Modelling Aspects of Longitudinal Control in an Integrated Driver Model - Detection and Prediction of Forced Decisions and Visual Attention Allocation at Varying Event Frequencies
Wortelen, Bertram and Zilinski, Malte and Baumann, Martin and Muhrer, Elke and Vollrath, Mark and Eilers, Mark and Lüdtke, Andreas and Möbus, Claus
Proceedings of Human Modelling in Assisted Transportation (HMAT)
Simulating and predicting behaviour of human drivers with Digital Human Driver Models (DHDMs) has the potential to support designers of new (partially autonomous) driver assistance systems (PADAS) in early stages with re-gard to understanding how assistance systems affect human driving behaviour. This paper presents the current research on an integrated driver model under de-velopment at OFFIS within the EU project ISi-PADAS2. We will briefly show how we integrate improvements into CASCaS, a cognitive architecture used as framework for the different partial models which form the integrated driver model. Current research on the driver model concentrates on two aspects of longitudinal control (behaviour a signalized intersections and allocation of visual attention dur-ing car following). Each aspect is covered by a dedicated experimental scenario. We show how experimental results guide the modelling process.
06 / 2010
978-88-470-1820-4
inproceedings
Springer
Iterate, ISi-PADAS, HUMAN
ISi-PADAS
Integrated Human Modelling and Simulation to support Human Error Analysis of Partially Autonomous Driver Assisatance Systems
Integrated Human Modelling and Simulation to support Human Error Analysis of Partially Autonomous Driver Assisatance Systems
P. Carlo Cacciabue, Magnus Hjälmdahl, Andreas Lüdtke, Costanza Riccioli
