SCENIMINI - Scenario Mining in Traffic Data

SCENIMINI automatically interprets vehicle movement data and processes it in such a way that it can be easily reused in the form of a knowledge base. SCENIMINI thus provides the foundation for the development and validation of automated driving functions, for measures to improve traffic safety, and for research into the behavior of road users.

SCENIMINI (Scenario Mining in Traffic Data) is a research service provided by the German Aerospace Center (DLR) and serves as the technological link between DLR research vehicles, infrastructure-based traffic data collection, and the systematic analysis of traffic.

Traffic data, particularly trajectory data, serves as the starting point for many research projects and scientific inquiries. This data is collected via infrastructure, for example at the AIM research intersection, in the Test Bed Lower Saxony, or through mobile measurement stations. In addition, trajectory data is generated by DLR research vehicles and in simulations.

For various applications, this data - which is often heterogeneous and initially unstructured - must be fused, synchronized, and further processed. This is particularly true for real-world data, where different sensor sources, collection conditions, and data formats must be integrated.

SCENIMINI supports the automated annotation and analysis of trajectory data to extract relevant traffic scenarios. The goal is to build a scenario-based knowledge base in which trajectory data is semantically annotated. This knowledge base serves as the foundation for further analyses, including those related to the development and validation of automated driving functions, the analysis of traffic safety, and the modeling of road user behavior.

Key Features

Scenario-Based Traffic Analysis
SCENIMINI enables the systematic analysis of real and simulated traffic data. Relevant traffic situations are identified from trajectory data, annotated, and made available in a structured format as scenarios.

Data Fusion and Semantic Annotation
SCENIMINI supports the processing of heterogeneous data sources from infrastructure, mobile measurement systems, research vehicles, and simulations. The data is fused, preprocessed, and semantically enriched.

Standardized Scenario Formats
Extracted scenarios can be provided in standardized data formats, specifically ASAM OpenDRIVE® and ASAM OpenSCENARIO® XML. This allows the scenarios to be reused in simulation, analysis, and validation environments.

Open-Source
TASI: A component of SCENIMINI is TASI, an open-source Python library for managing and analyzing traffic data. TASI on GitHub:
https://github.com/DLR-TS/TASI
Datasets: SCENIMINI was used to create and process publicly available datasets https://zenodo.org/records/15754836, https://zenodo.org/records/18540070

Areas of Application

SCENIMINI supports the following areas of application, among others:

  • Development and validation of automated driving functions
  • Traffic safety analysis
  • Modeling the behavior of road users
  • Data-driven traffic and mobility research
  • Scenario extraction for simulations
  • Establishment of reusable data foundations for research projects

Projects:

SCENIMINI is being used and further developed in various research and technology transfer projects.

AutoGVZ

At Germany’s largest Freight Village, the DLR is working with project partners to test how automation can make truck operations more energy-efficient and safer. The Bremen Freight Transport Center will serve as the test site for the AUTOGVZ project, which will test automated and remotely monitored trucks over a distance of approximately three kilometers.

VRIEDRICH

Road safety plays a central role in shaping the transportation system of the future. In line with Vision Zero, the goal is to reduce accidents resulting in fatalities and serious injuries - and, ideally, to eliminate them entirely.

IMoGer

The IMoGer research project is the first to combine a public transport service and courier, express and parcel logistics (CEP logistics) with the automated, modular U-Shift vehicle concept from DLR. This holistic mobility solution for the last mile is designed to reduce traffic congestion and stands for sustainability and efficiency.

VVMethods

The testing and validation of vehicle systems plays a key role in the introduction of fully automated and autonomous driving functions. Together with project participants from industry and research, DLR is developing legally compliant, time- and cost-efficient verification and validation methods.

SYNERGIES

The SYNERGIES project envisions a future where Cooperative, Connected, and Automated Mobility (CCAM) systems seamlessly integrate into everyday life, ensuring safer, more efficient, and sustainable transportation across Europe. By establishing a dynamic, continuously evolving platform for scenario-based validation and leveraging AI-driven innovations, SYNERGIES aims to set the global standard for the development and certification of automated mobility technologies.

Contact

Dr. Sascha Knake-Langhorst

Head of Department
German Aerospace Center (DLR)
Institute of Transportation Systems
Digitalized Road Transport
Lilienthalplatz 7, 38108 Braunschweig