The Braking systems as part of the mobility agenda (Part 2) session will take place on Thursday May 19th

Explore the challenges with enhancing the automated driving and assisted driving services of the future, available in English and Japanese.

The FISITA Autonomous HW and SW Technology Cluster issues its first thought leadership paper on Sensing Technology for Autonomous Vehicles.

Mega-trends are among the topics that are top-of-mind for FISITA members

Jaroslav Klapálek to talk about 3 different control/path planning algorithms ranging from simple reactive to close-to-optimal approaches

Patrick Fruth of TÜV SÜD to present on ensuring safety, secure & safe data access & handling, & sustainability in a changing future mobility

Bosch board of management member Dr Markus Heyn to present keynote on ADAS/automated driving at FISITA World Congress 2021

Jinzhu Wang describes details & implementation of a decision algorithm combining deep reinforcement learning with rule-based controllers

Anne Chambard introduces a virtual prototyping methodology in which a fully detailed virtual cabin for the Electric Vehicle was developed

Predictive braking control functions for autonomous driving during sudden changes in the road friction coefficient on sharp curves

Peter Riegl from THI discusses objective criteria for virtual vehicle safety testing that can help optimise real vehicle tests

A robust intelligent vehicle path tracking control strategy based on sliding mode predictive control (SMPC) to improve dynamic performance

Exploring new trends and related technologies of vehicular network architecture for future intelligent and connected vehicles

How understanding the emotional state of vehicle occupants will allow increased acceptance of autonomous vehicles in the future

A combined approach for interior concept development for autonomous vehicles considering human ergonomics, comfort & vehicle interior safety

A human perspective on the acceptance of autonomous vehicles with high level of automation & the challenges of charge of electric vehicles

Development of, and different optimization based tuning approaches for, an Unscented Kalman Filter algorithm based vehicle state estimator

Introducing an interface and optimizations method for the crash severity estimation and inevitability modelling in pre-crash safety systems

Dr Hajar Moussanif of Cadi Ayyad University provides additional responses to questions about autonomous vehicle testing and simulation

FISITA Online Conference videos on AV test and simulation, technology trends, carbon neutral mobility, automotive HMI, & more now available