extended-abstract

Computational Modeling of Driving Behaviors: Challenges and Approaches

Authors:

Myounghoon Jeon,

Christian P. Janssen,

Shan BaoAuthors Info & Claims

AutomotiveUI '21 Adjunct: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 160 - 163

https://doi.org/10.1145/3473682.3477436

Published: 22 September 2021 Publication History

Abstract

Computational modeling has great advantages in human behavior research, such as abstracting the problem space, simulating the situation by varying critical variables, and predicting future outcomes. Although much research has been conducted on driver behavior modeling, relatively little modeling research has appeared at the Auto-UI Conferences. If any, most work has focused on qualitative models about manual driving. In this workshop, we will first describe why computational driver behavior modeling is crucial for automotive research and then, introduce recent driver modeling research to researchers, practitioners, and students. By identifying research gaps and exploring solutions together, we expect to form the basis of a new modeling special interest group combining the Auto-UI community and the computational modeling community. The workshop will be closed with suggestions on the directions for future transdisciplinary work.

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Cited By

Jeon MZhang YBao SJeong H(2022)“Dummies, Learning Modeling Made Easy”: Improving Modeling Education in Human Factors ResearchProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/107118132266103166:1(1586-1590)Online publication date: 27-Oct-2022
https://doi.org/10.1177/1071181322661031

Computational Modeling of Driving Behaviors: Challenges and Approaches
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
2. Human-centered computing

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cover image ACM Conferences

AutomotiveUI '21 Adjunct: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2021

234 pages

ISBN:9781450386418

DOI:10.1145/3473682

Copyright © 2021 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 September 2021

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Extended-abstract
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AutomotiveUI '21

Sponsor:

SIGCHI

AutomotiveUI '21: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 9 - 14, 2021

Leeds, United Kingdom

Acceptance Rates

Overall Acceptance Rate 248 of 566 submissions, 44%

Upcoming Conference

AutomotiveUI '25

Sponsor:
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17th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 21 - 25, 2025

Brisbane , QLD , Australia

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Cited By

Jeon MZhang YBao SJeong H(2022)“Dummies, Learning Modeling Made Easy”: Improving Modeling Education in Human Factors ResearchProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/107118132266103166:1(1586-1590)Online publication date: 27-Oct-2022
https://doi.org/10.1177/1071181322661031

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