Vehicle lane change behavior, which is an important part of traffic flow theory, can have a
fundamental impact on the macro and micro characteristics of traffic flow. At the same time, it …

Road traffic accidents are one of the world's most serious problems, as they result in
numerous fatalities and injuries, as well as economic losses each year. Assessing the …

In 2015, over 17% of pedestrians were killed during vehicle crashes in Hong Kong while it
raised to 18% from 2017 to 2019 and expected to be 25% in the upcoming decade. In Hong …

This study proposes a cellular automaton model incorporating the platoon size of connected
automated vehicles (CAVs) to examine their impact on mixed traffic flow. First, vehicles are …

This research focuses on improving the modelling of highly automated centralized traffic
management. Authors use a binary integer modelling for traffic flow optimization. One of the …

Crashes involving vulnerable road users (VRUs) are types of traffic accidents which take up
a large proportion and cause lots of casualties. With methods of statistics and accident …

The identification of causative factors and implementation of measures to mitigate work zone
crashes can significantly improve overall road safety. This study introduces a Self-Paced …

Traffic emission is one of the most severe issues in our modern societies. A large part of
emissions occurs in cities and especially at intersections due to the high interactions …

With the high frequency of highway accidents, studying how to use connected automated
vehicles (CAVs) to improve traffic efficiency and safety will become an important issue. In …

Traditional deep learning approaches for prediction of future trajectory of multiple road
agents rely on knowing information about their past trajectory. In contrast, this work utilizes …