scholarly journals The Effect of Road Shoulder and Weather Conditions on the Occurrence of Rollover Crashes in Two-lane Highways

2019 ◽  
Author(s):  
Ali Abdi Kordani ◽  
Bahram Shirini ◽  
Mirbahador Yazdani
Keyword(s):  
Sensitivity Analysis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Final Model ◽  
Crash Data ◽  
Independent Variables ◽  
Binary Logit ◽  
Single Vehicle ◽  
Crash Types ◽  
Rollover Crash

Rollover crash is a type of dangerous crash that occurs often in two-lane highways. Therefore, this study evaluates the effect of road shoulder and weather condition on rollover crashes. Crash data show that 8,609 crashes were recorded from 2006 to 2009 on six two-lane highways located at the center of Iran. This data contains 1860 rollover crashes. Rollover crash in this paper not included the head on crashes and fixed object crashes. Therefore the rollover crashes are only single vehicle crashes. Binary logit was selected for modelling since there were two possible outcomes: rollover crashes and other crash types. The variables of the final model include highway class, road shoulder width, as well as rainy, snowy, foggy and night conditions. The modeling results show that rainy and foggy variables, with coefficients of 0.731 and 0.719 respectively, had the greatest effects on rollover crash occurrence. Also, road shoulder width and night conditions, with coefficients of 0.221 and 0.184 respectively, had the least effects on rollover crash occurrence. Afterward, sensitivity analysis was performed on all the independent variables, and the results show variable variation and indicate that the probability of rollover crash occurrence is 21.29 % on the mentioned highway.

Evaluation of Roundabout-Related Single-Vehicle Crashes

2017 ◽  
Vol 2637 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Beau Burdett ◽  
Andrea R. Bill ◽  
David A. Noyce
Keyword(s):  
Negative Binomial ◽  
Vehicle Crashes ◽  
Impaired Driving ◽  
Crash Data ◽  
Road Crashes ◽  
Run Off ◽  
Traffic Volumes ◽  
Single Vehicle ◽  
Total Proportion ◽  
Crash Types

Roundabouts reduce fatal and injury crashes at intersections when converted from other intersection control types. In Wisconsin, roundabouts have been linked to a 38% decrease in fatal and injury crashes. Part of this reduction can be attributed to crash types that result in the mitigation of more serious injuries. However, the reduction comes at a cost because other crash types, such as single-vehicle collisions, may increase. Six years of crash data on 53 roundabouts in Wisconsin were examined for crash causes and geometric characteristics that affected single-vehicle crashes. Weather and impaired driving, particularly by younger drivers, were primary causes for more than half of all single-vehicle crashes at the study roundabouts. Younger drivers (18 to 24 years of age) were involved in a significantly higher proportion of single-vehicle crashes than the total proportion of licensed drivers in that age group. Younger drivers were involved in approximately one-third of all crashes that involved impaired driving and in two-thirds of all speed-related single-vehicle crashes. A negative binomial model was constructed to estimate run-off-road crashes at approaches. It was found that roundabouts with higher approach speeds and higher traffic volumes experienced more run-off-road crashes. Landscaped central islands experienced significantly lower frequencies of run-off-road crashes.

Prediction of Occurrence and Severity of Run-off-Roadway Crashes on Rural Two-Lane Roadways Using Bayesian Networks

2021 ◽  
pp. 036119812110513
Author(s):  
Boniphace Kutela ◽  
Raul E. Avelar ◽  
Srinivas R. Geedipally ◽  
Ankit Jhamb
Keyword(s):  
Bayesian Networks ◽  
Graphical Model ◽  
Crash Data ◽  
Factors Associated ◽  
Independent Variables ◽  
The Road ◽  
Run Off ◽  
Study Results ◽  
On The Road ◽  
Crash Types

