PREDICTION OF PROTECTED-PERMISSIVE LEFT-TURN PHASING CRASHES BASED ON CONFLICT ANALYSIS

Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations

EFFECT OF SOCIOECONOMIC AND DEMOGRAPHIC FACTORS OF DRIVER RESIDENCE ON CRASH OCCURRENCE

In the U.S., road traffic crashes are a leading cause of death. Crash data from the state of Kentucky shows that the per capita crash rates and crash-related fatalities were higher than the national average for over a decade. In effort to explain why the U.S. Southeast experiences higher crash rates than other regions of the country, previous research has argued the region’s unique socioeconomic provide a compelling explanation. Taking this observation as a starting point, this study examines the relationship between highway safety and socioeconomic characteristics using an extensive crash dataset from Kentucky. The primary goal of this research is to define the at-risk group of drivers based on the socioeconomic and demographic attributes of the zip codes in which drivers reside. This study utilizes crashes that occurred in Kentucky during the period 2013-2016. The quasi-induced exposure technique used assumes that the not-at-fault drivers represent the total population in question and the crash rate measure of exposure is developed in terms of the relative accident involvement ratio (RAIR), which is the ratio of the percentage of at-fault drivers to the percentage of not-at-fault drivers from the same subgroup. With fault status, dichotomous in nature, being the response variable, binary logistic regression is used, which is beneficial when the effects of more than one explanatory variable are examined. The final prediction model estimates the probability of the fault status of the driver based on multiple independent variables. Logistic regression models are developed to predict the occurrence of single- and two-unit crashes based on socioeconomic variables. The models for single- and two-unit crashes are quite similar to each other. The results indicate that variables such as driver age-group and gender, rurality, poverty level, average conviction, and driver population density of the area are associated with a driver’s likelihood to be involved in a crash. Educational attainment is observed to have an impact only on single-unit crash occurrence. Finally, it is concluded that younger and older drivers residing in zip codes with low socioeconomic conditions have a higher likelihood of causing a crash for both single- and two-unit crashes: agreeing with prior research findings and maintaining the typical U-shape curve of crash involvement. Males have higher at-risk probability in their younger ages than females, while females perform better at their young ages when compared to males. The findings of this research thus identify at-risk groups of drivers who are most likely to be involved in crashes, and potential safety measures are recommended to control the risk of these targeted groups

Effect of Socioeconomic Factors on Crash Occurrence

Road traffic crashes are a leading cause of death in the United States. In Kentucky, per capita crash rates and crash-related fatalities have outpaced the national average for over a decade. Wanting to explain why the U.S. Southeast sees higher crash rates than other regions, researchers have argued the region’s unique socioeconomic conditions provide a compelling explanation. Taking this observation as a starting point, this study examined the relationship between highway safety and socioeconomic characteristics using an extensive crash dataset from Kentucky. This research sought to identify at-risk drivers based on the socioeconomic and demographic attributes of the zip codes in which they reside. Using the quasi-induced exposure approach, binary logistic regression was used to develop predictions of driver at-fault probability based on socioeconomic characteristics of their residence zip code. Statistical analysis found that variables such as income, education level, poverty level, employment, age, gender, rurality, and number of traffic-related convictions of a driver’s zip code influence the likelihood of their being at fault in a crash. This finding can be used to identify groups of drivers most likely to be involved in crashes and develop targeted and efficient safety programs. Spatial analysis did not uncover robust correlations between county-level socioeconomic characteristics and at-fault driver involvement across the state. The results can be used to identify target groups for safety improvements and aid in the Kentucky Safety Circuit Rider Program activities

