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HFES Europe Proceedings 1 Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2016 Annual Conference Human Factors and User Needs in Transport, Control, and the Workplace Edited by Dick de Waard, Antonella Toffetti, Rebecca Wiczorek, Andreas Sonderegger, Stefan Röttger, Petr Bouchner, Thomas Franke, Stephen Fairclough, Matthijs Noordzij, and Karel Brookhuis ISSN 2333-4959 (online) Please refer to contributions as follows: [Authors] (2017), [Title]. In D. de Waard, A. Toffetti, R. Wiczorek, A. Sonderegger, S. Röttger, P. Bouchner, T. Franke, S. Fairclough, M. Noordzij, and K. Brookhuis (Eds.) (2017). Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2016 Annual Conference (pp. pagenumbers). Downloaded from http://hfes- europe.org (ISSN 2333-4959) Available as open access Published by HFES 2 Contents SURFACE TRANSPORTATION Investigation of driving behaviour reflecting drivers’ risk anticipation for pedestrian collision risk assessment of right-turns at intersections Hiroshi Yoshitake, Motoki Shino, Hisashi Imanaga, & Nobuyuki Uchida Modality effects of secondary tasks on hazard detection performance of younger and older pedestrians in a simulated road crossing task Jan Siegmann, Janna Protzak, & Rebecca Wiczorek Impact of interface sonification with touchless gesture command in a car Ludovic Jaschinski, Sébastien Denjean, Jean-François Petiot, Frank Mars, & Vincent Roussarie Car-following techniques: reconsidering the role of the human factor Antonio Lucas-Alba, María T. Blanch, Teresa Bellés, Ana M. Ferruz, Ana Hernando, Óscar M. Melchor, Luis C. Delgado, Francisco Ruíz, & Mariano Chóliz Comparing different types of the track side view in high speed train driving Niels Brandenburger, Mareike Stamer, & Anja Naumann A framework for human factors analysis of railway on-train data Nora Balfe AUTOMATION Should the steering wheel rotate? Evaluation of different strategies of steering wheel behaviour regarding controllability and driver acceptance while driving in conditional automated mode Alexandra König, Bernhard Schlag, & Julia Drüke How does a symmetrical steering wheel transformation influence the take-over process? Philipp Kerschbaum, Kamil Omozik, Patrick Wagner, Sophie Levin, Joachim Hermsdörfer, & Klaus Bengler Development and evaluation of a method for an intuitive driver’s workplace adjustment in a motor vehicle Yucheng Yang, Victor Orlinskiy, Ingrid Bubb, & Klaus Bengler 4 HMI AND USER EXPERIENCE Predicting driver intentions: a study on users’ intention to use Dorothea Langer, André Dettmann, Veit Leonhardt, Timo Pech, Angelika C. Bullinger, & Gerd Wanielik Driver sleepiness detection based on eye movement evaluation – a driving simulator study Alina Mashko, Petr Bouchner, & Stanislav Novotný Can User Experience affect buying intention? A case study on the evaluation of exercise equipment Giuseppe Fedele, Mario Fedriga, Silvano Zanuso, Simon Mastrangelo, & Francesco Di Nocera From aircraft to e-government – using NASA-TLX to study the digital native’s enrolment experience for a compulsory e-service Chris Porter “What does beep mean?” – context free interpretation of short sinus wave stimuli Matthias Wille, Sabine Theis, Peter Rasche, Christina Bröhl, Rebecca Kummer, & Alexander Mertens Spatially distributed visual, auditory and multimodal warning signals – a comparison André Dettmann & Angelika C. Bullinger AVIATION Performance using low-cost gaze-control for simulated flight tasks Ulrika Ohlander, Oscar Linger, Veronica Hägg, Linn Nilsson, Åsa Holmqvist, Sandra Durefors, Jens Alfredson, & Erik Prytz Eye activity measures as indicators of drone operators’ workload and task completion strategies Philippe Rauffet, Assaf Botzer, Alexandre Kostenko, Christine Chauvin, & Gilles Coppin HEALTH A method for quantitative estimate of risk probability in use risk assessment Monica Tavanti & Lee Wood What do they really want? Reveal users’ latent needs through contextual Co- Creation Martin Jentsch, Sebastian Wendlandt, Niels Clausen-Stuck, & Gerhard Krämer 5 CONTROL ROOM PERFORMANCE AND OPTIMISATION Changes in operators’ performance and situation awareness after periods of non-use in process control Merle Lau, Barbara Frank, & Annette Kluge Using eye tracking to explore design features in nuclear control room interfaces Alexandra Fernandes, Sathiya Kumar Renganayagalu, & Maren H. Rø Eitrheim Investigation of driving behaviour reflecting drivers’ risk anticipation for pedestrian collision risk assessment of right-turns at intersections Hiroshi Yoshitake1, Motoki Shino1, Hisashi Imanaga2, & Nobuyuki Uchida2 1The University of Tokyo 2Japan Automobile Research Institute Japan Abstract The objective of this study is to discover driving behaviour features that indicate pedestrian collision risk of right-turns