Autor: Ksaibati, Khaled - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Investigating trends and characteristics of animal-vehicle crashes in Wyoming
Autorzy:: Roy, Uttara
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2141161.pdf
Data publikacji:: 2021
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: trends of animal-vehicle crashes
temporal patterns
crash characteristics
crash rates
Opis:: Animal-vehicle crashes (AVCs) are a severe concern in the United States as well as in Wyoming. This study investigated the current trends of AVCs and crash rate per vehicle miles traveled (VMT) for the State of Wyoming using police-reported crash data for ten years collected from the Wyoming Department of Transportation (WYDOT). The study also examined different driver, vehicular, roadway, and environmental conditions related factors that had a strong association with AVCs. The logistic regression model was developed to check how the factors prevalent in AVCs influence the severity of AVCs. The results showed that the percentage of AVCs to that of total crashes ranged from around 15% to 22%. Among different animals involved in crashes, the majority were deer. AVCs were found to have two peaks: dawn and dusk. AVC rate was found to be the highest in November. Also, dark and unlit conditions had a strong association with AVCs. Most of the AVCs tended to occur when there were no adverse weather conditions. When the speed limit was examined, it was found that the AVC crash rate tended to increase when the posted speed limit was higher than 60 mph. AVC rate was also higher when the road surface condition was dry. Higher posted speed limit, younger drivers, and dry road surface were also found to increase the severity of AVCs. The results identified in this study will be helpful to identify effective countermeasures to reduce AVCs in Wyoming.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2021, 6, 2; 25-42
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Automating the updated grade severity rating system (GSRS) using the Visual Basic.net programming language
Autorzy:: Ampadu, Vincent-Michael Kwesi
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2176016.pdf
Data publikacji:: 2022
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: updated GSRS
longitudinal downgrades
object-oriented programming
Visual Basic.net programming language
Opis:: 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 model through an interactive, intuitive, aesthetically appealing and user-friendly Visual Basic.net objected-oriented software to simplify the computation of the maximum safe descent speed on these downgrades based on the truck weight. The software provides functionality for both the continuous Slope and separate downgrade methods. The primary beneficiaries of this software will be the highway agencies who will be able to estimate the maximum safe speed of descent for trucks with various weight categories and hence produce Weight Specific Speed (WSS) signs for each downgrade or a multigrade section.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2022, 7, 2; 53--68
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Investigating snowplow-related injury severity along mountainous roadway in Wyoming
Autorzy:: Haq, Muhammad Tahmidul
Reza, Imran
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2204253.pdf
Data publikacji:: 2023
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: winter highway maintenance
snowplows
injury severity
mixed logit model
unobserved heterogeneity
Wyoming
environment
Opis:: Snow removal and deicing using snowplow trucks assist transportation agencies to enhance roadway safety and mobility. However, due to slower travel speeds during these operations, motorists often end up in crashes for poor visibility and disturbance of the snow. Despite the risk associated with snowplows, no previous study was found that exclusively investigate the factors associated with injury severity in snowplow-involved crashes. Therefore, this paper presents an extensive exploratory analysis and fills this knowledge gap by identifying the significant contributing factors affecting the occupant injury severity from the aspects of crashes with snowplow involvement. The study utilized eleven years (2010-2020) of historical snowplow-related crash data from Wyoming. Both the binary logit model and mixed binary logit model were developed to investigate the impacts of the various occupant, vehicle, crash, roadway, and environmental characteristics on the corresponding occupant injury severity. As one of the important findings from this research concludes that other vehicle drivers are more responsible than snowplow drivers contributing to more severe injuries in crashes involving snowplows. Recommendations suggested based on the modeling results are expected to help transportation agencies and policymakers take necessary actions in reducing snowplow-involved crashes by targeting appropriate strategies and proper resource allocation.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2023, 8, 1; 73--88
