QUATRA deals with the creation of tools for quality management for traffic data on freeways and in urban road environments. It has two major objectives:
The first objective is to develop procedures and software tools to measure and estimate the quality of incoming online traffic data in a freeway control centre. The incoming data, usually in a minute-to-minute interval is used for freeway control, management and information. For different control or information purposes it is often very important to know, if the underlying traffic data is correct or erroneous. In that case the type of error needs to be identified.
The second objective is to develop a comparable service for the evaluation of urban traffic data for cities and their transport authorities. This service has access to the cities’ traffic data database and calculates offline the performance measures and quality indicators on a daily basis. The results are then reported, e.g. via email, to the transport authority. The big challenge is to find and identify quality indicators for urban detectors as well as errors that corrupt the daily traffic control.
The quality management for freeways will increase the reliability of automated and manual traffic control under freeway conditions (for example guidance and speed harmonization) or the generated traffic messages which are also partly based on detector data. On urban roads it will improve for example the signal coordination mainly during peak times and will also help to reduce travel times and emissions.
The software will be developed in order to be used for a variety of different existing data collection systems and data formats. Test data of the ASFINAG (Austrian Freeway Authority) and the City of Munich will be analyzed.
Within QUATRA two comprehensive quality management tools for quality management of traffic data have been developed for the identification of erroneous data based on statistical estimations and logic based enquiries. The system can be used for analysis of different parameters such as traffic volumes, traffic densities and average vehicle speeds. Furthermore local/global/plausibility indicators have been developed that allow data evaluation and detection of inconsistencies. The erroneous data is flagged and can be analysed in order to differentiate between detector malfunctions and abnormal traffic conditions.
Based on the input from a state-of-the-art analysis relevant criteria and indicators have been defined for definition of the framework of the software tool and the development of statistical models. One tool can be used online to determine the quality of incoming traffic data for freeway control, the second tool is an offline city-service for measuring the quality of urban traffic data for signal control.
As part of the project scope additional concepts and ideas for the QUATRA system have been identified that could be integrated in future follow-up projects. This also covers data imputation for erroneous and missing values based on historical and actual information.
Both algorithms (freeway and urban) have been successfully tested with German and Austrian traffic data supplied by road operators.