Accident Risk in Complementary Transport Chains

Author(s):  
Gerhard Hundhausen
Keyword(s):  
2007 ◽  
Author(s):  
Bruce G. Coury ◽  
Deborah Bruce
Keyword(s):  

2020 ◽  
Vol 40 (2) ◽  
pp. 234-247
Author(s):  
Santosh Kumari ◽  
◽  
D.D SHARMA ◽  
VIRENDER SINGH ◽  
◽  
...  

2019 ◽  
Vol 11 ◽  
pp. 180-192 ◽  
Author(s):  
M.V. Pelipenko ◽  
◽  
S.V. Balovtsev ◽  
I.I. Aynbinder ◽  
◽  
...  

2018 ◽  
Vol 6 (1) ◽  
pp. 63-70
Author(s):  
Dong Hoon Lee ◽  
Yong Taek Ju ◽  
heon kim ◽  
Kyo Shik Park

2021 ◽  
Vol 79 (1) ◽  
pp. 401-414
Author(s):  
Max Toepper ◽  
Philipp Schulz ◽  
Thomas Beblo ◽  
Martin Driessen

Background: On-road driving behavior can be impaired in older drivers and particularly in drivers with mild cognitive impairment (MCI). Objective: To determine whether cognitive and non-cognitive risk factors for driving safety may allow an accurate and economic prediction of on-road driving skills, fitness to drive, and prospective accident risk in healthy older drivers and drivers with MCI, we examined a representative combined sample of older drivers with and without MCI (N = 74) in an observational on-road study. In particular, we examined whether non-cognitive risk factors improve predictive accuracy provided by cognitive factors alone. Methods: Multiple and logistic hierarchical regression analyses were utilized to predict different driving outcomes. In all regression models, we included cognitive predictors alone in a first step and added non-cognitive predictors in a second step. Results: Results revealed that the combination of cognitive and non-cognitive risk factors significantly predicted driving skills (R2adjusted = 0.30) and fitness to drive (81.2% accuracy) as well as the number (R2adjusted = 0.21) and occurrence (88.3% accuracy) of prospective minor at-fault accidents within the next 12 months. In all analyses, the inclusion of non-cognitive risk factors led to a significant increase of explained variance in the different outcome variables. Conclusion: Our findings suggest that a combination of the most robust cognitive and non-cognitive risk factors may allow an economic and accurate prediction of on-road driving performance and prospective accident risk in healthy older drivers and drivers with MCI. Therefore, non-cognitive risk factors appear to play an important role.


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