In modern vehicles, driver assistance and safety systems are increasingly supporting the driver in complex or dangerous situations by applying preventive strategies. These strategies include warnings, enhanced braking assistance, and automatic interventions to increase road safety. A key challenge is to quantitatively assess the safety performance in terms of reduction or mitigation of traffic accidents, as these real-life effects are key considerations for all stakeholders involved in the planning of future mobility. Accident re-simulation and stochastic traffic simulation provide large opportunities to predict these effects. Both approaches require widely recognized models and reliable simulation. Hence, in order to agree on validity and reproducibility, the overall method, from the combined use of heterogeneous data sources in modeling to simulation metrics must be transparent.

Virtual “what-if” re-simulation based on reconstructed accident trajectories may show if a system had affected particular accidents on a case-by-case basis. However, reconstruction relies on limited traces and does not cover the complete traffic situation. Stochastic traffic simulation based on accident data can model how conflicts emerge and how to avoid or mitigate them. However, their exposure in real world traffic systems is not known. “openPASS” (open platform for the assessment of safety systems) will provide a free access, functional framework for a reliable, state-of-the-art, and standardized method of completing effectiveness analysis. This will allow incorporating additional data source and results from other evaluation methods:​ e. g. track tests or driving simulator experiments. These laboratory conditions deliver precise measurements for specific and thus limited points. In field operational tests, the functionality in real-world normal driving conditions can be observed. Accident data outlines target populations and size of potential impacts. For future validation and verification, ex-post statistical analysis should show significant reductions for specific vehicle models in large data sets, after a system is introduced into the mass market.

The openPASS Working Group was founded in August 2016 to jointly develop a harmonized tool for effectiveness evaluation within the scope of the Eclipse Foundation. This group aims at fostering open source solutions for simulation tools in the field of active and passive vehicle safety. The open source approach makes use of infrastructure and the vivid ecosystem of the Eclipse foundation that provides synergies of both professional software development and open source spirit. Resulting code of the first related Eclipse project sim@openPASS is expected to be published in Q2/2017.

Related methodologies are discussed in P.E.A.R.S. (an initiative in this field) and PEGASUS (a German research project) and aim to combine different assessment approaches, in order to achieve overall valid results. OpenPASS addresses this need for a common framework:​ applicable metrics, thorough data basis, comprehensible models of driver behavior and sensor effects – and flexible, modular simulation platforms. This paper shows various options how to get involved:​ use of the software, providing scientific input, creating new open source modules, joining the Working Group.

OpenPASS offers an open source platform designed around open standards which fulfills requirements such as modularity, transparency and performance. It will foster a creative eco-system of exchange for traffic and vehicle safety research, module development and data acquisition to support analyses that make present traffic systems a safer system with less or – optimally - no casualties.