scholarly journals Keep your mind on the road: Predicting mind-wandering while driving using classification of pre-probe oscillatory brain activity and driving performance

2014 ◽  
Vol 14 (10) ◽  
pp. 635-635
Author(s):  
J. He ◽  
C. W. Ang ◽  
A. J. Miller ◽  
V. Maddali ◽  
J. G. Gaspar ◽  
...  
2018 ◽  
Vol 8 (9) ◽  
pp. 342-351
Author(s):  
Umair Ahmed ◽  
Soleman Mozammel ◽  
Habib Ahmed

The present study attempted to investigate the role or training effectiveness on the employee performance of blue-collar employees working in Bahrain Transportation sector. Therein, the study examined the effectiveness of five different training programs offered to large vehicle drivers serving in the transportation industry. A total of 135 bus drivers from Alsadiq transport company Bahrain were sampled for the study to outline the effectiveness of three major training programs that they were offered including Customer Handling & Passenger Safety, Health & Hygiene and Guide to traffic laws and driving in Bahrain on their driving performance. Structural equation modeling using smart PLS was used for the present study for data analysis and interpretation. The study found a significant relationship impact of two programs on their driving performance of the respondents. The study forwards theoretical and practical implications and scope for further studies.


SLEEP ◽  
2020 ◽  
Vol 43 (7) ◽  
Author(s):  
Annemiek Vermeeren ◽  
Stefan Jongen ◽  
Patricia Murphy ◽  
Margaret Moline ◽  
Gleb Filippov ◽  
...  

Author(s):  
T. R. M. Leufkens ◽  
J. G. Ramaekers ◽  
A. W. de Weerd ◽  
W. J. Riedel ◽  
A. Vermeeren

SLEEP ◽  
2015 ◽  
Vol 38 (11) ◽  
pp. 1803-1813 ◽  
Author(s):  
Annemiek Vermeeren ◽  
Hong Sun ◽  
Eric F.P.M. Vuurman ◽  
Stefan Jongen ◽  
Cees J. Van Leeuwen ◽  
...  

2013 ◽  
Vol 43 (3) ◽  
pp. 556-561 ◽  
Author(s):  
Becca R. Levy ◽  
Reuben Ng ◽  
Lindsey M. Myers ◽  
Richard A. Marottoli

2021 ◽  
Author(s):  
Denise Bijlenga ◽  
Bram Urbanus ◽  
Nick N. J. J. M. van der Sluiszen ◽  
Sebastiaan Overeem ◽  
Jan G. Ramaekers ◽  
...  

SLEEP ◽  
2018 ◽  
Vol 42 (4) ◽  
Author(s):  
Annemiek Vermeeren ◽  
Stefan Jongen ◽  
Patricia Murphy ◽  
Margaret Moline ◽  
Gleb Filippov ◽  
...  

Abstract Study Objectives To assess potential effects of lemborexant on next-morning driving performance in adult and elderly healthy volunteers. Methods Randomized, double-blind, double-dummy, placebo and active-controlled, four period incomplete crossover study in 48 healthy volunteers (22 females), 23–78 years old. Participants were treated at bedtime for eight consecutive nights with two of three dose levels of lemborexant (2.5, 5, or 10 mg), zopiclone 7.5 mg (on the first and last night with placebo on intervening nights), or placebo. Driving performance was assessed in the morning on days 2 and 9 using a standardized highway driving test in normal traffic, measuring standard deviation of lateral position (SDLP). Drug–placebo differences in SDLP >2.4 cm were considered to reflect clinically meaningful driving impairment. Results Mean drug–placebo differences in SDLP following lemborexant 2.5, 5, and 10 mg on days 2 and 9 were 0.74 cm or less. The upper bound of the 95% confidence intervals (CIs) for lemborexant treatment groups were all below 2.4 cm and the 95% CIs included zero, indicating that the effects were neither clinically meaningful nor statistically significant. Symmetry analysis further supported the lack of clinically meaningful impairment with lemborexant. Conclusions When assessed starting ~9 h after lemborexant administration at bedtime the previous night, there was no statistically significant or clinically meaningful effect on driving performance in healthy adults and elderly, as assessed by either mean differences in SDLP relative to placebo or symmetry analysis. In this study, lemborexant at doses up to 10 mg was well-tolerated. Clinical Trial Registration clinicaltrials.gov, NCT02583451. https://clinicaltrials.gov/ct2/show/NCT02583451.


Author(s):  
Bernhard Schmiedel ◽  
Frank Gauterin ◽  
Hans-Joachim Unrau

Road wetness can lead to a significant loss in tyre traction. Although a driver can easily distinguish between dry and wet roads, the thickness of a water film on the road (wetness) and its impact on the vehicle dynamics are more difficult for a driver to classify. Furthermore, autonomous vehicles also need a graded classification of road conditions. There are known sensors, which are able to classify road conditions, but these are either not able to quantify the road wetness or are not suitable for mass production. Therefore, this work analyses a method to measure the road wetness by analysing tyre spray with plain acceleration sensors at positions like wheel arch liner or side skirt. It discusses influences of vehicle speed, road wetness, tyres, road structure and sensor positioning. The results show that a quantification of road wetness is possible, but it relies on the sum of all boundary conditions.


2015 ◽  
Vol 73 ◽  
pp. 19-29 ◽  
Author(s):  
Ignacio Alvarez ◽  
Hanan Alnizami ◽  
Jerone Dunbar ◽  
France Jackson ◽  
Juan E. Gilbert

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