Transport Safety computer analysis can provide useful information to researchers and engineers to design better vehicles, as well as investigate future safety concepts. Computer models are nowadays ever more complex, due to the fact that software is easier to use, algorithms more precise and solvers more powerful. Science is gaining accuracy, but the bottleneck of time is still present. Machine learning brings new opportunities to move science and engineering forward.
This webinar highlights the benefits of using artificial intelligence in the design of vehicle crash structures as well as occupant kinematics in future autonomous vehicles.
This webinar is a part of Rev-Sim’s Learn From Your Peers webinar series.
View recordings of all previous webinars here.
Dr Christophe Bastien is an Associate Professor in Transport Safety, leading the Transport Safety and Simulation research group. He has over 27 years of industrial and academic experience in the field of vehicle safety evidenced by 21 patents, 29 journal publications and 125 citations. Winner of the Prince Michael International Road Safety Award 2021 on “Delivering Improved Pedestrian Post Crash Triage”, his research expertise relates to the field of human traumatology computation in transport settings. A recent research output is an innovative computer method, based on Peak Virtual Power (PVP), showing to predict accurately soft tissue injuries compared to post-mortem information. His group has created a trauma research method, which has been implemented worldwide as part of the Total Human Model for Safety (THUMS), developed by JSOL. He leads the trauma simulation strategy of The Central Trauma Research and Innovation Platform (C-TRIP), fostering innovation collaborations between UHCW, the University of Warwick (UoW) and Coventry University (CU). Dr Christophe Bastien lectures crashworthiness modelling using explicit finite element, as well as vehicle safety, which he teaches at undergraduate, postgraduate and industry level. Dr Bastien’s interests are also in the quantification of human injury risks, trauma characterisation and comfort in future Connected Autonomous Vehicles.
