Research for Improvement of Traffic Safety
Meta-platform for Traffic Information

The BMVBS (Bundesministerium für Verkehr, Bau und Stadtentwicklung - Federal Ministry for Traffic, Building and Urban Development) considers setting up a meta-platform via which access to all available traffic and travel relevant information should be accomplished - for road traffic as well as for public transport. This activity - belonging to the high-tech initiative of the BMVBS - not only aims at an increase in operational efficiency and an improved set of commercial end-user services for motorists, but is also expected to improve traffic safety.

The main target audience of this platform are expected to be public and private sector service providers, who will directly benefit from being able to offer various services on the basis of these data and will thus contribute their share to an intelligent use of the roads. But it is also public authorities that will benefit from using the data offered by the platform for traffic management.

As a first stage of this project the BMVBS has instructed several studies to get an overview on information and information channels already available today, as well as an analysis of the technical framework conditions for standardised data referencing, quality assurance and data distribution. In this context the Heusch/Boesefeldt GmbH - together with its partner GEVAS software GmbH - was tasked with an analysis of "technical framework requirements for the integration of traffic data", mainly focussing on available data exchange interfaces and technologies.

With regard to the survey concerning "detection procedures within road traffic", Heusch/Boesefeldt and GEVAS software are supported by PTV AG. Within the frame of this project, state of the art in traffic monitoring technology is assessed and areas without or with inadequate traffic monitoring are to be identified. Based on the results of this survey, qualitative recommendations are to be developed concerning data aggregation as well as the integration of additional potential sources of data.