Press Release, 4 February 2026
dSPACE and MathWorks have deepened their long-standing collaboration with a key integration that makes autonomous vehicle traffic simulation more efficient and streamlined for developers. Under the expanded partnership, road networks and models created with MathWorks’ RoadRunner tool can now be used directly in dSPACE’s latest traffic simulation environment, ASM OpenX, without the need for time-consuming conversions or manual rework. This integration aligns both tools around open data standards like OpenDRIVE and OpenSCENARIO, reducing errors and accelerating development workflows for engineers working on advanced driver-assistance systems (ADAS) and automated driving functions.
The combined solution aims to address a common challenge in autonomous software development: efficiently creating and validating traffic scenarios that closely mimic real-world conditions. Traditionally, engineers have spent significant time converting road and scenario files between different formats before they could run simulations. With RoadRunner’s rich editor and programmable APIs now feeding directly into ASM OpenX which natively supports OpenDRIVE and OpenSCENARIO that conversion step is eliminated. The result is a more cohesive toolchain where detailed 3D road maps, traffic behaviors, and operational design domains can flow seamlessly from design to simulation, saving time and improving reliability in virtual testing cycles.
Leaders from both companies note that this tighter integration reflects a shared commitment to open standards and practical engineering workflows, helping teams reduce development friction while improving simulation quality. By enabling smoother transitions from road modeling to traffic simulation, the collaboration supports quicker iteration on automated driving functions a critical advantage as vehicle makers and suppliers push toward higher levels of autonomy and safety.
This enhanced partnership highlights how aligning complementary tools through open standards can boost productivity in the increasingly complex arena of autonomous vehicle engineering.
Compiled using AI
