Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations

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Abstract

When designing experimental studies in the driving domain, an important decision is which driving scenarios to include. It is proposed that HMI need to be adaptive to the complexity of the driving situation, in order to avoid overloading the driver. To further study adaptive HMI a comprehensive list of factors that determine the perceived complexity of a driving situation is required, yet absent. In this, infrastructure- and traffic characteristics that may influence the perceived complexity of a driving situation were collected from literature. Next, four sets of driving scenarios of varying complexities were created and validated in an online survey. The results of this study include: 1) a list of infrastructure- and traffic characteristics that influence the overall complexity of a driving situation, and 2) validated scenarios of varying complexities. These outcomes help researchers and designers in setting up future driving studies.
Original languageEnglish
Title of host publicationAdvances in Human Factors of Transportation
Subtitle of host publicationProceedings of the AHFE 2020 International Conference on Human Factors in Transportation
EditorsNeville Stanton
Place of PublicationCham
PublisherSpringer
Pages3-10
Number of pages8
ISBN (Electronic)978-3-030-50943-9
ISBN (Print)978-3-030-50942-2
DOIs
Publication statusPublished - 1 Jul 2020
Event11th International Conference on Applied Human Factors and Ergonomics, AHFE 2020 - Hilton San Diego Bayfront, San Diego, United States
Duration: 16 Jul 202020 Jul 2020
Conference number: 11
https://ahfe2020.org/

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1212
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference11th International Conference on Applied Human Factors and Ergonomics, AHFE 2020
Abbreviated titleAHFE 2020
CountryUnited States
CitySan Diego
Period16/07/2020/07/20
Internet address

Keywords

  • Automated driving
  • Human-machine interaction
  • Driving situations
  • Complexity

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