Mobile information services will play an important role in our future work and private life. Enabling mobility in urban and populous areas needs innovative tools and novel techniques for individual traffic planning. However, though there already are navigation systems featuring route planning, their usability is often difficult, because neither current information nor personal user preferences are incorporated. We present a prototype of a traffic information system offering advanced personalized route planning, including added services like traffic jam alerting by means of SMS. The fast changing nature of such data requires to gather it from on-line Internet sources. Given current bandwidth limitations an asynchronous update strategy of a central service database prepares the ground to meet real-time requirements though providing up-to-date information. The top results of a personalized route planning query can be efficiently computed by our SR-Combine algorithm in less than 3 seconds as practical case studies show. XSLT technology automatically converts these results for the delivery to various mobile devices. In summary we give evidence that by intelligently joining latest technologies for preference modeling and preference query evaluation advanced personalized mobile traffic information systems are feasible today.