On the Research of Control and Sequence Dynamics of Driving Tasks: Tools and Prospects.

Abstract

Event Abstract Back to Event On the Research of Control and Sequence Dynamics of Driving Tasks: Tools and Prospects. Inaki Rano1*, Sebastian Noth1, Gregor Schöner1 and Johann Edelbrunner2 1 Ruhr-Universitaet-Bochum, Germany 2 NISYS GmbH, Germany Big research efforts nowadays focus on modeling human drivers in order to improve safety and achieve smooth traffic flows. While dynamic models exist for driving tasks at the control level, models for lane keeping, car following and lane change, at the tactical level, the sequencing of these tasks is commonly performed as static finite state machines [Song et al, 2000]. Our aim is to bring light to the sequencing dynamics of the tactical level of human driving. This is a challenging task that requires accurate models of the control level tasks as performed by humans. This poster presents the tools and methods we will use to obtain complete models of human driving behavior. While most of the models are obtained from data where the human driver interacts with simulated drivers, we propose a multi-driver configuration to obtain more realistic driver interaction. We set up a multi-driver laboratory with ten independent cabins and implemented a realistic multi-driver simulator where all the drivers interact while driving on the same simulated road. All vehicle and environment state data relevant to model a driver behavior can be stored, the global status of the simulated cars can be monitored on-line through the local network and instructions can be delivered to individual drivers. Therefore, our simulator allows us to establish or force specific traffic situations, that could be impermissible in real life, while still having human drivers involved to gather relevant control and sequencing data sets. Based on these data sets and using state of the art control level models we plan to develop a methodology to build human-like driver models that can be used for testing and validating Advanced Driving Assistance Systems (ADAS). Once the control level is fully identified we will design and carry out experiments to model the sequence and decision dynamics in normal driving situations [Pellecchia et al, 2005]. Early experiments on car following control have been already performed and we are experimenting with a driver model for steering control that includes sensoriomotor aspects of human driving [Sentouh et al, 2009]. References A. Pellecchia, C. Igel, J. Edelbrunner and G. Schöner. “Making Driver Modeling Attractive” IEEE Intelligent Systems, pp 8-12. 2005. C. Sentouh, P Chevrel, F. Mars and F. Claveau. “A Sensoriomotor Driver Model for Steering Control”. Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics. 2009. B. Song, D. Delorme and J. VanderWerf. “Cognitive and Hybrid Model of Human Driver”. Proceedings of the IEEE Intelligent Vehicles Symposium 2000. Keywords: data analysis, driving modeling, machine learning Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Poster Topic: data analysis and machine learning (please use "data analysis and machine learning" as keyword) Citation: Rano I, Noth S, Schöner G and Edelbrunner J (2011). On the Research of Control and Sequence Dynamics of Driving Tasks: Tools and Prospects.. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00075 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Dr. Inaki Rano, Ruhr-Universitaet-Bochum, Bochum, Germany, inaki.rano@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Inaki Rano Sebastian Noth Gregor Schöner Johann Edelbrunner Google Inaki Rano Sebastian Noth Gregor Schöner Johann Edelbrunner Google Scholar Inaki Rano Sebastian Noth Gregor Schöner Johann Edelbrunner PubMed Inaki Rano Sebastian Noth Gregor Schöner Johann Edelbrunner Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.