DC13. AI-aided BIM-based design for road infrastructure

Göker Malik Altuntaş

Education
BA of Architecture: Anadolu University
MSc in Building Information Modelling (BIM): University of Liverpool
About
Experienced Building Information Modelling (BIM) Coordinator with extensive skills in Revit and ArchiCAD including plug-in development. Currently working on the recognition of 3D geometries by the FeaStNet Machine Learning (ML) algorithm.

Hosts: UH & Cegeka

Objectives:

  • To identify data generating processes to create BIMs for existing road networks and assess the available AI techniques and data
  • To evaluate the AI contribution to BIM approach efficiency (advanced BIM frameworks utilise AI to improve their efficiency and capabilities; BIM software can use ML to advance the model building process)
  • To advance the BIM application and further develop specifications of the digital twin approach to optimise the safe operation of CAVs and VRU

Expected results:

  • An AI-aided BIM-based framework for road infrastructure design practice and evaluation of best geometric design scenarios for CAVs’ movement
  • Application of BIM models to address the safety of routes used by cyclists and pedestrians, to let users become aware of the potential safety issues when using and learning about novel routes to their destination
  • Integration of BIM models within existing asset management systems
  • A BIM methodology to assess infrastructure risk elements that may cause CAVs to be outside their operational design domain (ODD)

Planned secondment(s):

  • INFRANEA – BE, Purpose: to validate the developed AI-aided BIM framework on some particular cases.