Effect of Socioeconomic Factors on Kentucky Truck Driver Crashes

Kentucky crash data for the 2015-2016 period reveal that per capita crash rates and increases in crash-related fatalities in the state outpaced the national average. To explain why the U.S. Southeast sees higher crash rates than other regions of the country, previous research has argued the region’s unique socioeconomic conditions provide a compelling explanation. Taking this observation as a starting point, this study uses an extensive crash dataset from Kentucky to examine the relationship between highway safety and socioeconomic and demographic characteristics. Its focus is single- and two-unit crashes that involve commercial motor vehicles (CMVs) and automobiles. Using binary logistic regression and the quasi-induced exposure technique to analyze data on the socioeconomic and demographic attributes of the zip codes in which drivers reside, factors are identified which can serve as indicators of crash occurrence. Variables such as income, education level, poverty level, employment, age, gender, and rurality of the driver’s zip code influence the likelihood of a driver being at fault in a crash. Socioeconomic factors exert a similar influence on CMV and automobile crashes, irrespective of the number of vehicles involved. Research findings can be used to identify groups of drivers most likely to be involved in crashes and develop targeted and efficient safety programs

Improving the Quality of Traffic Records for Traffic Incident Management

Traffic incidents in US roadways cause 25 percent of all delays experienced by users. The resulting congestion may lead to secondary crashes, increasing economic costs and further risking the lives of travelers. Traffic Incident Management is a process that detects, responds to, and clears traffic incidents as quickly as possible so that traffic flow is restored safely. This project analyzes the three TIM performance measures: Roadway Clearance Time, Incident Clearance Time and Secondary Crashes of Kentucky to identify a baseline for performance which may indicate potential for improvement. The study pinpoints different data sources, tools and technologies that can be used to collect and analyze TIM performance measures. Kentucky State Police (KSP) Crash Database and TRIMARC Incident Records are the two principal data sources used. In addition, Waze and HERE speed data are also examined for potential use. Lastly, the three national performance measures are summarized and analyzed. They comprise a baseline for future performance assessment

Improving the Quality of Traffic Records for Traffic Incident Management

Traffic incidents in US roadways cause 25 percent of all delays experienced by users. The resulting congestion may lead to secondary crashes, increasing economic costs and further risking the lives of travelers. Traffic Incident Management is a process that detects, responds to, and clears traffic incidents as quickly as possible so that traffic flow is restored safely. This project analyzes the three TIM performance measures: Roadway Clearance Time, Incident Clearance Time and Secondary Crashes of Kentucky to identify a baseline for performance which may indicate potential for improvement. The study pinpoints different data sources, tools and technologies that can be used to collect and analyze TIM performance measures. Kentucky State Police (KSP) Crash Database and TRIMARC Incident Records are the two principal data sources used. In addition, Waze and HERE speed data are also examined for potential use. Lastly, the three national performance measures are summarized and analyzed. They comprise a baseline for future performance assessment

Potential Effect of Cable Median Barriers on Commercial Vehicle Crossover Crashes

In 2016, commercial motor vehicles (CMVs) were involved in 4,079 fatal crashes in the U.S., representing 11.8 percent of all fatal crashes. State of Kentucky crash data for 2015-2016 show that per capita crash rates and increases in crash-related fatalities exceeded the national average. Crossover crashes occur when a vehicle leaves its intended path and veers into the path of oncoming traffic, typically resulting in head-on or sideswipe opposite direction crashes. Cable median barriers are a countermeasure which can potentially be used to mitigate crossover crashes. This research investigated the potential effectiveness of cable median barriers on CMV crashes. Analysis relied on an expert panel approach that evaluated the potential effects of cable barriers on altering the crash severity for fatal and incapacitating injuries (K and A in the KABCO severity index) and developed safety performance functions (SPFs) that resulted in crash prediction models that can be used to develop crash modification factors (CMFs) for estimating how the presence of cable median barriers can potentially affect crash occurrence and severity. The expert panel analysis concluded that safety gains are possible by installing cable median barriers and that their effectiveness is greater for fatalities. The average score of over 2 from the panel (on a scale from 0-5) indicates a moderate effect on crash outcomes. SPFs developed also supported the overall expert panel assessment. Analysis found that CMV crash outcomes benefit from installing cable median barriers, although only interstate routes were examined. The results indicate that CMV crashes will indeed be mitigated by installing cable median barriers. Both analyses supported this finding, and the overall conclusion is one of a positive impact. Benefits may be greater on divided roadways, since installations on two-lane roads may be more problematic due to space limitations. Additional research is recommended to evaluate this finding in light of which vehicle is the errant vehicle, since there could be significant implications for assessing the effectiveness of the cable median barrier if the CMV is the crossing-over vehicle

