Research and Publications - Alabama Transportation Institute
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Browsing Research and Publications - Alabama Transportation Institute by Author "Adanu, Emmanuel Kofi"
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Item A low-cost approach to identify hazard curvature for local road networks using open-source data(Elsevier, 2021-06) Hu, Qinglin; Li, Xiaobing; Liu, Jun; Adanu, Emmanuel KofiVehicle crashes are a leading cause of death in the United States. Curvature in local roadways has been identified as one of the most significant factors that lead to fatal crashes. Given the large number of local roads and their relatively low traffic volume ‐ compared with interstates or freeways ‐ most local roads may not receive priorities in the first phase of highway upgrades, and critical locations, e.g., sharp curves (vertical and/or horizontal), in the network may be a deadly threat for both advanced autonomous vehicles and conventional vehicles. Furthermore, identifying local roadway curvatures presents various obstacles, such as high budgets and lack of survey data. To fill this gap, this study offers a low‐cost approach to constructing three‐dimensional geometric profiles for local roads in a relatively large study area using open‐source data. Given these profiles, critical road segments, including extreme horizontal and vertical curves and their combinations, can be identified. This study re‐classifies the local road segments into 20 sub‐categories based on the calculated vertical grades and curve radii and incorporates those segments into a zero‐inflated native binomial model for crash occurrence. Model results showed that grades or curves were associated with decreased crash frequency compared with straight and flat roads. However, segments with larger horizontal curve radii and low grades were found to be associated with increased crash frequency. Further implications are discussed in the paper.Item An Analysis of the Effects of Crash Factors and Precrash Actions on Side Impact Crashes at Unsignalized Intersections(Wiley, 2021) Adanu, Emmanuel Kofi; Li, Xiaobing; Liu, Jun; Jones, StevenAnnually, side impact crashes contribute to a significant proportion of road fatalities. These crashes typically occur as a result of traffic violations at intersections. This study contributes to efforts in addressing side impact crashes at unsignalized intersections by performing a path analysis to unravel some behavioral trajectories through which these crashes occur. The study further investigated how these behavioral pathways influence the severity of the crashes. Crashes that occurred at unsignalized four-way intersections and T-junctions in Alabama were used for model estimations. Three precrash actions, failed to yield right-of-way at the stop sign, failed to yield right-of-way at a turn, and running stop sign, were considered. +e model estimation results reveal that some of the crash factors were more associated with certain precrash factors but not others at either four-way intersections or T-junctions or both. It was observed that side impact crashes that occurred under daylight conditions at four-way intersections, for instance, were less likely to involve running a stop sign but more likely to involve failure to yield at the stop sign and failure to yield right-of-way at a turn, but under dark and unlit roadway conditions, the at-fault drivers were more likely to run a stop sign or fail to yield at a stop sign but less likely to be involved in failure to yield right-of-way at a turn. +is approach to injury severity analysis uncovers complex underlying relationships between precrash actions, other contributing factors, and crash outcomes.Item Effects of the autonomous vehicle crashes on public perception of the technology(Elsevier, 2021-06-01) Penmetsa, Praveena; Sheinidashtegol, Pezhman; Musaev, Aibek; Adanu, Emmanuel Kofi; Hudnall, MatthewIn March 2018, an Uber-pedestrian crash and a Tesla's Model X crash attracted a lot of media attention because the vehicles were operating under self-driving and autopilot mode respectively at the time of the crash. This study aims to conduct before-and-after sentiment analysis to examine how these two fatal crashes have affected people's perceptions of self-driving and autonomous vehicle technology using Twitter data. Five different and relevant keywords were used to extract tweets. Over 1.7 million tweets were found within 15 days before and after the incidents with the specific keywords, which were eventually analyzed in this study. The results indicate that after the two incidents, the negative tweets on “self-driving/autonomous” technology increased by 32 percentage points (from14% to 46%). The compound scores of “pedestrian crash”, “Uber”, and “Tesla” keywords saw a 6% decrease while “self-driving/autonomous” recorded the highest change with an 11% decrease. Before the Uber incident, 19% of the tweets on Uber were negative and 27% were positive. With the Uber-pedestrian crash, these percentages have changed to 30% negative and 23% positive. Overall, the negativity in the tweets and the percentage of negative tweets on self-driving/autonomous technology have increased after their involvement in fatal crashes. Providing opportunities to interact with this developing technology has shown to positively influence peoples' perception.Item Identification of factors associated with road crashes among functionally classified transport modes in Namibia(Elsevier, 2020-03) Adanu, Emmanuel Kofi; Jones, Steven; Odero, KennethNamibia, like other low- and middle-income countries, is facing a public health crisis from deaths and injuries attributable to road crashes. The crash fatality rate in Namibia was recently estimated to be 23.9 per 100,000 population. Such a high rate of road deaths exacts serious social and economic stress on many countries, hence the need to critically examine and understand factors driving this trend. This paper seeks to enhance the understanding of some underlying factors that influence road safety in Namibia and, by