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 …

With the objective to improve road safety, the automotive industry is moving toward more
“intelligent” vehicles. One of the major challenges is to detect dangerous situations and react …

In this paper, we proposed a new risk assessment based decision-making algorithm to
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …

Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …

In this paper, we propose a decision-making framework for autonomous driving at road
intersections that determines appropriate maneuvers for an autonomous vehicle to navigate …

This paper presents a decision-making framework for automated driving in highway
environments. The framework is capable of reliably, robustly assessing a given highway …

Driving is a social activity which involves endless interactions with other agents on the road.
Failing to locate these agents and predict their possible future actions may result in serious …

This paper proposes an approach to automatically generating test cases for testing motion
controllers of autonomous vehicular systems. Test scenarios may consist of single or …

How to drive safely in complex real-world traffic settings has long been a question and
challenge for autonomous vehicles (AVs). Decision-making systems (DecSs) are the core of …

The estimation of risk is a central cornerstone in the evaluation of traffic scene situations for
intelligent ADAS. This applies to all levels of functions ranging from simple advices and …