scholarly journals Impact of LED Color Temperatures on Perception Luminance in the Interior Zone of a Tunnel considering Fog Transmittance

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Lili Dong ◽  
Enzhong Zhao ◽  
Yang Chen ◽  
Ge Qin ◽  
Wenhai Xu
Keyword(s):  
Traffic Safety ◽  
Light Attenuation ◽  
Experimental System ◽  
Calculation Model ◽  
Color Temperature ◽  
Low Light ◽  
Factors Affecting ◽  
Human Eye ◽  
Mesopic Vision ◽  
Interior Zone

LEDs are widely applied in highways and tunnels for their long life, low light attenuation, and being environment friendly in recent years. The influence of correlated color temperature (CCT) of LED on lighting safety has attracted people’s attention as the demand increased. In this paper, a calculation model of perception luminance of human eye considering mesopic vision and fog concentration was proposed. The influence of different CCTs on perception luminance of human eye under different levels of fog concentration and luminance was calculated and analyzed. The CCT of LED employed in the interior zone of a tunnel was selected based on the highest perception luminance in mesopic vision. Seven kinds of LEDs with different CCTs (3000–6500K) were applied in the experimental system with adjustable fog concentrations. The results showed that the main factors affecting visual perception are luminance and fog concentration. Higher luminance or lower fog concentration provides drivers with higher perception luminance. In contrast, although CCT has a less effect on perception luminance, LEDs with higher CCT (about 6500K) can provide higher perception luminance considering fog in mesopic vision. This paper provides technical support for tunnel lighting and guaranteeing traffic safety.

Regression analysis of indicators of a numerical experiment to determine the cooling time of oil

2020 ◽  
pp. 89-97
Author(s):  
A. U. Yakupov ◽  
D. A. Cherentsov ◽  
K. S. Voronin ◽  
Yu. D. Zemenkov
Keyword(s):  
Regression Analysis ◽  
Computer Experiment ◽  
Calculation Model ◽  
Cooling Time ◽  
Regression Coefficients ◽  
Fisher Criterion ◽  
Empirical Relationships ◽  
Factors Affecting ◽  
Oil Pipeline ◽  
Significant Regression

The article performed the processing of the results of a computer experiment to determine the cooling time of oil in a stopped oil pipeline. We proposed a calculation model in previous works that allows you to simulate the process of cooling oil.There was a need to verify the previously obtained results when conducting a laboratory experiment on a stand with soil. To conduct the experiment, it was necessary to conduct the planning of the experiment. The factors affecting the cooling time of oil in the oil pipeline, which will vary in the proposed experiment, are determined, empirical relationships are established. A regression analysis was carried out, and the dispersion homogeneity was checked using the Cochren criterion. The estimates of reproducibility variances are calculated. The adequacy hypothesis was tested using the Fisher criterion. Significant regression coefficients are established.

Research on the hydrographic survey cycle for updating navigational charts

2021 ◽  
pp. 1-13
Author(s):  
Jing Duan ◽  
Xiaoxia Wan ◽  
Jianan Luo
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Calculation Model ◽  
Impact Factors ◽  
Factors Affecting ◽  
Material Resources ◽  
Hydrographic Survey ◽  
Survey Planning ◽  
The Impact ◽  
The Relationship

Abstract Due to the vast ocean area and limited human and material resources, hydrographic survey must be carried out in a selective and well-planned way. Therefore, scientific planning of hydrographic surveys to ensure the effectiveness of navigational charts has become an urgent issue to be addressed by the hydrographic office of each coastal state. In this study, a reasonable calculation model of hydrographic survey cycle is established, which can be used to make the plan of navigational chart updating. The paper takes 493 navigational charts of Chinese coastal ports and fairways as the research object, analyses the fundamental factors affecting the hydrographic survey cycle and gives them weights, proposes to use the BP neural network to construct the relationship between the cycle and the impact factors, and finally establishes a calculation model of the hydrographic survey cycle. It has been verified that the calculation cycle of the model is effective, and it can provide reference for hydrographic survey planning and chart updating, as well as suggestions for navigation safety.

scholarly journals The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi

2020 ◽  
Vol 14 (1) ◽  
pp. 237-250
Author(s):  
Dinh Hiep ◽  
Vu V. Huy ◽  
Teppei Kato ◽  
Aya Kojima ◽  
Hisashi Kubota
Keyword(s):  
Primary School ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Primary Schools ◽  
Traffic Accidents ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Almost All

Introduction: One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents. Methods: The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software. Results and Discussion: The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk). Conclusion: Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.

scholarly journals Study on Change Rules of Factors Affecting Gas Loss during Coalbed Air Reverse Circulation Sampling

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Demin Chen ◽  
Wei Long ◽  
Yanyan Li ◽  
Rui Zhang
Keyword(s):  
Particle Size ◽  
Sharp Decrease ◽  
Experimental System ◽  
Gas Content ◽  
Impact Factors ◽  
Extreme Pressure ◽  
Factors Affecting ◽  
Reverse Circulation ◽  
Gas Loss ◽  
Skew Distribution

