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Jonas Bärgman
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Analysis of naturalistic driving study data: SAFER glances, driver inattention, and crash risk SHRP 2 safety project SO8
T Victor, M Dozza, J Bärgman, CN Boda, J Engström, C Flannagan, ...
Wahsington, DC: Transportation Research Board of the National Academy of …, 2015
327*2015
Analysis of naturalistic driving study data: Safer glances, driver inattention, and crash risk
T Victor, M Dozza, J Bärgman, CN Boda, J Engström, C Flannagan, ...
SHRP 2 Report, 2015
3212015
Analysis of naturalistic driving study data: Safer glances, driver inattention, and crash risk
T Victor, M Dozza, J Bärgman, CN Boda, J Engström, C Flannagan, ...
SHRP 2 Report, 2015
3212015
Analysis of naturalistic driving study data: Safer glances, driver inattention, and crash risk
T Victor, M Dozza, J Bärgman, CN Boda, J Engström, C Flannagan, ...
SHRP 2 Report, 2015
3212015
A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies
G Markkula, J Engström, J Lodin, J Bärgman, T Victor
Accident Analysis & Prevention 95, 209-226, 2016
1812016
Vulnerable road users and the coming wave of automated vehicles: Expert perspectives
W Tabone, J de Winter, C Ackermann, J Bärgman, M Baumann, S Deb, ...
Transportation Research Interdisciplinary Perspectives 9, 100293, 2021
1652021
Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems
M Bärgman, Jonas, Boda, Christian-Nils, Dozza
Accident Analysis & Prevention 102, 165–180, 2017
1032017
Great expectations: A predictive processing account of automobile driving
J Engström, J Bärgman, D Nilsson, B Seppelt, G Markkula, GB Piccinini, ...
Theoretical Issues in Ergonomics Science 19 (2), 156-194, 2018
932018
How does glance behavior influence crash and injury risk? A ‘what-if’counterfactual simulation using crashes and near-crashes from SHRP2
J Bärgman, V Lisovskaja, T Victor, C Flannagan, M Dozza
Transportation Research Part F: Traffic Psychology and Behaviour 35, 152-169, 2015
932015
Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM)
A Habibovic, E Tivesten, N Uchida, J Bärgman, ML Aust
Accident Analysis & Prevention 50, 554-565, 2013
872013
A clustering approach to developing car-to-two-wheeler test scenarios for the assessment of Automated Emergency Braking in China using in-depth Chinese crash data
B Sui, N Lubbe, J Bärgman
Accident Analysis & Prevention 132, 105242, 2019
722019
Drivers overtaking cyclists in the real-world: Evidence from a naturalistic driving study
J Kovaceva, G Nero, J Bärgman, M Dozza
Safety Science 119, 199-206, 2019
692019
Driving aid system and method of creating a model of surroundings of a vehicle
J Bärgman, JE Källhammer
US Patent 8,346,463, 2013
692013
Quantifying drivers’ comfort-zone and dread-zone boundaries in left turn across path/opposite direction (LTAP/OD) scenarios
J Bärgman, K Smith, J Werneke
Transportation Research Part F: Traffic Psychology and Behaviour 35, 170-184, 2015
682015
Pedestrian detection with near and far infrared night vision enhancement
O Tsimhoni, J Bärgman, MJ Flannagan
LEUKOS 4 (2), 113-128, 2007
522007
Chunking: A procedure to improve naturalistic data analysis
M Dozza, J Bärgman, JD Lee
Accident Analysis & Prevention 58, 309-317, 2013
502013
Predicted road traffic fatalities in Germany: The potential and limitations of vehicle safety technologies from passive safety to highly automated driving
N Lubbe, H Jeppsson, A Ranjbar, J Fredriksson, J Bärgman, M Östling
Proceedings of IRCOBI conference. Athena, Greece, 2018
462018
The potential of naturalistic driving for in-depth understanding of driver behavior: UDRIVE results and beyond
N van Nes, J Bärgman, M Christoph, I van Schagen
Safety Science 119, 11-20, 2019
442019
Methods for analysis of naturalistic driving data in driver behavior research: From crash-causation analysis using expert assessment to quantitative assessment of the effect of …
J Bärgman
Chalmers University of Technology, 2016
41*2016
Methods for analysis of naturalistic driving data in driver behavior research
J Bärgman
Chalmers University of Technology, 2016
412016
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