Related papers: MIT Advanced Vehicle Technology Study: Large-Scale…
Given the rapid advance in ITS technologies, future mobility is pointing to vehicular autonomy. However, there is still a long way before full automation, and human intervention is required. This work sheds light on understanding human…
Imitation learning is a promising approach for training autonomous vehicles (AV) to navigate complex traffic environments by mimicking expert driver behaviors. While existing imitation learning frameworks focus on leveraging expert…
With increasing automation in passenger vehicles, the study of safe and smooth occupant-vehicle interaction and control transitions is key. In this study, we focus on the development of contextual, semantically meaningful representations of…
A smart vehicle should be able to monitor the actions and behaviors of the human driver to provide critical warnings or intervene when necessary. Recent advancements in deep learning and computer vision have shown great promise in…
Autonomous driving is a multi-task problem requiring a deep understanding of the visual environment. End-to-end autonomous systems have attracted increasing interest as a method of learning to drive without exhaustively programming…
The capabilities of automated vehicles are advancing rapidly, yet achieving full autonomy remains a significant challenge, requiring ongoing human cognition in decision-making processes. Incorporating human cognition into control algorithms…
Autonomous Vehicle (AV) technology is advancing rapidly, promising a significant shift in road transportation safety and potentially resolving various complex transportation issues. With the increasing deployment of AVs by various…
With the growing technological advances in autonomous driving, the transport industry and research community seek to determine the impact that autonomous vehicles (AV) will have on consumers, as well as identify the different factors that…
Both assistant driving and self-driving have attracted a great amount of attention in the last few years. However, the majority of research efforts focus on safe driving; few research has been conducted on in-vehicle climate control, or…
Automated Vehicles (AVs) promise significant advances in transportation. Critical to these improvements is understanding AVs' longitudinal behavior, relying heavily on real-world trajectory data. Existing open-source trajectory datasets of…
Car-Following (CF), as a fundamental driving behaviour, has significant influences on the safety and efficiency of traffic flow. Investigating how human drivers react differently when following autonomous vs. human-driven vehicles (HV) is…
This paper presents a novel approach to Autonomous Vehicle (AV) control through the application of active inference, a theory derived from neuroscience that conceptualizes the brain as a predictive machine. Traditional autonomous driving…
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 autonomous vehicle (AV) control in the era of mixed…
The acquisition and analysis of high-quality sensor data constitute an essential requirement in shaping the development of fully autonomous driving systems. This process is indispensable for enhancing road safety and ensuring the…
Car-following is a control process in which a following vehicle (FV) adjusts its acceleration to keep a safe distance from the lead vehicle (LV). Recently, there has been a booming of data-driven models that enable more accurate modeling of…
Autonomous systems are becoming increasingly prevalent in new vehicles. Due to their environmental friendliness and their remarkable capability to significantly enhance road safety, these vehicles have gained widespread recognition and…
Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving. To overcome those complicated scenarios that rule-based methods could…
Safe and smooth interacting with other vehicles is one of the ultimate goals of driving automation. However, recent reports of demonstrative deployments of automated vehicles (AVs) indicate that AVs are still difficult to meet the…
Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or Advanced Driver Assistance Systems (ADAS), have the opportunity to improve energy savings. However, lower levels of…
Automated vehicles can change the society by improved safety, mobility and fuel efficiency. However, due to the higher cost and change in business model, over the coming decades, the highly automated vehicles likely will continue to…