mode as well as the route normally used for the daily trip to work has an essential impact; particularly car commuters consider using their car as a high basic benefit.