Department of Civil, Construction & Environmental Engineering

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Browsing Department of Civil, Construction & Environmental Engineering by Author "Adanu, Emmanuel Kofi"

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    Exploratory applications of epidemiological methods in transport safety and mobility
    (University of Alabama Libraries, 2017) Adanu, Emmanuel Kofi; Jones, Steven L.; University of Alabama Tuscaloosa
    Evident similarities and links between the outcomes of traffic crashes and stranded (or constrained) mobility have been identified and are reported in this research. Generally, a high level of travel activities is an indicator of high crash exposure. However, studies have shown that the highest rates of traffic fatalities occur in low- and middle-income regions, where many citizens experience relatively low levels of motorized travel. This ironic observation reveals serious challenges facing transport mobility systems in the less privileged regions of the world. Studies on traffic crashes and mobility constraints also reveal that they both have individual and regional variations in their occurrence, effects, and severities. Consequently, the outcomes of traffic crashes and constrained mobility are serious public health concerns worldwide. As public health problems, their study is analogous to the study of diseases and other injuries and thus, suitable for the application of epidemiological techniques. This dissertation therefore explores the use of epidemiological techniques to analyze traffic crashes and mobility/accessibility constraints from a human-centered perspective. The dissertation therefore consists of two major focus areas. The first part of the study applies widely used epidemiology/public health – based statistical tools to analyze traffic crashes with the aim of gaining better understanding of the human-centered causes and factors that influence these causes, and how these ultimately affect the severity of crashes. This part is further divided into two sub-sections. The first sub-section used latent class analysis to identify homogeneous clusters of human-centered crash causal factors and then applied latent class logit and random parameters logit modeling techniques to investigate the effects of these factors on crash outcomes. The second sub-section of the first part of the dissertation applies multilevel regression analysis to understand the effects of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across sub-regions. Both studies are necessary to develop potential human-centered mitigations and interventions and for the effective and targeted implementation of those countermeasures. The second part of the study provides an epidemiological framework for addressing mobility/accessibility constraints with a view to diagnosing symptoms, recommending treatment, and even discussing the idea of transmission of constrained mobility among city dwellers. The medical condition, hypomobility, has been used to connote constrained mobility and accessibility for people in urban areas. In transportation and urban studies, hypomobility can result in a diminished ability to engage in economic opportunities and social activities, hence deepening poverty and social exclusion and increasing transport costs, among other negative outcomes. The condition is especially pronounced in poor urban areas in developing countries. The framework proposed in this study is expected to help identify and address barriers to mobility and accessibility in the rapidly growing cities throughout the developing world, with particular applicability to the rapidly developing cities in Sub-Saharan Africa. Ultimately, this dissertation explores the application of epidemiological techniques to two major transportation problems: traffic safety and constrained mobility. The techniques presented in this dissertation provide policy makers, agencies, and transport professionals with tools for evidence-based policies and effective implementation of appropriate countermeasures.
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    How did the COVID-19 pandemic affect road crashes and crash outcomes in Alabama?
    (Pergamon, 2021) Adanu, Emmanuel Kofi; Brown, David; Jones, Steven; Parrish, Allen; University of Alabama Tuscaloosa
    With the rising number of cases and deaths from the COVID-19 pandemic, nations and local governments, including many across the U.S., imposed travel restrictions on their citizens. This travel restriction order led to a significant reduction in traffic volumes and a generally lower exposure to crashes. However, recent preliminary statistics in the US suggest an increase in fatal crashes over the period of lockdown in comparison to the same period in previous years. This study sought to investigate how the pandemic affected road crashes and crash outcomes in Alabama. Daily vehicle miles traveled and crashes were obtained and explored. To understand the factors associated with crash outcomes, four crash-severity models were developed: (1) Single-vehicle (SV) crashes prior to lockdown order (Normal times SV); (2) multi-vehicle (MV) crashes prior to lockdown order (Normal times MV); (3) Single-vehicle crashes after lockdown order (COVID times SV); and (4) Multi-vehicle crashes after lockdown order (COVID times MV). The models were developed using the first 28 weeks of crashes recorded in 2020. The findings of the study reveal that although traffic volumes and vehicle miles traveled had significantly dropped during the lockdown, there was an increase in the total number of crashes and major injury crashes compared to the period prior to the lockdown order, with speeding, DUI, and weekends accounting for a significant proportion of these crashes. These observations provide useful lessons for road safety improvements during extreme events that may require statewide lockdown, as has been done with the COVID-19 pandemic. Traffic management around shopping areas and other areas that may experience increased traffic volumes provide opportunities for road safety stakeholders to reduce the occurrence of crashes in the weeks leading to an announcement of any future statewide or local lockdowns. Additionally, increased law enforcement efforts can help to reduce risky driving activities as traffic volumes decrease.