Study of Correlation of Pre-Operative Findings with Intra-Operative Ossicular Status in Patients with Chronic Otitis Media

Introduction: Chronic otitis media (COM) has been broadly classified into mucosal and squamous subtypes. COM types are associated with erosion of the ossicular chain. The aim of the present study was to correlate the type of COM, the site of perforation/retraction, and the type of disease pathology with the pattern and degree of ossicular chain necrosis.   Materials and Methods: A prospective cross-sectional study was performed in 76 cases of COM, who were subjected to tympanomastoidectomy. Pre-operative findings were compared with per-operative ossicular chain status and pathology.   Results: Incus was found to be the most vulnerable ossicle for erosion, followed by malleus and suprastructure of stapes. The pattern of multiple ossicle involvement was more common. Ossicular chain erosion was more common in squamous COM than mucosal COM (X2=66.25; P=0.0001) and in the presence of cholesteatoma and granulations. Ossicular necrosis was most common in squamous disease with cholesteatoma, followed by squamous disease with granulations, mucosal disease with granulations, and inactive mucosal disease in that order.   Conclusion: The degree of ossicular necrosis has a positive correlation with the type of disease pathology, being higher in squamous disease than in mucosal disease. The pattern of ossicular necrosis varies with the site of origin of the disease and the pattern of spread of cholesteatoma, being variable for pars tensa and pars flaccida squamous disease

Describing Adolescents with Disabilities’ Experiences of COVID-19 and Other Humanitarian Emergencies in Low- and middle-income Countries: a Scoping Review

Background: The COVID-19 pandemic and other humanitarian emergencies exacerbate pre-existing inequalities faced by people with disabilities. They experience worse access to health, education, and social services, and increased violence in comparison with people without disabilities. Adolescents with disabilities are amongst those most severely affected in these situations. Using participatory research methods with adoles-cents can be more effective than other methods but may be challenging in such emergency contexts. Objectives: We conducted a scoping review to: 1) describe the literature and methods used in peer-reviewed and grey literature on adolescents (aged ten to nineteen) with disabilities’ experience of COVID-19 and other humanitarian emergencies in low- and middle-income countries, and 2) identify research gaps and make recommendations for future research. Methods: The review followed a protocol developed using PRISMA guidelines and the Arksey and O’Malley framework. We searched grey and peer-reviewed literature between 2011 and 2021. Results: Thirty studies were included. Twelve were peer-reviewed, and of those seven used participatory methods. Humanitarian emergencies had adverse effects on adolescents with disabilities across health, education, livelihoods, social protection, and community participa-tion domains. Surprisingly few studies collected data directly with adolescents with disabil-ities. Twenty-three studies combined data from non-disabled children, caregivers, and disabled adults which made it challenging to understand adolescents with disabilities’ unique experience. Conclusions: Our review highlights both the scarcity of literature and the importance of conducting research with adolescents with disabilities in humanitarian contexts. Despite challenges, our review shows that it has been possible to conduct research with adolescents with disabilities to explore their experiences of humanitarian emergencies, and that these experiences were different from those of non-disabled adolescents. There is a need to disaggregate findings and support the implementation and reporting of rigorous research methods. Capacity development through partnerships between non-governmental organisa-tions and researchers may improve reporting of methods

UV Spectrophotometric Stability Indicating Method Development and Validation for the Determination of Finasteride Bulk and Dosage Form.

A simple, specific and economic UV spectrophotometric method has been developed using as diluents Methanol to determine the finasteride content in bulk and pharmaceutical dosage formulations. The quantitative determination of the drug has been carried out at a predetermined λmax of 255 nm, it was proved linier in the range 2-12 μg/mL and exhibited good correlation coefficient (R2=0.999) and excellent mean recovery (98-99%). LOQ and LOD were found to be1.178µg/ml and 5.40µg/ml respectively. The method was validated statically and by recovery studies for linearity, precision, repeatability and reproducibility as per ICH guideline. The obtained results proved that the method can be employed for the routine analysis of finasteride in bulk as well as in the commercial formulations. Keywords: Finasteride, UV Spectroscopy, Method Validation