24 research outputs found
P5.010 Red light running rate in the Kumasi metropolis of Ghana
No full textIn Ghana, approximately 12% of all road traffic fatalities occur at junctions and the cause of these crashes, as assigned by the traffic police, include signal violation. Red light running place the violator and other road users at risk of road traffic crash. The main aim of the research work was to undertake baseline study to establish the current level of red light running through a direct observation survey and determine the risk factors associated with traffic light violation in the Kumasi Metropolis of Ghana. An uninterrupted road side observational survey was conducted at ten (10) signalized intersections using pro-forma checklist. A binary logit model was employed to determine the risk factors associated with traffic light violations. Overall, drivers were observed running red in 35% of all the red phases observed. From the model, factors which influence red light running include the age and gender of the driver, presence of a passenger in the vehicle, vehicle type, junction type, cycle length of the signal and queue length. There is a need for public awareness campaigns on the dangers of red light running. The education on red light violation must be accompanied by sustained enforcement of the traffic law by the traffic police to help reduce the violation of red light. Deployment of automatic red light cameras will also go a long way in ensuring enforcement at all times
Mode of transport to work by government employees in the Kumasi metropolis, Ghana
No full textThe paper presents the empirical results of a study into the journey to work by government employees in the Kumasi metropolis, Ghana using data obtained from a field survey conducted in April, 2012. The choice of mode of transport to work was investigated using a conditional logit regression model; the purpose was to determine individual and alternative specific variables that influence mode choice for trips to work. The results from the estimated model indicate that individual characteristics such as family size, educational status, income, home-to-work distance and marital status are significant determinants of the choice of commute mode by government employees. Furthermore, the results indicate that government workers are less likely to choose transport modes with longer travel times. It was also found that about 75% of the workers using public transport and that 19% of those using personal means of transport were prepared to shift to an institutionally arranged large bus services. It was therefore recommended that government institutions in the metropolis as a policy provide large buses to convey employees to and from work
Modelling the risk factors for injury severity in motorcycle users in Ghana
No full textAim: This study aims to determine risk factors associated with the injury severity of motorcycle users in Ghana.Subject and methods: Data on all reported crashes involving motorcycle users in Ghana were analyzed. The data were extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR). Generalized ordered logit models were specified separately for riders and pillion passengers to determine the relationship between injury severity, as an ordered categorical outcome, and a set of possible explanatory variables.Results: The results from the model showed that the injury severity of both riders and pillion passengers was significantly influenced by the day of the week when the crash occurred, weather conditions, road geometry, location type, and traffic control. In addition, the injury severity of riders was also influenced by their age, presence of passenger, and light conditions, whilst the injury severity of pillion passengers was influenced by the time of the crash.Conclusion: The findings from this study provide useful information to improve the understanding of risk factors associated with motorcycle user injury severity. Such data are also important to support the development of appropriate countermeasures to help prevent motorcycle crashes.</p
Structural equation modelling of COVID-19 knowledge and attitude as determinants of preventive practices among university students in Ghana
No full textCoronavirus disease (COVID-19) has distorted the economic development activities of many countries across continents. This undesirable tragedy has highly affected the educational system, which majorly contributes to the wellbeing of an individual and the economy as a whole. The study aims to explore the determinants of COVID-19 preventive practices among students considering their knowledge about COVID-19 and attitudes toward the disease. The data for the study were collected through an online questionnaire survey involving university students. The relationship between students’ knowledge, attitude and their preventive practices towards COVID-19 were investigated using structural equation modelling. The results indicated that most students demonstrated substantial knowledge on COVID-19, moderate to strongly agree attitude towards COVID-19, and sometimes practiced COVID-19 preventive and safety protocols. In addition, a positive relationship between knowledge and attitudes towards COVID-19 was established. Also, a positive effect was established for students’ knowledge about COVID-19 and preventive practices, whilst an adverse effect was confirmed for attitudes towards COVID-19 and practices to avoid spreading the COVID-19 disease.</p
A generalized ordered logit analysis of risk factors associated with driver injury severity
No full textAim: Road traffic crashes remain a major public health issue and have been the subject of debate in many studies due to their effect on society. This study contributes to the discussion by investigating the risk factors that significantly contribute to driver injury severity sustained in traffic crashes. Subject and methods: Using the crash data from the Greater Accra region of Ghana, spanning a 3-year period (2014–2016), a generalized ordered logit (GOL) model was estimated to determine the effect of a wide range of variables on driver injury severity outcome. Results: The results suggest that, in the event of a crash, more severe driver injury was influenced by multiple factors including driver’s gender, driver’s action (e.g., turning, overtaking, going ahead), number of vehicles involved, day of week of the crash, vehicle size, and road width. Conclusion: The findings of this study highlight the need to further study risk factors significantly influencing driver injury severity.</p
Prevalence rate of helmet use among motorcycle riders in Kumasi, Ghana