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    An in-depth analysis of head-on crash severity and fatalities in Ghana
    (Cell Press, 2023) Adanu, Emmanuel Kofi; Agyemang, William; Lidbe, Abhay; Adarkwa, Offei; Jones, Steven; University of Alabama Tuscaloosa
    Head-on collisions are often linked to more serious injuries compared to other types of crashes, due to the intense impact they cause. In low-and middle-income countries, these collisions frequently involve high occupancy public transportation vehicles, leading to higher fatality rates per crash. Given the high risk of injury and potential for multiple casualties, this study delves into the factors influencing the outcomes of head-on crashes and the number of fatalities in Ghana. The study analyzed six years of historical head-on collision data from Ghana and developed two models to address the issue. The injury-severity analysis was performed using a random param-eter multinomial logit with heterogeneity in means and variances approach and aimed to identify the factors that have a significant impact on the severity of injuries sustained in head-on colli-sions, while the random parameters negative binomial fatality count model was designed to examine the factors that contribute to the number of fatalities in these crashes in the country. Results showed that head-on collisions with drivers over 65, buses, motorcycles, and those be-tween 25 and 65 years of age were more likely to result in fatalities. Speeding and vehicle malfunctions were also found to be significant contributing factors to fatal head-on collisions. Head-on crashes involving minibuses and incidents where the driver was attempting to overtake another vehicle were found to be more likely to result in a higher number of fatalities. The results of this study uncover an intriguing interaction between human-related elements and socioeco-nomic factors, which pose obstacles to the Government's endeavor to upgrade the major high-ways in the country. Additionally, the increasing need for transportation has led to the presence of vehicles on the roads that may not meet safety standards. Consequently, it is no surprise that several of the study's findings align with expectations. Nevertheless, within the specific context of Ghana, these findings furnish compelling data-driven evidence supporting the adoption and implementation of the safe systems approach as a means to tackle fatal head-on collisions in the country.
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    Severity analysis of crashes involving in-state and out-of-state large truck drivers in Alabama: A random parameter multinomial logit model with heterogeneity in means and variances
    (Elsevier, 2022) Okafor, Sunday; Adanu, Emmanuel Kofi; Jones, Steven; University of Alabama Tuscaloosa
    The trucking sector contributes significantly to the economic vitality of the United States. Large trucks are primarily used for transporting goods within and across states. Despite its economic importance, large truck crashes constitute public safety concerns. To minimize the consequences, there is a need to understand the factors that contribute to the severity outcomes of truck-involved crashes. Since many large truck drivers transport goods across several states, the driver-centered crash factors are expected to differ between in-state and out-of-state drivers. For this reason, this study developed two random parameters multinomial logit models with heterogeneity in means and variances to examine the factors contributing to the severity of crashes involving in-state and out-of-state large truck drivers in Alabama. The study was based on the 2016-2020 large truck crashes in Alabama. After data cleaning and preparation, it was observed that approximately 20% of in-state and 23% of out-ofstate large truck crashes were fatigue-related. There were more speeding related crashes (12.4%) among in-state large truck drivers, but the contribution of speeding to crash severity outcomes was only significant in the out-ofstate model. More crashes related to red light running violation (14.2%) were observed among out-of-state drivers, pointing to the fundamental issues of fatigue and unfamiliarity with the operations of signalized intersections in Alabama. The study contributes to the literature on large truck crashes by uncovering the nuances in crashes involving in-state and out-of-state large truck drivers. Despite the seeming similarity in factors that influence crash outcomes, this study provides the basis for truck drivers' training and communication campaigns on the differences that may exist in roadway characteristics from state to state. Also, policy formulations and strategies that prioritizes the well-being of the large truck drivers and creates a better working condition for them should be explored.