extension, serve as an illustrative example for an analysis of similar data within the context of other developing countries. A latent class multinomial logit model was estimated to examine factors that are associated with crashes involving different categories of vehicles commonly used in Namibia. The findings from this study provide evidence of crash contributing factors such as driver age, visibility constraints, rainfall effects, and characteristics of crash locations associated with different transport modes. In highlighting additional contributing factors related to roadway features and vehicle categories, this work forms the foundation of a Safe Systems approach towards addressing road crashes in Namibia and, other countries with similar road safety challenges.Item Incorporating systems thinking approach in a multilevel framework for human-centered crash analysis(Elsevier, 2019) Adanu, Emmanuel Kofi; Penmetsa, Praveena; Wood, Dustin; Jones, Steven L.Variations that exist in the frequency and severities of crashes across regions may be due to differences in road user behaviors or indirectly due to differences in regional characteristics. Regional strategies towards “vision zero” road fatalities, consisting of appropriate safety policies and laws, supported with public education and backed by appropriate sanctions, have the ability to shape road user behaviors in the long term. In this paper, certain human-centered crash factors are viewed as the outcome of a hierarchical system made up of road users nested in regions, in a way that regional characteristics like policies and punitive measures influence road user behaviors. Hence, we propose a multilevel framework that captures driver characteristics and regional attributes that directly and indirectly affect crash outcomes. The concept was applied to crash data analysis for the state of Alabama, where it was found that the probability of a fatal crash involving a typical driver is 0.115. About 6.19% of the variability in the fatal crash rate involving drivers from the state is accounted for by the city and 3.84% is accounted for by the county of residence of the causal driver, leaving 89.97% of the variability to be accounted for by driver attributes or other crash contributing factors. Fatal crash rates varied significantly across the state and some crash factors were more pronounced among drivers from particular cities and counties. In view of these findings, specific countermeasures and structural adjustments may be targeted in locations with the highest proportions of risky driver behaviors.Item Perceptions and expectations of autonomous vehicles – A snapshot of vulnerable road user opinion(Elsevier, 2019) Penmetsa, Praveena; Adanu, Emmanuel Kofi; Wood, Dustin; Wang, Teng; Jones, Steven L.Public perceptions play a crucial role in wider adoption of autonomous vehicles (AVs). This paper aims to make two contributions to the understanding of public attitudes toward AVs. First, we explore opinions regarding the perceived benefits and challenges of AVs among vulnerable road users – in particular, pedestrians and bicyclists. Second, the paper evaluated whether interaction experiences with AVs influence perceptions among vulnerable road users. To explore this, we examined survey data collected by Bike PGH, a Pittsburgh based organization involved in programs to promote safe mobility options for road users. Analysis of the data revealed that respondents with direct experience interacting with AVs reported significantly higher expectations of the safety benefits of the transition to AVs than respondents with no AV interaction experience. This finding did not differ across pedestrian and bicyclist respondents. The results of this study indicate that as the public increasingly interacts with AVs, their attitudes toward the technology are more likely to be positive. Thus, this study recommends that policy makers should provide the opportunities for the public to have interaction experience with AVs. The opportunities can be provided through legislation that allows auto manufacturers and technology industries to operate and test AVs on public roads. This interactive experience will positively affect people's perceptions and help in wider adoption of AV technology.Item Understanding the Factors That Are Associated with MotorcycleCrash Severity in Rural and Urban Areas of Ghana(Wiley, 2021-12-22) Agyemang, William; Adanu, Emmanuel Kofi; Jones, StevenLike many countries in sub-Saharan Africa, Ghana has witnessed an increase in the use of motorcycles for both commercial transport and private transport of people and goods. The rapid rise in commercial motorcycle activities has been attributed to the problem of urban traffic congestion and the general lack of reliable and affordable public transport in rural areas. This study investigates and compares factors that are associated with motorcycle crash injury outcomes in rural and urban areas of Ghana. This comparison is particularly important because the commercial use of motorcycles and their rapid growth in urban areas are a new phenomenon, in contrast to rural areas where people have long relied on motorcycles for their transportation needs. Preliminary analysis of the crash data revealed that more of the rural area crashes occurred under dark and unlit roadway conditions, while urban areas recorded more intersection-related crashes. Additionally, it was found that more pedestrian collisions happened in urban areas, while head-on collisions happened more in rural areas. The model estimation results show that collisions with a pedestrian, run-off-road, and collisions that occur under dark and unlit roadway conditions were more likely to result in fatal injury. Findings from this study are expected to help in crafting and targeting appropriate countermeasures to effectively reduce the occurrence and severity of motorcycle crashes throughout the country and, indeed, sub-Saharan Africa.Item Unintended Consequences of Automobility – Will Autonomous Vehicles be any Different?(Crimson Publishers, 2019-06-28) Adanu, Emmanuel Kofi; Jones, Steven