No full textObjectives: This study investigated the prevalence rate and identified the associated factors influencing helmet use in Kumasi, Ghana. Methods: The data used in this study were collected from motorcycle riders in the Kumasi metropolis through questionnaire survey. The contributing factors influencing helmet use were determined using a logistic regression model. Results: The results show that the rate of helmet use was about 47% and the influential factors include rider’s gender, marital status, educational attainment, ownership of a helmet, and motorcycle license. The most important reasons influencing noncompliance with helmet use as reported by the riders include discomfort, distance traveled, not owning a helmet, and forgetfulness. Conclusion: The findings highlight the need for policymakers to set up policy guidelines to enforce compliance with helmet use. For instance, any effort seeking to increase helmet use may first have to deal with helmet ownership, which also relates to the cost of helmet. In addition, helmet producers should conform to high quality standards in order to avoid discomfort while wearing a helmet.</p
The effect of road and environmental characteristics on pedestrian hit-and-run accidents in Ghana
No full textThe number of pedestrians who have died as a result of being hit by vehicles has increased in recent years, in addition to vehicle passenger deaths. Many pedestrians who were involved in road traffic accident died as a result of the driver leaving the pedestrian who was struck unattended at the scene of the accident. This paper seeks to determine the effect of road and environmental characteristics on pedestrian hit-and-run accidents in Ghana. Using pedestrian accident data extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana, a binary logit model was employed in the analysis. The results from the estimated model indicate that fatal accidents, unclear weather, nighttime conditions, and straight and flat road sections without medians and junctions significantly increase the likelihood that the vehicle driver will leave the scene after hitting a pedestrian. Thus, integrating median separation and speed humps into road design and construction and installing street lights will help to curb the problem of pedestrian hit-and-run accidents in Ghana.</p
The relationship between driver and passenger’s seatbelt use:a bivariate probit analysis
No full textVehicle seatbelt has been shown to have a beneficial impact on occupants. However, some occupants do not use the seatbelt when inside a moving vehicle. Despite the numerous investigation on the risk factors associated with seatbelt use by occupants, little is known about the relationship between driver and passenger seatbelt use. This gap is analyzed with road side observational survey data on driver and front-right seat passenger’s seatbelt use behaviour using bivariate probit model. The use of the bivariate probit model is based on the premise that the front-right passenger’s seatbelt use is endogenously related to that of the driver. Out of the 5,433 vehicles observed, the prevalence rate of driver and front-right passengers’ seatbelt use were 81% and 33%, respectively. In addition, there is a positive relationship between driver and passenger’s seatbelt use with correlation coefficient of 0.53. Thus, the unobserved factors that influence the probability of a driver seatbelt use also influence their front-right passenger's seatbelt use propensity.</p
Brief Research Report:A Monte Carlo Simulation Study of Small Sample Bias in Ordered Logit Model under Multicollinearity
No full textThis study investigated the small sample biasness of the ordered logit model parameters under multicollinearity using Monte Carlo simulation. The results showed that the level of biasness associated with the ordered logit model parameters consistently decreases for an increasing sample size while the distribution of the parameters becomes less variable with low extreme values. In the presence of multicollinearity, the level of biasness increases and this issue is particularly severe for small sample sizes. By comparing three different approaches for dealing with the multicollinearity problem in the model, the study demonstrated that the use of penalized maximum likelihood estimation technique provides better results which is interpretable compared to the other approaches considered.</p
Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana:Insights from a data mining and binary logit regression approach
No full textDespite the countless benefits derived from motorcycle usage, it has become a significant public health concern, particularly in developing countries, due to the plateauing number of fatal/serious injuries associated with them. Although it has been well documented that the frequency and fatality rates of intersection-related motorcycle crashes are high, little research efforts have been made to explore the contributory factors influencing motorcycle-involved crashes at these locations. Interestingly, no study has investigated the latent patterns and chains of factors that simultaneously contribute to the injury severity sustained by motorcycle crash casualties at intersections under different traffic control conditions in developing countries. Since motorcycles are mostly used as taxis in developing countries, it is imperative to consider the injury severity sustained by all crash casualties in the motorcycle safety analysis. This study bridges the research gap by employing a plausible data mining tool to explore hidden rules associated with motorcycle crash casualty injury severity outcomes at both signalized and non-signalized intersections in Ghana's most densely populated region, Accra, using three-year crash data spanning 2016–2018. Besides, a binary logit regression model was also employed to explore the impact of crash factors on casualty severity outcomes using the same dataset. The results from both analysis techniques were consistent; however, the data mining technique provided chains of factors which provided additional insights into the groups of factors that collectively influence the casualty injury severity outcomes. From the rule discovery results, while full license status, daytime/daylight, and shoulder presence increased the risk of fatal injuries at signalized intersections, factors such as inattentiveness, good road surface, nighttime, shoulder absence, and young rider were highly likely to increase casualty fatalities at non-signalized intersections. By controlling all or some of these risk factors, the level of injury severity on the roadways could be reduced. Based on the findings, we provide enforcement, education, and engineering-based recommendations to help improve motorcycle safety.</p
