Mobility Data Analysis and Evaluation

Efficient mobility management requires sufficient reliable information on planning, technical and operational data, as well as the ability to interpret their meaning. A comprehensive understanding of the systems is crucial for the development of effective mobility solutions. In this context, we identify the requirements and objectives of the various stakeholders in the first step. We then analyze urban mobility patterns and issues to identify relevant challenges.

 

Our expertise includes:

 

  • Identifying requirements and objectives
  • Analyzing urban transportation patterns and issues
  • Evaluating data quality
  • Gathering and correcting information
  • Creating system models and scenarios
  • Evaluating the economic viability, efficiency and safety of mobility solutions
  • Stakeholder and requirements management

Selected Projects

STREAM – Trustworthy Data from C-ITS Information

The aim of the German-Czech cooperation project is to establish the trustworthiness of information by adapting, developing and implementing intelligent algorithms for detecting anomalies within the data. To this end, an anomaly analyzer is provided that evaluates lane-specific measurement of the traffic flow, the description of scenarios and the perception of movements.

 

Data4PoM – Homogeneous Data for the Digital Provision of Travel Chain Information

The aim of the Data4PoM project is to develop a highly innovative interface that can be used to combine and access digital stop-specific information – industrywide. To this end, algorithms are provided for the detection and automated cleansing of incorrect data.

 

Traffic Monitoring Dresden – Live Camera System for an Integrated Traffic Management

The recognition and evaluation of live camera data is an essential basis for an efficient real-time control and disposition of mobility. The operation of the city's traffic camera system by Fraunhofer IVI has been one of the most important sources of information for urban mobility management since the mid-2000s.