Abstract
Driver intention recognition can enhance the driver-vehicle interaction by offering more intuitive assistance and automated driving support. Especially urban environments require fast reactions and hence assistance systems which act in accordance to driver’s intentions. Assistance should provide comfortably timed warnings only in situations when drivers really need this support and not in situations when the driver is already intending to react to a thread.
Fraunhofer IAO developed an algorithm in the UR:BAN MV subproject VIE to detect driver’s intention to brake when passing a pedestrian. The Fraunhofer algorithm analyses eye gaze data in correspondence with pedal activity to judge the driver’s attention on the pedestrian and the readiness to brake. BMW implemented the algorithm in the UR:BAN KA subproject SVT in a research vehicle and combined it with an environmental analysis of the situation.
In a test scenario the timing of a warning to the driver was adapted to the recognized intention to brake. Together with BMW’s pedestrian intention recognition algorithm, the driver intention recognition allows early warnings, while limiting the frequency of warnings to really relevant situations.
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References
European commission: EU transport in figures. Statistical pocket book, 2014 (2015). http://ec.europa.eu/transport/facts-fundings/statistics/doc/2014/pocketbook2014.pdf, Accessed 29 Apr 2015
Auto Club Europa: Daten und Fakten: Fußgänger-Unfälle. Eine Studie des ACE Auto Club Europa (2012). http://www.ace-online.de/presse/medien-service/grafiken/datei/studie-fussgaengerunfaelle.html?eID=nfcmedialibrary&tx_nfcmedialibrary_pi1%5Bdownuid%5D=14707, Accessed 29 Apr 2015
Nasar, J.L., Troyer, D.: Pedestrian injuries due to mobile phone use in public places. Accid Analysis Prev 57, 91–95 (2013)
Euro NCAP Rating Review: Report from the Ratings Group. European New Car Assessment Programme Ratings Group Report (2015). euroncap.blob.core.windows.net/media/16470/ratings-group-report-2015-version-10-with-appendix.pdf, Accessed 08 Apr 2015
Winner, H., Hakuli, S., Lotz, F. (eds.): Handbuch Fahrerassistenzsysteme. Grundlagen, Komponenten und Systeme für aktive Sicherheit und Komfort, 3rd edn. Springer Fachmedien, Wiesbaden (2015). ATZ/MTZ-Fachbuch
Manstetten, D., Bengler, K., Busch, F., Färber, B., Lehsing, C., Neukum, A.: “UR:BAN MV” – a German project focusing on human factors to increase traffic safety in urban areas. Proceedings of the 20th ITS World Congress, Tokyo, 2013. (2013)
Lehsing, C., Bngler, K., Busch, F., Schendzielorz, T.: UR:BAN – the German Research Initiative for User Centered Driver Assistance Systems and Traffic Network Management. Proceedings of the mobil.TUM Conference. (2013)
Schmidt, S., Färber, B.: Pedestrians at the kerb. Recognising the action intentions of humans. Transportation research part F: traffic psychology and behaviour 12.4 (2009):300–310 (2009)
Brouwer, N., Kloeden, H., Stiller, C.: Comparison and Evaluation of Pedestrian Motion Models for Vehicle Safety Systems. In Intelligent Transportation Systems (ITSC). IEEE 19th International Conference on (2207–2212), 2016, Sao Paolo, Brazil. IEEE (2016)
Kobiela, F.: Fahrerintentionserkennung für autonome Notbremssysteme. Technischen Universität Dresden, Dresden (2012)
Kopf, M.: Was nützt es dem Fahrer, wenn Fahrerinformations- und -assistenzsysteme etwas über ihn wissen? In: Maurer, M., Stiller, C. (eds.) Fahrerassistenzsysteme mit maschineller Wahrnehmung. basiert auf ausgewählten Vorträgen eines Workshops in Walting (Altmühltal), pp. 117–139. Springer, Berlin (2005)
Heckhausen, H., Gollwitzer, P.M.: Thought contents and cognitive functioning in motivational versus volitional states of mind. Motiv Emot 11(2), 101–120 (1987)
Achtziger, A., Gollwitzer, P.M.: Motivation und Volition im Handlungsverlauf. In: Heckhausen, J., Heckhausen, H. (eds.) Motivation und Handeln, pp. 309–335. Springer, Berlin, Heidelberg (2010). Springer-Lehrbuch
Diederichs, F., Pöhler, G.: Driving Maneuver Prediction Based on Driver Behavior Observation. Proceedings of the 5th International Conference on Applied Human Factors and Ergonomics AHFE 2014, Krakau, 19.7.2014. (2014). J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73
Diederichs, F.: Entwicklung von verhaltensbasierten Verfahren zur Erkennung von Fahrerintention für die Prädiktion von Fahrmanövern. PhD-Thesis. University of Stuttgart (in press)
Diederichs, F., Schuttke, T., Spath, D.: Driver Intention Algorithm for Pedestrian Protection and Automated Emergency Braking Systems. In Intelligent Transportation Systems (ITSC). 2015 IEEE 18th International Conference. IEEE, pp 1049–1054 (2015)
Diederichs, F., Seitz, W., Spath, D.: Fahrerintentionserkennung auf Basis von Blickanalysen zur Vermeidung von Fußgängerkollisionen. 11. Berliner Werkstatt Mensch-Maschine-Systeme (BWMMS), Berlin-Brandenburgische Akademie der Wissenschaften, Oktober 2015 (2015)
Rehder, E., Kloeden, H., Stiller, C.: “Head detection and orientation estimation for pedestrian safety.” Intelligent Transportation Systems (ITSC). 2014 IEEE 17th International Conference on. vol. 2014. IEEE (2014)
Höfer, M.: Dissertation: Fahrerzustandsadaptive Assistenzfunktionen. IAT der Universität Stuttgart (2015)
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Diederichs, F., Brouwer, N., Klöden, H., Zahn, P., Schmitz, B. (2018). Application of a Driver Intention Recognition Algorithm on a Pedestrian Intention Recognition and Collision Avoidance System. In: Bengler, K., Drüke, J., Hoffmann, S., Manstetten, D., Neukum, A. (eds) UR:BAN Human Factors in Traffic. ATZ/MTZ-Fachbuch. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-15418-9_14
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