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Jonas Bärgman

Chalmers University of Technology

Gothenburg

SE-412 96 Goteborg

Sweden

  • Chalmers University of Technology

SCHOLARLY PAPERS

4

DOWNLOADS

66

TOTAL CITATIONS

0

Scholarly Papers (4)

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1.

Strategic Decision Points in Experiments: A Predictive Bayesian Optional Stopping Method

Number of pages: 36 Posted: 03 Mar 2025
Xiaomi Yang, Carol Flannagan and Jonas Bärgman
Chalmers University of Technology, University of Michigan at Ann Arbor and Chalmers University of Technology
Downloads 32 (1,304,549)

Abstract:

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Bayesian stopping, experiment planning, decision-making, sample size, predictive power analysis

2.

Evaluation of Adaptive Sampling Methods in Scenario Generation for Virtual Safety Impact Assessment of Pre-Crash Safety Systems

Number of pages: 49 Posted: 13 Apr 2025
Xiaomi Yang, Henrik Imberg, Carol Flannagan and Jonas Bärgman
Chalmers University of Technology, Chalmers University of Technology, University of Michigan at Ann Arbor and Chalmers University of Technology
Downloads 23 (1,411,822)

Abstract:

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virtual safety impact assessment, active sampling, importance sampling, machine learning, domain knowledge, crash-causation model, glance behavior.

3.

Practical validation of synthetic pre-crash scenarios

Number of pages: 13 Posted: 13 Jun 2026
Jian Wu, Ulrich Sander, Carol Flannagan and Jonas Bärgman
Chalmers University of Technology, affiliation not provided to SSRN, University of Michigan at Ann Arbor and Chalmers University of Technology
Downloads 11

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Practical Equivalence Testing, Synthetic Pre-Crash Scenarios, Driving automation systems, Virtual Simulations, Safety impact assessment

4.

How Safe is Tuning a Radio?: Using the Radio Tuning Task as a Benchmark for Distracted Driving

MIT Center for Transportation & Logistics Research Paper No. 2018/009, Accident Analysis & Prevention, volume 110, 2018[10.1016/j.aap.2017.10.009]
Posted: 28 Apr 2025
Ja Young Lee, John D. Lee, Jonas Bärgman, Joonbum Lee and Bryan Reimer
affiliation not provided to SSRN, affiliation not provided to SSRN, Chalmers University of Technology, affiliation not provided to SSRN and Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics

Abstract:

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Crash risk, Driver distraction, Naturalistic driving data, Radio tuning