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Implementing safety toolkit on the Fort Peck Indian Reservation, Montana
Autorzy:: Nazneen, Sahima
Rezapour Mashhadi, Mahdi
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2141067.pdf
Data publikacji:: 2020
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: Indian reservation
crashes
tribes
crash injury
Opis:: Indian Reservations have suffered from high crash rates that lead to fatal and incapacitating injuries for years. Among numerous issues, resource gap, rustic nature of the reservations, cross jurisdictional issues, and scarce crash data, act as obstacles in an effort to reduce the number of these fatal and serious crashes. Numerous organizations have recognized the importance of addressing issues on Indian reservations and improving roadway safety. Wyoming Technology Transfer Center / Local Technical Assistance Program (WYT2/LTAP) center developed a safety toolkit for tribal communities to ascertain high-risk crash locations and determine the low-cost safety improvement countermeasures. This safety toolkit acts as a guideline providing information, field examples, and resources in key topic areas to improve roadway safety through the use of the five-step methodology from Wyoming Rural Road Safety Program. These steps included compiling and crash data analysis, level I field evaluation, combined ranking, level II field evaluation, and benefit-cost analysis. In this study, the safety toolkit was implemented on the Fort Peck Indian Reservation (FPIR), Montana, to provide the tribes with a real-life example. This study reveals that low-cost safety countermeasures have significant impacts in reducing the number of fatal and serious injury crashes on the FPIR. This methodology with slight modification can be applied to other Indian reservations or similar entities to improve roadway safety.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2020, 5, 1; 6-18
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Performance and cost-effectiveness of air disc brakes and air drum brakes for truck semi-trailers in different road and speed conditions
Autorzy:: Ampadu, Vincent-Michael Kwesi
Alrejjal, Anas
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2204251.pdf
Data publikacji:: 2023
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: GSRS
braking systems
grades
speeds
life cycle cost analysis
brake torque capacity
Opis:: This study uses TruckSim™ to model disc brakes and drum brakes on a fully loaded truck semi-trailer to study the performance of each brake type as downgrades and speeds vary. The brake performance is measured based on braking distance. A simplified economic comparison based on life cycle cost analysis to determine which road and vehicle conditions give rise to the cost-effectiveness of disc brakes is performed. The studies suggest that disc brakes shorten braking distances by 10-20%. They also suggest that the percentage reduction in braking distance as speed increases and downgrade gets steeper is approximately 12-19%. Evidence is provided that trucking companies operating their vehicles in steep terrain and at high speeds with disc brakes could benefit from 12-80% in long-term cost savings. Finally, at the societal level, by preventing crashes arising from rear-end collisions and runaway truck incidents, disc brakes save at least $649 million annually.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2023, 8, 1; 24--42
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: An assessment of machine learning and data balancing techniques for evaluating downgrade truck crash severity prediction in Wyoming
Autorzy:: Ampadu, Vincent-Michael Kwesi
Haq, Muhammad Tahmidul
Ksaibati, Khaled
Powiązania:: https://bibliotekanauki.pl/articles/2176018.pdf
Data publikacji:: 2022
Wydawca:: Fundacja Centrum Badań Socjologicznych
Tematy:: crash severity
performance
extreme gradient boosting tree
adaptive boosting tree
random forest
gradient boost decision tree
adaptive synthetic algorithm
Opis:: 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 truck crashes on Wyoming road networks. The accuracy of these seven methods was then compared. The Final ROC AUC score for the optimized random forest model is 95.296 %. The next highest performing model was the k-NN with 92.780 %, M.L.P. with 87.817 %, XGBoost with 86.542 %, Gradboost with 74.824 %, SVM with 72.648 % and AdaBoost with 67.232 %. Based on the analysis, the top 10 predictors of severity were obtained from the feature importance plot. These may be classified into whether safety equipment was used, whether airbags were deployed, the gender of the driver and whether alcohol was involved.
Źródło:: Journal of Sustainable Development of Transport and Logistics; 2022, 7, 2; 6--24
2520-2979
Pojawia się w:: Journal of Sustainable Development of Transport and Logistics
Dostawca treści:: Biblioteka Nauki

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