Martin Baumann
Zitiert von
Zitiert von
Autonomous driving: investigating the feasibility of car-driver handover assistance
M Walch, K Lange, M Baumann, M Weber
Proceedings of the 7th international conference on automotive user …, 2015
Evaluation of in-vehicle HMI using occlusion techniques: experimental results and practical implications
M Baumann, A Keinath, JF Krems, K Bengler
Applied ergonomics 35 (3), 197-205, 2004
From car-driver-handovers to cooperative interfaces: Visions for driver–vehicle interaction in automated driving
M Walch, K Mühl, J Kraus, T Stoll, M Baumann, M Weber
Automotive user interfaces, 273-294, 2017
UDRIVE: the European naturalistic driving study
R Eenink, Y Barnard, M Baumann, X Augros, F Utesch
Proceedings of Transport Research Arena, 2014
Towards cooperative driving: involving the driver in an autonomous vehicle's decision making
M Walch, T Sieber, P Hock, M Baumann, M Weber
Proceedings of the 8th international conference on automotive user …, 2016
A neural network model for driver’s lane-changing trajectory prediction in urban traffic flow
C Ding, W Wang, X Wang, M Baumann
Mathematical Problems in Engineering 2013, 2013
Situation awareness and driving: A cognitive model
M Baumann, JF Krems
Modelling driver behaviour in automotive environments, 253-265, 2007
The study design of UDRIVE: the naturalistic driving study across Europe for cars, trucks and scooters
Y Barnard, F Utesch, N van Nes, R Eenink, M Baumann
European Transport Research Review 8 (2), 14, 2016
Interaction design of automatic steering for collision avoidance: challenges and potentials of driver decoupling
M Heesen, M Dziennus, T Hesse, A Schieben, C Brunken, C Löper, ...
IET intelligent transport systems 9 (1), 95-104, 2015
External HMI for self-driving vehicles: which information shall be displayed?
SM Faas, LA Mathis, M Baumann
Transportation research part F: traffic psychology and behaviour 68, 171-186, 2020
A comparison of selected simple supervised learning algorithms to predict driver intent based on gaze data
F Lethaus, MRK Baumann, F Köster, K Lemmer
Neurocomputing 121, 108-130, 2013
Dynamic simulation and prediction of drivers’ attention distribution
B Wortelen, M Baumann, A Lüdtke
Transportation research part F: traffic psychology and behaviour 21, 278-294, 2013
Investigation of cooperative driving behaviour during lane change in a multi-driver simulation environment
M Heesen, M Baumann, J Kelsch, D Nause, M Friedrich
Human Factors and Ergonomics Society (HFES) Europe Chapter Conference …, 2012
The effect of cognitive tasks on predicting events in traffic
MRK Baumann, T Petzoldt, C Groenewoud, J Hogema, JF Krems
Proceedings of the European Conference on Human Centred Design for …, 2008
Elaborating feedback strategies for maintaining automation in highly automated driving
P Hock, J Kraus, M Walch, N Lang, M Baumann
Proceedings of the 8th International Conference on Automotive User …, 2016
The more you know: trust dynamics and calibration in highly automated driving and the effects of take-overs, system malfunction, and system transparency
J Kraus, D Scholz, D Stiegemeier, M Baumann
Human factors 62 (5), 718-736, 2020
Situation awareness and secondary task performance while driving
MRK Baumann, D Rösler, JF Krems
International conference on engineering psychology and cognitive ergonomics …, 2007
Carrot and Stick: A Game-theoretic Approach to Motivate Cooperative Driving through Social Interaction
M Zimmermann, D Schopf, N Lütteken, Z Liu, K Storost, M Baumann, ...
Transportation Research Part C: Emerging Technologies 88 (January), 159-175, 2018
How to design valid simulator studies for investigating user experience in automated driving: review and hands-on considerations
P Hock, J Kraus, F Babel, M Walch, E Rukzio, M Baumann
Proceedings of the 10th International Conference on Automotive User …, 2018
Using pattern recognition to predict driver intent
F Lethaus, MRK Baumann, F Köster, K Lemmer
International Conference on Adaptive and Natural Computing Algorithms, 140-149, 2011
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