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Truck crashes on steep downgrades due to excessive brake heating, resulting from brake applications to control speeding, are a continuing cause of concern for the Wyoming Department of Transportation (WYDOT). In 2016, WYDOT funded a project to update the existing Grade Severity Rating System. Furthermore, in 2020, WYDOT commissioned a research project to automate the updated version of the mathematical...
Random parameter logit regression is used to analyze police-reported data on 8,253 heavy vehicle-related crashes in Addis Ababa between July 2014 and June 2017. The analysis shows that fatal crashes are more likely to occur during the day and on weekdays, particularly when the circulation of trucks is high. It also shows the disproportionately high involvement of young drivers in heavy vehicle crashes...
Pedestrian infrastructures are a critical part of the sustainable transportation system of a city across the world. The key risks to pedestrians are well documented, including infrastructure in terms of the lack of dedicated pedestrian facilities, such as sidewalks, crossings, and raised medians. This paper aimed to assess pedestrian infrastructures of the road transport system in Jimma city. The...
In highly competitive shipping market environment, container network operators-Freight forwarders, shipping companies etc. are concerned about design, development and deployment of optimized allocation model to achieve cost savings through improved container storage yard operations, crane productivity, outbound container allocation/distribution to seaport terminals and hence reduction in ships’ waiting...
This study is focused on the influence that artificial intelligence can bring on warehouse performance. A sample of 329 workers from selected warehouses was used for this study, and a self-administered questionnaire was used to collect data. An index was constructed using the Principal Component Analysis (PCA) method to measure the influence on warehouse performance. Mann Whitney U test and Kruskal-Wallis...
This study involved the investigation of various machine learning methods, including four classification tree-based ML models, namely the Adaptive Boosting tree, Random Forest, Gradient Boost Decision Tree, Extreme Gradient Boosting tree, and three non-tree-based ML models, namely Support Vector Machines, Multi-layer Perceptron and k-Nearest Neighbors for predicting the level of severity of large...
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