at intersections for collision risk assessment. Right-turns at intersections is a typical accident scene of vehicle-pedestrian accidents in Japan, and if the collision risk of this scene becomes measurable, driver- assistance-systems will be able to prevent those accidents. To realise the objective, driving behaviour reflecting drivers’ risk anticipation was focused on. Because collisions occur when drivers fail to anticipate risk correctly and driving behaviour is partially determined considering the drivers’ anticipation, collision risk could be evaluated based on the driving behaviour features reflecting risk anticipation. To discover the driving behaviour features, first, near-miss incident data with high collision risk behaviour was analysed. Features of drivers’ visual search and vehicle control were extracted as driving behaviour index candidates. Next, pedestrian collision risk scenes were experimentally reproduced and the relationship between the driving behaviour index candidates and collision risk were investigated. Evaluation indices based on drivers’ visual search behaviour features showed significant correlation with pedestrian collision risk. From the results, it was clarified that pedestrian collision risk is evaluable with driver’s visual search behaviour, and the visual search behaviour feature to realize the evaluation was identified. Introduction In Japan, among the fatal traffic accidents occurred in 2015, collisions with crossing pedestrians accounted for the most. Therefore, prevention of traffic accidents involving pedestrians is demanded to decrease the fatalities. If collision risk against pedestrians is evaluable in advance based on driving behaviour, driving-assistance- systems will be able to support the driver to select sufficient driving behaviour for collision avoidance and prevent collisions with crossing pedestrians. To realise such a system, a method to evaluate the collision risk against pedestrians based on driving behaviour is necessary. In D. de Waard, A. Toffetti, R. Wiczorek, A. Sonderegger, S. Röttger, P. Bouchner, T. Franke, S. Fairclough, M. Noordzij, and K. Brookhuis (Eds.) (2017). Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2016 Annual Conference. ISSN 2333-4959 (online). Available from http://hfes-europe.org 8 Yoshitake, Shino, Imanaga, & Uchida Drivers select their driving behaviour (e.g. adjust vehicle speed, adjust margins between objects) not to collide with static objects and other traffic participants based on the risk anticipation of the traffic environment (Van der Hulst et al., 1999). If driving behaviour selected to avoid collision based on driver’s risk anticipation is identified, collision risk could be evaluated by comparing the present driving behaviour with the identified driving behaviour reflecting driver’s risk anticipation. To anticipate the transition of traffic environment and set driving behaviour targets based on the anticipation, drivers use visual information obtained from their eyes. From this fact, not only driving operation and vehicle behaviour but driver’s visual search behaviour is assumed to reflect the driver’s risk anticipation and has the possibility to evaluate collision risk based on the behaviour. Therefore, visual search behaviour as well as driving operation and vehicle behaviour is focused on in this study. Attention selection of driving is classified into four modes (Trick et al., 2004). Among the four modes, habit and deliberation are known as top-down selection, which are driven by goals and expectation (Engström et al., 2013). Habitual attention is often allocated to places where the main hazards exist based on the driver’s experience, but in some situations if the attention allocation does not suit the actual situation it becomes critical. To avoid it, habitual visual attention is needed to be overridden by deliberate visual attention. To drive deliberate selection correctly and avoid the critical situation, sufficient risk anticipation of the situation is necessary. From this, it is suggested that the deliberate attention selection is related to risk anticipation. Therefore, when a driver is not anticipating the appearance of a pedestrian in a certain driving situation, it is assumed that the driver’s visual attention will not be deliberate but habitual and the collision risk against the pedestrian will be high. The objective of this study is to discover driving behaviour features reflecting risk anticipation of the driver which can evaluate pedestrian collision risk for future driver assistance systems, focusing on driver’s visual search behaviour as well as driver’s operation and vehicle behaviour. First, candidates of driving behaviour indices are extracted by analysing near-miss incident
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