Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …

Decision-making and planning are the core aspects of autonomous driving systems. These
factors are crucial for improving the safety, driving experience, and travel efficiency of …

This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …

To address the safety and efficiency issues of vehicles at multi-lane merging zones, a
cooperative decision-making framework is designed for connected automated vehicles …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

Intersection management of Connected Autonomous Vehicles (CAVs) has the potential to
improve safety and mobility. CAVs approaching an intersection can exchange information …

This research conducts a comprehensive review on the social impacts of Cooperative
Automated Driving (CAD), including Infrastructure Enabled Autonomy (IEA). In order for …

To improve the safety and efficiency of the intelligent transportation system, particularly in
complex urban scenarios, in this paper a game theoretic decision-making framework is …

The rapid conceptual development and commercialization of connected automated vehicle
(CAV) has led to the problem of mixed traffic, ie, traffic mixed with CAVs and conventional …

Intersections are a major source of traffic delays and accidents within modern transportation
systems. Compared to signalized intersection management, autonomous intersection …