Jonas Bärgman

发表

Sensor Fusion for Vehicle Positioning in Intersection Active Safety Applications

Jonas Sjöberg, Mathias R Lidberg, Tohid Ardeshiri, 2006 .

On the analysis of naturalistic driving data: development and evaluation of methods for analysis of naturalistic driving data from a variety of data sources

Jonas Bärgman, J. Bärgman, 2015 .

Analysis of the role of inattention in road crashes based on naturalistic on-board safety monitoring data

Johan Engström, Julia Werneke, Jonas Bärgman, 2013 .

Safer Glances, Driver Inattention, and Crash Risk: An Investigation Using the SHRP 2 Naturalistic Driving Study

Marco Dozza, Jonas Bärgman, Trent Victor, 2013 .

What Are Drivers Doing When They Aren't on the Cell Phone?

Carol A. C. Flannagan, Jonas Bärgman, András Bálint, 2018 .

Chunking: a procedure to improve naturalistic data analysis.

Marco Dozza, Jonas Bärgman, John D Lee, 2013, Accident; analysis and prevention.

DREAMi – Final Report

Jonas Bärgman, Azra Habibovic, 2013 .

Deliverable D3.3: Data management in euroFOT

Marco Dozza, David Sanchez, Jonas Bärgman, 2012 .

Detection and response to critical lead vehicle deceleration events with peripheral vision: Glance response times are independent of visual eccentricity.

Jonas Bärgman, Trent Victor, Malin Svärd, 2020, Accident; analysis and prevention.

Methods for Analysis of Naturalistic Driving Data in Driver Behavior Research

Jonas Bärgman, J. Bärgman, 2016 .

Quantifying Drivers’ Comfort-Zone and Dread-Zone Boundaries in Left Turn Across Path/Opposite Direction (LTAP/OD) Scenarios

Kip Smith, Julia Werneke, Jonas Bärgman, 2015 .

Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM).

Nobuyuki Uchida, Jonas Bärgman, Mikael Ljung Aust, 2013, Accident; analysis and prevention.

Factors contributing to commercial vehicle rear-end conflicts in China: A study using on-board event data recorders.

Xuesong Wang, Jonas Bärgman, Johan Engström, 2017, Journal of safety research.

Risk factors, crash causation and everyday driving

Mandy Dotzauer, Meng Zhang, Eric Stemmler, 2017 .

Safety device in a vehicle

Jonas Bärgman, Dion Kruse, 1999 .

Using Wireless Communication to Control Road-user Interactions in the Real World

Jonas Bärgman, Christian-Nils Åkerberg Boda, Marco Dozza, 2017 .

The perfect mismatch: Analysis of rear-end crash causation mechanisms based on naturalistic crash data

Johan Engström, Jonas Bärgman, Hrafnhildur Hekla Eiríksdóttir, 2017 .

The potential of naturalistic driving for in-depth understanding of driver behavior: UDRIVE results and beyond

Nicole van Nes, Michiel Christoph, Ingrid van Schagen, 2019, Safety Science.

Using Manual Measurements on Event Recorder Video and Image Processing Algorithms to Extract Optical Parameters and Range

Kip Smith, Johan Engström, Julia Werneke, 2017 .

DRIVER PERFORMANCE AND WORKLOAD USING A NIGHT VISION SYSTEM

Brandon Schoettle, Jonas Bärgman, John M. Sullivan, 2017 .

Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk

Marco Dozza, Johan Engström, Gustav Markkula, 2014 .

Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.

Marco Dozza, Jonas Bärgman, Christian-Nils Boda, 2017, Accident; analysis and prevention.

A quantitative driver model of pre-crash brake onset and control

Gustav Markkula, Jonas Bärgman, Johan Engström, 2017 .

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.

Jonas Bärgman, Bo Sui, Nils Lubbe, 2019, Accident; analysis and prevention.

Initial Analyses from the SHRP 2 Naturalistic Driving Study - Addressing Driver Performance and Behavior in Traffic Safety

Marco Dozza, Jonas Bärgman, Trent Victor, 2013 .

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies.

Gustav Markkula, Jonas Bärgman, Trent Victor, 2016, Accident; analysis and prevention.

On data security and analysis platforms for analysis of naturalistic driving data

Erik Steinmetz, Marco Dozza, Jonas Bärgman, 2011 .

Replacement of distractions with other distractions: A propensity-based approach to estimating realistic crash odds ratios for driver engagement in secondary tasks

Carol A. C. Flannagan, Jonas Bärgman, András Bálint, 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

How safe is tuning a radio?: using the radio tuning task as a benchmark for distracted driving.

Bryan Reimer, John D Lee, Jonas Bärgman, 2018, Accident; analysis and prevention.

On the analysis of naturalistic driving data

Jonas Bärgman, 2015 .

The UDrive dataset and key analysis results

Fridulv Sagberg, Martin Winkelbauer, Tsippy Lotan, 2017 .

Holistic assessment of driver assistance systems: how can systems be assessed with respect to how they impact glance behaviour and collision avoidance?

Jonas Bärgman, Trent Victor, 2020 .

Predicted road traffic fatalities in Germany: The potential and limitations of vehicle safety technologies from passive safety to highly automated driving

Jonas Fredriksson, Jonas Bärgman, Hanna Jeppsson, 2018 .

A comparison of computational driver models using naturalistic and test-track data from cyclist-overtaking manoeuvres

Marco Dozza, Jonas Bärgman, Jordanka Kovaceva, 2020, Transportation Research Part F: Traffic Psychology and Behaviour.

Interactions with vulnerable road users

Martin Winkelbauer, Tsippy Lotan, Nicole van Nes, 2017 .

An Invariant May Drive the Decision to Encroach at Unsignalized Intersections

Jonas Bärgman, Kersha Smith, Christian Blåberg, 2017 .

How does glance behavior influence crash and injury risk? A ‘what-if’ counterfactual simulation using crashes and near-crashes from SHRP2

Marco Dozza, Carol A. C. Flannagan, Jonas Bärgman, 2015 .

Vulnerable road users and the coming wave of automated vehicles: Expert perspectives

Neville A. Stanton, Natasha Merat, Riender Happee, 2021, Transportation Research Interdisciplinary Perspectives.

Methodological Framework for Modelling and Empirical Approaches (Deliverable D1.1 in the H2020 MSCA ITN project SHAPE-IT)

Martin Baumann, Jonas Bärgman, Mohamed Nasser, 2021 .

An Overview of Interfaces for Automated Vehicles (inside/outside) (Deliverable D2.1 in the H2020 MSCA ITN project SHAPE-IT)

Natasha Merat, Martin Baumann, Jonas Bärgman, 2021 .

Great expectations: a predictive processing account of automobile driving

Johan Engström, Daniel Nilsson, Gustav Markkula, 2018 .

Driver Distraction and Inattention

Mandy Dotzauer, Meng Zhang, Fridulv Sagberg, 2017 .