Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

Every day, humans make hundreds of decisions, most of which are based on information we
gather from our surroundings. The majority of this perception when it comes to driving is …

Autonomous vehicle driving systems (AVDSs) have independent decision structures from
the users to manage and control the operations of the vehicles both in normal conditions …

Employing recent research results covering smart transportation systems, and building my
argument by drawing on data collected from AAA, Abraham et al.(2017), AUDI AG …

AI-based perception is a key factor towards the automation of driving systems. A conclusive
safety argumentation must provide evidence for safe functioning. Existing safety standards …

If not restricted by tolls, private decisions to drive on a highway result in inefficiently high
usage which leads to traffic jams. When traffic demand is high, traffic jams can occur simply …

The safety validation of automated vehicles is currently a major challenge, even though
substantial achievements have been made. The credibility of the results of conventional …

This study alms at the automatic understanding of pedestrians' car-hailing intention in traffic
scenes. Traffic scenes are highly complex, with a completely random spatial distribution of …

This review examines the utilization of Artificial Neural Networks (ANNs) in the analysis of
road crash data and their prospective contribution to autonomous vehicles. Artificial neural …

Assessing and encoding human driving expertise while handling challenging events,
primarily during drifts, can unveil new insights regarding the professional response to …