Full TGIF Record # 315623
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DOI:10.1016/j.ufug.2021.126976
Web URL(s):https://www.sciencedirect.com/science/article/pii/S1618866721000017
    Last checked: 03/12/2021
    Access conditions: Item is within a limited-access website
https://www.sciencedirect.com/science/article/pii/S1618866721000017/pdfft
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Publication Type:
i
Refereed
Author(s):Jiang, Bin; He, Jibo; Chen, Jielin; Larsen, Linda
Author Affiliation:Jiang: Virtual Reality Lab of Urban Environments and Human Health, HKUrbanlabs, Faculty of Architecture, The University of Hong Kong, Hong Kong and Division of Landscape Architecture, Department of Architecture, The University of Hong Kong, Hong Kong; He: Department of Psychology, Tsinghua University, China; Chen: Virtual Reality Lab of Urban Environments and Human Health, HKUrbanlabs, Faculty of Architecture, The University of Hong Kong, Hong Kong and Department of Architecture, National University of Singapore, Singapore; Larsen: Smart Energy Design Assistance Center, University of Illinois at Urbana-Champaign
Title:Moderate is optimal: A simulated driving experiment reveals freeway landscape matters for driving performance
Source:Urban Forestry & Urban Greening. Vol. 58, March 2021, p. 1-16.
# of Pages:16
Publishing Information:Jena, Germany: Urban & Fischer
Related Web URL:https://www.sciencedirect.com/science/article/pii/S1618866721000017#abs0010
    Last checked: 04/08/2021
    Notes: Abstract only
Abstract/Contents:"Driving on freeways is a daily activity across the world. Poor driving performance on freeways can cause severe injuries and deaths. However, few studies have examined whether and to what extent different types of freeway landscapes influence driving performance. A simulated driving task was designed to measure the impacts of six types of freeway landscape on 33 participants driving performance. Each participant completed a driving experiment with six blocks of 90-minute driving sessions in a random sequence. During the experiment, participants driving performance was measured through eight parameters. A set of repeated-measure one-way ANOVA analyses show that landscapes with three-dimensional branch and foliage (shrub & tree) were generally more beneficial for driving performance than barren (concrete-paved ground) or low green landscape conditions (turf). Furthermore, a repeated-measure two-way ANOVA analysis of four conditions with vertical green foliage (two shrub and two tree conditions) showed moderate levels of greenness and complexity are optimal for driving performance."
Language:English
References:86
Note:"Article 126976"
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ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Jian, B., J. He, J. Chen, and L. Larsen. 2021. Moderate is optimal: A simulated driving experiment reveals freeway landscape matters for driving performance. Urban Forestry & Urban Greening. 58:p. 1-16.
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DOI: 10.1016/j.ufug.2021.126976
Web URL(s):
https://www.sciencedirect.com/science/article/pii/S1618866721000017
    Last checked: 03/12/2021
    Access conditions: Item is within a limited-access website
https://www.sciencedirect.com/science/article/pii/S1618866721000017/pdfft
    Requires: PDF Reader
    Access conditions: Item is within a limited-access website
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