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Cited by 58Human-Automation Interaction and SafetyTraffic control and managementTraffic and Road Safety

Adaptive driver modelling in ADAS to improve user acceptance: A study using naturalistic data

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Fleming, James M., Allison, Craig K., Yan, Xingda, Lot, Roberto, Stanton, Neville A.·2019·Safety Science
DOI 10.1016/j.ssci.2018.08.023
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  • The construction industry has the highest incidence of work-related injuries in both high-income and low-to-middle income countries.

    “The occurrence of work-related injuries varies depending on the industry, with the construction industry in both high-income countries and low-to-middle income countries having the highest incidence (Salminen et al. 2019; Villanueva et al. 2019).”

    From Impact of risk mitigation strategies on non-fatal injuries in the construction sector in qatar: a retrospective analysis (2025) · cites this paper as Villanueva et al. 2019

    Section 2, “ADAS for safety and eco-driving” (page unavailable), discusses UK road-traffic injuries, not occupational injuries by industry. Searches for construction-industry injury incidence and comparisons between high-income and low-to-middle-income countries found no passage addressing the claim. (LLM, conf=0.76)

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Cited by

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Authors
Fleming, J. M., Allison, C. K., Yan, X., Lot, R., & Stanton, N. A.
Affiliations
University of Southampton (GB)
Corresponding author
Fleming, James M.
ORCID
Venue
Safety Science
Publisher
Elsevier BV
Published
2019-11
Volume
119
Pages
76-83
ISSN
0925-7535 (ISSN-L)
DOI
10.1016/j.ssci.2018.08.023
OpenAlex
W2888883372
Cited by
58
References
2
Citations by year
2026: 2 · 2025: 13 · 2024: 6 · 2023: 6 · 2022: 9 · 2021: 8 · 2020: 8 · 2019: 6
FWCI
7.44
Type
journal article
Language
en
Open access
Licence
Locations
  • Safety Science (publishedVersion)
  • ePrints Soton (University of Southampton) (submittedVersion)
  • Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
  • Padua Research Archive (University of Padova) (submittedVersion, other-oa)
Funders
Engineering and Physical Sciences Research Council
Topics
  • Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
  • Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
Keywords
driver assistance systems, user acceptance, vehicle following, cornering, speed choice, inter-vehicle distance, lateral acceleration, curve driving, eco-driving, road safety, naturalistic driving data

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