Run-off-roadway (ROR) crashes are among the most common crash types on rural two-lane roadways. Current methodologies to predict their occurrence and severity by considering conditional nature and interactions between independent variables require complex mathematical procedures. This study employs Bayesian networks (BNs), a non-functional form graphical model, to determine factors associated with the occurrence and severity of ROR crashes. The study used five-year (2014–2018) crash data collected from 397 randomly selected road segments within Texas. Out of 397 segments, 279 did not experience ROR crashes. The first BN model used all 397 segments and explored factors associated with occurrences of ROR crashes. The second BN model used the remaining 118 segments that involved ROR crashes and focused on factors associated with different crash types (guardrail [GR], overturning [OT], and fixed object [FO] crashes) and their associated severity levels. Study results revealed that the presence of horizontal curves and utility poles within the clear zone on the road individually increased the chance of ROR crashes by about 35%. Moreover, FO crashes resulted in 36% more fatal and injury crashes than GR crashes, which showed the effectiveness of guardrails in reducing severity. This study also explored the combined influence of variables on ROR crash occurrence and severity, as well as the interrelation between several independent variables. The proposed methodology can be used to evaluate the effectiveness of countermeasures.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

scholarly journals It’s the Weather: Quantifying the Impact of Weather on Retail Sales

2021 ◽  
Author(s):  
Natalie Rose ◽  
Les Dolega
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Influential Factor ◽  
Retail Sector ◽  
Retail Sales ◽  
Weather Impact ◽  
High Street ◽  
Sector Decision ◽  
The Impact ◽  
The Relationship

AbstractThe weather is considered as an influential factor on consumer purchasing behaviours and plays a significant role in many aspects of retail sector decision making. As a result, better understanding of the magnitude and nature of the influence of variable UK weather conditions can be beneficial to many retailers and other stakeholders. This study addresses the dearth of research in this area by quantifying the relationship between different weather conditions and trading outcomes. By employing comprehensive daily sales data for a major high street retailer with over 2000 stores across England and adopting a random forest methodology, the study quantifies the influence of various weather conditions on daily retail sales. Results indicate that weather impact is greatest in the summer and spring months and that wind is consistently found to be the most influential weather condition. The top five most weather-dependent categories cover a range of different product types, with health foods emerging as the most susceptible to the weather. Also, sales from out-of-town stores show a far more complex relationship with the weather than those from traditional high street stores with the regions London and the South East experiencing the greatest levels of influence. Various implications of these findings for retail stakeholders are discussed and the scope for further research outlined.

Examining Driver Injury Severity in Single-Vehicle Road Departure Crashes Involving Large Trucks

2021 ◽  
pp. 036119812110101
Author(s):  
Mehdi Hosseinpour ◽  
Kirolos Haleem
Keyword(s):  
Rural Areas ◽  
Injury Severity ◽  
Factors Affecting ◽  
Crash Data ◽  
Natural Logarithm ◽  
Concrete Barriers ◽  
Local Roads ◽  
Single Vehicle ◽  
Safety Countermeasures ◽  
Injury Severities

Road departure (RD) crashes are among the most severe crashes that can result in fatal or serious injuries, especially when involving large trucks. Most previous studies neglected to incorporate both roadside and median hazards into large-truck RD crash severity analysis. The objective of this study was to identify the significant factors affecting driver injury severity in single-vehicle RD crashes involving large trucks. A random-parameters ordered probit (RPOP) model was developed using extensive crash data collected on roadways in the state of Kentucky between 2015 and 2019. The RPOP model results showed that the effect of local roadways, the natural logarithm of annual average daily traffic (AADT), the presence of median concrete barriers, cable barrier-involved collisions, and dry surfaces were found to be random across the crash observations. The results also showed that older drivers, ejected drivers, and drivers trapped in their truck were more likely to sustain severe single-vehicle RD crashes. Other variables increasing the probability of driver injury severity have included rural areas, dry road surfaces, higher speed limits, single-unit truck types, principal arterials, overturning-consequences, truck fire occurrence, segments with median concrete barriers, and roadside fixed object strikes. On the other hand, wearing seatbelt, local roads and minor collectors, higher AADT, and hitting median cable barriers were associated with lower injury severities. Potential safety countermeasures from the study findings include installing median cable barriers and flattening steep roadside embankments along those roadway stretches with high history of RD large-truck-related crashes.

scholarly journals The effects of flooding and weather conditions on leptospirosis transmission in Thailand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sudarat Chadsuthi ◽  
Karine Chalvet-Monfray ◽  
Anuwat Wiratsudakul ◽  
Charin Modchang
Keyword(s):  
Sensitivity Analysis ◽  
Public Education ◽  
Mathematical Models ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Weather Conditions ◽  
Transmission Dynamics ◽  
Multiplication Rate ◽  
High Degree ◽  
Transmission Models

