scholarly journals Driver Compliance in Daytime Headlights Zones in the U.S

Author(s):  
Wayne D. Cottrell

Aims: Observe driver compliance with daytime headlights requirements along two-lane highways in California and Arizona.  Determine overall compliance rates, while identifying any statistical differences between highways. Study Design: Travel along highways having daytime headlight use requirements during daylight hours, recording ambient conditions and compliance.  Distinguish between cars, large commercial trucks, and motorcycles, and between manual (low-beam) and automated (very low-beam) headlights.  Add supportive information from synergistic research. Place and Duration of Study: California State Routes 4, 18, 74, 247, and U.S. Highway 95 in Arizona, during September 2010, and June and July 2015, over seven data collection days during the summer, and one on the first day of autumn. Methodology: Calculate average driver headlight compliance rates and deviations to a 95% level of confidence.  Assume that compliance follows a normal probability distribution pattern. Results: A total of 758 motor vehicles were observed.  Removing the 104 vehicles observed on a “cloudy” highway, 266 of the 654 drivers were using their headlights (40.7% ± 3.6% compliance).  There was no difference between the proportions of compliant drivers on the six highways (95% level of confidence).  A total of 66 of 104 drivers used their headlights under cloudy conditions (63.5% ± 9.6% compliance).  A Facebook survey of 24 respondents found that 20% of drivers were unaware of daytime headlights zones (DHZs), and an additional 13% were deliberately noncompliant.  Interviews of two California Highway Patrol officers revealed that citations for noncompliance were “not popular” (among the officers), and that there was some skepticism as to the effectiveness of the requirement. Conclusions: Further observation is needed under cloudy skies to develop a more precise proportion of compliance.  The low compliance suggests that the effectiveness of DHZs cannot be truly assessed.  Compliance might be improved with enhanced driver education, as to their existence and purpose, less reluctant enforcement, a revised headlight sign design, and more frequent signing.

1975 ◽  
Vol 11 (2) ◽  
pp. 229-235 ◽  
Author(s):  
Stephen J. Burges ◽  
Dennis P. Lettenmaier ◽  
Courtney L. Bates

2020 ◽  
Vol 1013 ◽  
pp. 114-119
Author(s):  
Azhar Badaoui

The aim of this paper is the evaluation of concrete carbonation depth from a probabilistic analysis, focusing specifically on the study of the marble powder diameters randomness effect on the reinforced concrete carbonation. Monte Carlo simulations are realized under the assumption that the marble powder diameter (Dmp) is random variable with a log-normal probability distribution.


1999 ◽  
Vol 56 (2) ◽  
pp. 191-200 ◽  
Author(s):  
James H Power ◽  
E Barry Moser

Sampling with nets or trawls remains a common technique for determining the comparative abundances of aquatic organisms, and the objective of such studies is frequently to evaluate relationships among the counts of individuals caught and exogenous variables. Analysis of such data is often done with a general linear model (e.g., ANOVA, ANCOVA, regression), assuming an underlying normal probability distribution. Such analyses are not fully satisfactory because of the symmetry and continuous nature of the assumed normal probability distribution and the high variance to low mean value relationships common to counts of biological populations. The negative binomial is a discrete probability distribution that is recognized as a suitable descriptor of organism count data. We present an approach for undertaking linear model analyses of net catch data that permits estimation of model parameters (including the negative binomial k parameter) and hypothesis testing of both continuous and discrete model effects and their interactions using bootstrap replication. The analysis incorporates adjustment for varying element sizes, such as differences in the amounts of water filtered during sampling.


2021 ◽  
pp. 153-169
Author(s):  
Rehan Ahmad Khan Sherwani ◽  
Muhammad Aslam ◽  
Muhammad Ali Raza ◽  
Muhammad Farooq ◽  
Muhammad Abid ◽  
...  

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