Publication

The development and test of future Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) AD functions requires sophisticated data from pre-crash scenarios. As real-world traffic provides an infinite variety of scenarios and vehicles are usually sold in many markets, valuable simulation datasets from several countries seem
indispensable. The paper describes how we combined the format of the Pre-Crash Matrix (PCM) with global accident data from IGLAD. The goal was to create harmonized pre-crash simulation files from real accidents coming from several countries/continents and to use them exemplarily within a field-of-view analysis for future ADAS.

The basic data source is the IGLAD database. Within the “Initiative for the Global Harmonization of Accident Data” (IGLAD) traffic safety researchers from Europe, North America, South America, Asia, and Australia bring together road accident data in a harmonized dataset. Each single accident is reconstructed and contains relevant information like vehicle data, injury severities, anthropometric data, and scaled sketches.

The PCM format describes the vehicle dynamics (trajectories) in a defined time before the collision. It is similar to the OpenX formats and contains relevant information about the road layout, markings, view obstacles, etc.

The paper describes the process of creating IGLAD-PCM data, including the establishment of requirements, the harmonization of country-specific characteristics, and the definition of quality features.

In 2022, IGLAD-PCM was released for the first time providing 200 pre-crash simulations from real accidents coming from seven countries on three continents. The paper presents descriptive statistics (e.g. accident characteristics, accident configurations, injury severities) from these cases and a comparison to the current IGLAD dataset (with approximately 9,400 accidents from 10 different countries). We provide an overview of relevant accident situations and country-specific characteristics for different regions of the world, e.g. US, India, China, Germany, France, Italy, etc.

The paper also highlights the benefit of PCM data as one essential source for data-driven system development. During the concept definition of safety systems, pre-crash trajectory data is used to derive the required functional behavior. First, the relative positions and orientations of other traffic opponents are the basis for defining the necessary sensor field-of-view in given accident scenarios. Second, the speed distributions of ego and opponent serve as key performance indicators for the vehicle actuation system. Here, a relevant accident scenario is discussed, and relevant regional differences analyzed.

The IGLAD-PCM forms a unique global dataset of pre-crash simulations based on reconstructed traffic accidents. Of course, case numbers are quite low at this early stage, but will increase annually by more than 200. Using the data can enhance the development of ADAS and AD functions and help to adjust systems towards country-specific
characteristics.

We have demonstrated that the PCM allows to harmonize pre-crash data from different countries and still can cover regional specifics. As the PCM is an open data format, various scenario descriptions can easily be generated, and existing development tool chains can be supported. Thus, we believe that the PCM can serve as a standard format for data-driven system development and simulation.