No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

In this paper, we propose a deep learning based vehicle trajectory prediction technique
which can generate the future trajectory sequence of surrounding vehicles in real time. We …

The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …

Ensuring the safety of fully autonomous vehicles requires a multi-disciplinary approach
across all the levels of functional hierarchy, from hardware fault tolerance, to resilient …

In this paper, we propose an efficient vehicle trajectory prediction framework based on
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …

Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …

Accurately discovering hazards and issuing appropriate warnings to drivers in advance or
performing autonomous control is the core of the Collision Avoidance (CA) system used to …

Driving Behavior (DB) is a complex concept describing how the driver operates the vehicle
in the context of the driving scene and surrounding environment. Recently, DB assessment …