The gas loss in sampling is the root of coalbed gas content measurement error. The pressure and particle size have a significant impact on the gas loss. Using the self-developed coal particle pneumatic pipeline transportation experimental system, this study investigated the pressure and particle size changes in the sampling pipeline. It is found that the sampling process can be divided into four stages: no flow field stage, sample outburst stage, stable conveying stage, and tail purging stage. The extreme pressure in the sampling pipeline appears at the sample outburst stage; and the pressure in the pipeline has levelled off after sharp decrease in the stable conveying stage. It is also found that the extreme pressure increases first and then decreases with the increase of particle size. The duration of outburst stage is negatively correlated with particle size, and that of stable conveying stage is positively correlated with particle size. In addition, the results show that the loss rate of 1–3 mm particles is the smallest after the test but that particles less than 1 mm increase by about two times and particles greater than 3 mm decrease by more than three times. The study also shows that the particle size distribution of coal samples is a single peak with left skew distribution, and the gas reverse circulation sampling test does not change the location of the peak but makes it higher and sharper. The single size coal sample is more likely to collide than the mixture. This study can help to advance the understanding of impact factors on gas loss during reverse circulation sampling.

scholarly journals Factor Identification and Prediction for Teen Driver Crash Severity Using Machine Learning: A Case Study

2020 ◽  
Vol 10 (5) ◽  
pp. 1675 ◽  
Author(s):  
Ciyun Lin ◽  
Dayong Wu ◽  
Hongchao Liu ◽  
Xueting Xia ◽  
Nischal Bhattarai
Keyword(s):  
Machine Learning ◽  
Traffic Safety ◽  
Rural Areas ◽  
Computational Cost ◽  
The United States ◽  
Crash Severity ◽  
Rural Roads ◽  
Factors Affecting ◽  
West Texas ◽  
Teen Drivers

Crashes among young and inexperienced drives are a major safety problem in the United States, especially in an area with large rural road networks, such as West Texas. Rural roads present many unique safety concerns that are not fully explored. This study presents a complete machine leaning pipeline to find the patterns of crashes involved with teen drivers no older than 20 on rural roads in West Texas, identify factors that affect injury levels, and build four machine learning predictive models on crash severity. The analysis indicates that the major causes of teen driver crashes in West Texas are teen drivers who failed to control speed or travel at an unsafe speed when they merged from rural roads to highways or approached intersections. They also failed to yield on the undivided roads with four or more lanes, leading to serious injuries. Road class, speed limit, and the first harmful event are the top three factors affecting crash severity. The predictive machine learning model, based on Label Encoder and XGBoost, seems the best option when considering both accuracy and computational cost. The results of this work should be useful to improve rural teen driver traffic safety in West Texas and other rural areas with similar issues.

Examining the factors affecting the severity of run-off-road crashes in Abu Dhabi

2016 ◽  
Vol 43 (2) ◽  
pp. 132-138 ◽  
Author(s):  
Mohamed Shawky ◽  
Hany M. Hassan ◽  
Atef M. Garib ◽  
Hussain A. Al-Harthei
Keyword(s):  
Traffic Safety ◽  
Surface Condition ◽  
Probit Model ◽  
Abu Dhabi ◽  
Factors Affecting ◽  
Environment Factors ◽  
Crash Data ◽  
Road Crashes ◽  
Run Off ◽  
Road Type

Recently, the severity of injuries resulting from traffic crashes has been extensively investigated in numerous studies. However, the number of studies that addressed the severity of the run-off-road (ROR) crashes is relatively low. In the Emirate of Abu Dhabi (AD), approximately 22% of the total serious crashes and fatalities that occurred from 2007 to 2013 were ROR crashes. Despite these facts and the uniqueness of the composition of licensed drivers in AD (approximately 87% of them are non-Emiratis), the factors affecting the occurrence and severity of ROR crashes in AD have not been explicitly addressed in any prior studies. Therefore, this study aims to investigate the characteristics of at-fault drivers involved in ROR crashes in AD, the nature and main causes of those crashes. In this regard, conditional distribution and two-way contingency tables were developed. In addition, this study aims to identify and quantify the factors affecting the severity of ROR crashes such as driver, road, vehicle and environment factors. To achieve this goal, ordered probit model approach was employed. Crash data for a total of 3819 ROR crashes that occurred in AD were employed in the analysis. The results indicated that driver factors (carelessness, speeding, and nationality), vehicle characteristics (vehicle type), and road and environment factors (road type, crash location and road surface condition) were the significant factors influencing the severity of ROR crashes in AD. Countermeasures to improve traffic safety and reduce numbers and severity of ROR crashes in AD were discussed.

scholarly journals Inter-annual chemical stratification in Brazilian natural lakes: meromixis and hypolimnetic memory

