Introduction The emergence of automated machine learning or AutoML has raised an
interesting trend of no-code and low-code machine learning where most tasks in the …

Automated machine learning (AutoML) is a generic term for a specific approach to machine
learning (ML) area that tries to automate the end-to-end process of employing repetitive ML …

The modeling of distracted driving behavior has been studied for many years, however,
there remain many distraction phenomena that can not be fully modeled. This study …

Both driver inattention and driver distraction present significant challenges in road safety,
leading to an increasing number of accidents and fatalities every year. As drivers …

As the shared micromobility becomes a part of our daily life and environment, we expect the
number of low-speed modes for first-and-last mile trips to grow rapidly. The shared …

This study aims to quantify the resilience of the United States' domestic aviation network
during significant disruptions, with the COVID-19 pandemic as a case study. We apply an …

To conclude our study of the traffic conditions generated by commuters of the eastern contra
costa county to the western counties, firstly we will focus on the route options that these …

Comprehensive Review of Recent Advances in Transportation, Machine Learning, and
Infrastructure Management Ertan TUNCAL The chal Page 1 Comprehensive Review of Recent …

This article provides a comprehensive analysis of various research studies focusing on the
resilience of transportation networks, automated machine learning applications, congestion …

China is famous for its high-speed trains. The national network reached 35,000 km (22,000
mi) in total length, accounting for about two-thirds of the world's high-speed rail tracks in …