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

Anika  Boelhouwer; Arie Paul van den Beukel; Mascha C. van der Voort; Marieke Martens

doi:10.1007/978-3-030-50943-9_1

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

Anika Boelhouwer, Arie Paul van den Beukel, Mascha C. van der Voort, Marieke Martens

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

94 Downloads (Pure)

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 language	English
Title of host publication	Advances in Human Factors of Transportation
Subtitle of host publication	Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation
Editors	Neville Stanton
Place of Publication	Cham
Publisher	Springer
Pages	3-10
Number of pages	8
ISBN (Electronic)	978-3-030-50943-9
ISBN (Print)	978-3-030-50942-2
DOIs	https://doi.org/10.1007/978-3-030-50943-9_1
Publication status	Published - 1 Jul 2020
Event	11th International Conference on Applied Human Factors and Ergonomics, AHFE 2020 - Hilton San Diego Bayfront, San Diego, United States Duration: 16 Jul 2020 → 20 Jul 2020 Conference number: 11 https://ahfe2020.org/

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	1212
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	11th International Conference on Applied Human Factors and Ergonomics, AHFE 2020
Abbreviated title	AHFE 2020
Country/Territory	United States
City	San Diego
Period	16/07/20 → 20/07/20
Internet address	https://ahfe2020.org/

Keywords

Automated driving
Human-machine interaction
Driving situations
Complexity
22/2 OA procedure

Access to Document

10.1007/978-3-030-50943-9_1

Boelhouwer2020determiningFinal published version, 1.46 MBLicence: Taverne

Cite this

Boelhouwer, A., van den Beukel, A. P., van der Voort, M. C., & Martens, M. (2020). Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations. In N. Stanton (Ed.), Advances in Human Factors of Transportation: Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation (pp. 3-10). (Advances in Intelligent Systems and Computing; Vol. 1212). Springer. https://doi.org/10.1007/978-3-030-50943-9_1

Boelhouwer, Anika ; van den Beukel, Arie Paul ; van der Voort, Mascha C. et al. / Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations. Advances in Human Factors of Transportation: Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation. editor / Neville Stanton. Cham : Springer, 2020. pp. 3-10 (Advances in Intelligent Systems and Computing).

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title = "Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations",

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.",

keywords = "Automated driving, Human-machine interaction, Driving situations, Complexity, 22/2 OA procedure",

author = "Anika Boelhouwer and {van den Beukel}, {Arie Paul} and {van der Voort}, {Mascha C.} and Marieke Martens",

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Boelhouwer, A, van den Beukel, AP, van der Voort, MC & Martens, M 2020, Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations. in N Stanton (ed.), Advances in Human Factors of Transportation: Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation. Advances in Intelligent Systems and Computing, vol. 1212, Springer, Cham, pp. 3-10, 11th International Conference on Applied Human Factors and Ergonomics, AHFE 2020, San Diego, California, United States, 16/07/20. https://doi.org/10.1007/978-3-030-50943-9_1

Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations. / Boelhouwer, Anika ; van den Beukel, Arie Paul; van der Voort, Mascha C. et al.
Advances in Human Factors of Transportation: Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation. ed. / Neville Stanton. Cham: Springer, 2020. p. 3-10 (Advances in Intelligent Systems and Computing; Vol. 1212).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Martens, Marieke

N1 - Conference code: 11

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AB - 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.

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Boelhouwer A, van den Beukel AP, van der Voort MC, Martens M. Determining Infrastructure- and Traffic Factors That Increase the Perceived Complexity of Driving Situations. In Stanton N, editor, Advances in Human Factors of Transportation: Proceedings of the AHFE 2020 International Conference on Human Factors in Transportation. Cham: Springer. 2020. p. 3-10. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-50943-9_1

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

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Keywords

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