2012 ◽  
Vol 24 (2) ◽  
pp. 127-139 ◽  
Author(s):  
Luciana Gomes Barbosa ◽  
Francisco Antonio Rodrigues Barbosa ◽  
Carlos Eduardo de Mattos Bicudo
Keyword(s):  
Electrical Conductivity ◽  
Light Attenuation ◽  
Total Dissolved Solids ◽  
Light Limitation ◽  
Low Light ◽  
Dissolved Solids ◽  
Attenuation Coefficients ◽  
Natural Lakes ◽  
Chemical Stratification ◽  
High Chemical Stability

AIM: chemical stratification and the patterns of light limitation and nutrients of two natural lakes, one shallow and the other one deep, were comparatively evaluated, both lakes located in the southeast Brazil. METHODS: pH, electrical conductivity, dissolved oxygen, total dissolved solids and nutrients were monthly collected during 5 consecutive years at the vertical profile of the two lakes. RESULTS: multivariate analysis indicated that the long thermal stratification period favored the occurrence of chemical stratification in the two lakes. However, in the deeper lake the stratified thermal profile with high hypolimnetic nutrient concentration, electrical conductivity, total dissolved solids and redox potential indicated that the mixing was not complete even during the annual circulation period, suggesting a slight meromixis and a high chemical stability at the hypolimnion. In the shallower lake, high light attenuation and high availability of nitrogen forms (mainly N-NH4) and phosphorus was observed along the water column, even during stratification. In the deeper lake, N and P co-limitation and low light attenuation coefficients were detected. CONCLUSION: thermal and chemical stratification patterns indicated that the Carioca lake is a shallow, turbid, nutrient rich, whereas the Dom Helvecio lake is a deep, clear, oligotrophic system with a tendency towards meromixis and the isolation of solutes in the hypolimnion. Consequently, meromixis was compared to a "hypolimnetic memory", which was defined, in the case of the deeper lake, as the maintenance of the chemical stratification along the years, during the lake thermal circulation period.

scholarly journals Exploring Factors Impacting Paths of Left-Turning Vehicles from Minor Road Approach at Unsignalized Intersections

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Guoqiang Zhang ◽  
Yuli Qi ◽  
Jun Chen
Keyword(s):  
Traffic Safety ◽  
Major Road ◽  
Traffic Crashes ◽  
Factors Affecting ◽  
Traffic Efficiency ◽  
Logistic Analysis ◽  
Unsignalized Intersections ◽  
Minor Road ◽  
Traffic Conflicts ◽  
Probability Prediction

At unsignalized intersections, left-turning vehicles from minor road approach are more likely to be involved in traffic conflicts and traffic crashes and are one of the most leading factors impacting traffic efficiency and capacity. The authors of the paper observed that some drivers behaved illegally and dangerously while performing left turns from minor road approach, resulting in abnormal trajectories at unsignalized intersections. By applying binary logistic analysis, a probability prediction model was developed to explore various factors affecting probability of normal path taken by drivers while turning left from minor road approach. Based upon the model, measures such as lowering running speeds of vehicles on major road or minor road and adding more lanes on minor road can be used to encourage more drivers to take normal vehicle paths, which is helpful for the improvement of traffic safety, efficiency, and capacity. Results of the paper can be used for the guidance of design and management of unsignalized intersections.

scholarly journals Mesopic Photometry and Street Lighting

2019 ◽  
pp. 67-72
Author(s):  
L. Nazarenko ◽  
H. Kononenko ◽  
Т. Mozharovska ◽  
V. Chernets
Keyword(s):  
Traffic Safety ◽  
Spectral Characteristics ◽  
Luminous Flux ◽  
Maximum Efficiency ◽  
Light Sources ◽  
Photometric System ◽  
Street Lighting ◽  
Factors Affecting ◽  
The Road ◽  
Lighting Systems

The article reveals the question of achieving security for people on the streets at night with the help of artificial lighting. The author analyzed the factors affecting traffic safety and the possibility of creating the necessary visual conditions for this by means of street lighting. In addition, the article raised an important question regarding the characteristics of the roadway. It is noted that the modern pavement is not standardized on the lighting characteristics. Knowing the spectral characteristics of the applied light sources, these data could be applied in the development of new types of canvases that would allow achieving a new level of illumination in terms of both improving the quality and its efficiency and economy. Without this, it is impossible to talk about the maximum efficiency of the use of the luminous flux as a whole. For existing lighting systems, the brightness calculation is performed by measuring the illumination and reflectivity of the road surface. The obtained brightness values are entered into the mesopic photometric system in order to determine the parameters of the complete system, which provides equivalent visual perception of the illuminated objects and is intended to replace the existing installation. To determine the required lamp power when replacing existing luminaires, it is recommended to use a mesopic photometric system, which allows you to perform calculations taking into account the S/P ratios. In this regard, it is necessary to thoroughly review the computer programs used in the creation of the lighting project, as well as to ensure active participation in international cooperation in the formation of modern lighting standards.

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