Connected and automated vehicle technologies are widely expected to revolutionize
transport systems, enhancing the mobility and quality of life while reducing the …

With an increasing number of automated vehicles (AV) appearing on roads and interacting
with conventional traffic, there is a need for improved simulation approaches to replicate and …

Modeling, prediction, and evaluation of personalized driving behaviors are crucial to
emerging advanced driver-assistance systems (ADAS) that require a large amount of …

This research aims to model system dynamics for mixed traffic flow consisting of Connected
and Automated Vehicles (CAVs) and Human-driven Vehicles (HVs). It quantifies the impact …

The area of traffic flow modelling and analysis that bridges civil engineering, computer
science, and mathematics has gained significant momentum in the urban areas due to …

Automated driving may lead to much higher road capacities, combined with increased road
safety, increased driver comfort, and lower costs. Although this vision may hold ground in the …

The gradual deployment of automated vehicles on the existing road network will lead to a
long transition period in which vehicles at different driving automation levels and capabilities …

In the foreseeable future, connected vehicles (CVs) will coexist with traditional vehicles
(TVs) resulting in a complex mixed traffic environment and the success of CVs will depend …

With the popularization of autonomous vehicle (AV) technology, mixed traffic flows that
consist of AVs and human‐driven vehicles (HDVs) will appear in the real world. Although …

The macroscopic evaluation of road traffic characteristics is vital as they will alter
significantly with the emergence of Connected and Autonomous Vehicles (CAVs). The …