Driver models play a vital role in developing and verifying autonomous vehicles (AVs).
Previously, they were mainly applied in traffic flow simulation to model driver behavior. With …

In recent years, autonomous vehicles (AVs), which observe the driving environment and
lead a few or all of the driving tasks, have garnered tremendous success. The field of AVs …

The continuous advancement of connected and automated driving technologies has
garnered considerable public attention regarding the safety and reliability of automated …

Connected and Autonomous Vehicles (CAVs) are becoming a reality and are progressively
penetrating the markets level by level. CAVs are a promising solution for traffic safety …

Automated Vehicles (AVs) have a great potential to change transport fundamentally by
making it safer, by reducing travel time, and by increasing mobility and accessibility for all …

Autonomous vehicle (AV) technology has advanced rapidly in recent years with some
automated features already available in vehicles on the market. AVs are expected to reduce …

Testing any new safety technology of Autonomous Vehicles (AV) and Advanced Driver
Assistance Systems (ADAS) requires simulation-based validation and verification. The …

Several past studies showed that Autonomous Vehicles (AVs) can reduce crash risk, stop-
and-go traffic, and travel time. To analyze the safety benefits of AVs, most of the researchers …

A variety of simulation approaches based on automated driving technologies have been
proposed to develop traffic operations strategies to prevent traffic crashes and alleviate …

Driver models are crucial for the safety assessment of autonomous vehicles (AVs) because
of their role as reference models. Specifically, an AV is expected to achieve at least the …