Semantic 3D Models from Real World Scene Recordings for Traffic Accident Simulation

Ludwig Mohr, Martin Öttl, Michael Haberl, Matthias Rüther, Horst Bischof

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

We propose a novel extension to traffic accident simulation by means of semantic 3D environment information allowing for a broader view by incorporating the entire close-by environment. In this course, the effect of Advanced Driver Assistance Systems (ADAS) can be simulated, as well as the visibility of objects from people’s perspectives. We present an enclosed pipeline generating 3D objects, their extents and relative positions as well as their semantic class from a combination of photogrammetric recordings and LiDAR (Light Detection And Ranging) scans. By adjusting the desired level of detail, these objects are suitable for both direct integration into the 3D scene reconstruction for use in the accident simulation software PC-Crash, as well as for fine tuning parameters in traffic flow simulations and for convincing visualization and presentation of simulation results, be it in courts or to policy makers in urban planning.
Original languageEnglish
Title of host publicationProceedings of 7th Transport Research Arena TRA 2018
Publication statusPublished - 16 Apr 2018

Fingerprint Dive into the research topics of 'Semantic 3D Models from Real World Scene Recordings for Traffic Accident Simulation'. Together they form a unique fingerprint.

  • Cite this

    Mohr, L., Öttl, M., Haberl, M., Rüther, M., & Bischof, H. (2018). Semantic 3D Models from Real World Scene Recordings for Traffic Accident Simulation. In Proceedings of 7th Transport Research Arena TRA 2018