AbstractThe epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.

scholarly journals Terminal Airspace Capacity Evaluation Model under Weather Condition from Perspective of a Controller

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Liu
Keyword(s):  
Network Flow ◽  
Topological Structure ◽  
Evaluation Model ◽  
Weather Condition ◽  
Weather Conditions ◽  
Severe Weather ◽  
Safe Operation ◽  
Weather Factor ◽  
Route Network ◽  
Capacity Evaluation

A route network lays in the terminal airspace. The route network can be divided into multiple subnetworks according to sectors. When severe weather conditions occur, a controller takes measures to obtain safe operation of flights, such as navigation guidance or changing the availability of routes. In such circumstances, the route structure of a subnetwork is changed, and the controller’s attention paid to each route is also changed as well as the unit workload on it. As the subnetwork is handled by one controller, capacities of routes in it are associated. We find the way to determine the “related capacity” of a route in the conditions that whether topological structure of the terminal route network is changed or not. The capacity of the terminal route network calculated by network flow theory represents the capacity of terminal airspace. According to the analysis results, the weather factor reduces capacity of terminal airspace directly by reducing the capacities of routes blocked. Indirectly, it diverts controller’s attention to change capacities of other routes in the subnetwork.

Multiple regression analyses of midwinter fattening of the white-throated sparrow

1986 ◽  
Vol 64 (11) ◽  
pp. 2405-2411 ◽  
Author(s):  
Charles R. Blem ◽  
Michael H. Shelor
Keyword(s):  
Body Weight ◽  
Multiple Regression ◽  
Weather Conditions ◽  
Multiple Regression Model ◽  
Fine Tuning ◽  
Zonotrichia Albicollis ◽  
Independent Variables ◽  
Average Temperature ◽  
Extreme High Temperature

Midwinter lipid depots of the white-throated sparrow (Zonotrichia albicollis) at Richmond, Virginia, are correlated with a suite of environmental and morphological variables. Lipid reserves allow this species to survive even the most extreme winter conditions for several hours. Variables having the greatest individual correlations with lipid reserve are average temperature of the 20 days prior to capture, fat class, body weight, and long-term (32-year) average temperature of the date of capture. A comprehensive multiple regression model based on analyses of all possible independent variables accounts for 87% of the variation in lipid reserves. The most important independent variables in this model are body weight, mean temperature of the 20 days preceding collection, fat class, extreme high temperature of the day of capture, long-term average temperature, relative humidity, chill factor, wet-bulb temperatures of the day before and the day of capture, wing length, and precipitation. The "best" equation using only measurements of environment as independent variables included time of collection in hours after sunrise and hours before sunset, Eastern Standard Time, temperature of the 20 days prior to capture, and mean wind velocity of the day before capture. Models computed solely from temperature measurements included dry-bulb temperatures of the day of capture and the day before capture, low extreme temperatures of the day of capture, wet-bulb temperatures of the day before capture, and the 20-day average dry-bulb temperature of the period prior to collection. Fattening in response to weather conditions appears to be a form of "fine-tuning" of energy reserves superimposed on a more stable, intrinsic cycle of winter fattening.

scholarly journals Weather Prediction using Advanced Machine Learning Techniques

2021 ◽  
Vol 2089 (1) ◽  
pp. 012059
Author(s):  
G. Hemalatha ◽  
K. Srinivasa Rao ◽  
D. Arun Kumar
Keyword(s):  
Linear Relationship ◽  
Weather Prediction ◽  
Weather Condition ◽  
Weather Conditions ◽  
Machine Learning Techniques ◽  
Weather Data ◽  
Learning Techniques ◽  
Proposed Model ◽  
Non Linear ◽  
The Relationship

Abstract Prediction of weather condition is important to take efficient decisions. In general, the relationship between the input weather parameters and the output weather condition is non linear and predicting the weather conditions in non linear relationship posses challenging task. The traditional methods of weather prediction sometimes deviate in predicting the weather conditions due to non linear relationship between the input features and output condition. Motivated with this factor, we propose a neural networks based model for weather prediction. The superiority of the proposed model is tested with the weather data collected from Indian metrological Department (IMD). The performance of model is tested with various metrics..

Sign in / Sign up

Export Citation Format

Share Document