For mobile robots navigating on sidewalks, the ability to safely cross street intersections is
essential. Most existing approaches rely on the recognition of the traffic light signal to make …

Self-driving vehicles need to continuously analyse the driving scene, understand the
behavior of other road users and predict their future trajectories in order to plan a safe …

Car-following is the activity of safely driving behind a leading vehicle. Traditional
mathematical car-following models capture vehicle dynamics without considering human …

To navigate a complex urban environment, it is essential for autonomous vehicles to make
educated assumptions and accurate predictions of the movement of other traffic agents …

This paper provides a literature review of some of the most important concepts, techniques,
and methodologies used within autonomous car systems. Specifically, we focus on two …

Simulation is the key to scaling up validation and verification for robotic systems such as
autonomous vehicles. Despite advances in high-fidelity physics and sensor simulation, a …

We propose a nearby traffic flow modelling solution based on built-in Cyber-Physical System
(CPS) sensors of autonomous vehicles. Our goal is to enhance the offline route planning …

Connected and automated vehicles are expected to be at the core of future intelligent
transportation systems. One of the main practical challenges for self-driving vehicles on …

Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic
environment composed of human drivers and do not adapt to local conditions and socio …

We propose a multi-agent based computational framework for modeling decision-making
and strategic interaction at micro level for smart vehicles in a smart world. The concepts of …