Related papers: Accuracy-Aware Cooperative Sensing and Computing f…
Cooperative Adaptive Cruise Control (CACC) is an autonomous vehicle-following technology that allows groups of vehicles on the highway to form in tightly-coupled platoons. This is accomplished by exchanging inter-vehicle data through…
Perception plays a central role in connected and autonomous vehicles (CAVs), underpinning not only conventional modular driving stacks, but also cooperative perception systems and recent end-to-end driving models. While deep learning has…
In the last few years, robotic technology has been increasingly employed in agriculture to develop intelligent vehicles that can improve productivity and competitiveness. Accurate and robust environmental perception is a critical…
The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technology has enormous potential for improving efficiency and safety…
Coordination among connected and autonomous vehicles (CAVs) is advancing due to developments in control and communication technologies. However, much of the current work is based on oversimplified and unrealistic task-specific assumptions,…
Autonomous vehicles use multiple sensors, large deep-learning models, and powerful hardware platforms to perceive the environment and navigate safely. In many contexts, some sensing modalities negatively impact perception while increasing…
Autonomous Vehicles (AVs) use multiple sensors to gather information about their surroundings. By sharing sensor data between Connected Autonomous Vehicles (CAVs), the safety and reliability of these vehicles can be improved through a…
Deriving optimal control strategies for coordination of connected and automated vehicles (CAVs) often requires re-evaluating the strategies in order to respond to unexpected changes in the presence of disturbances and uncertainties. In this…
Cooperative perception has been widely used in autonomous driving to alleviate the inherent limitation of single automated vehicle perception. To enable cooperation, vehicle-to-vehicle (V2V) communication plays an indispensable role. This…
Cooperative perception is challenging for safety-critical autonomous driving applications.The errors in the shared position and pose cause an inaccurate relative transform estimation and disrupt the robust mapping of the Ego vehicle. We…
This paper addresses the joint optimization of trajectories and bandwidth allocation for multiple Unmanned Aerial Vehicles (UAVs) to enhance energy efficiency in the cooperative data collection problem. We focus on an important yet…
This paper investigates underwater cooperative target detection using autonomous underwater vehicles (AUVs), with a focus on the critical trade-off between cooperation efficiency and communication covertness. To tackle this challenge, we…
Connected and autonomous vehicles (CAVs) are promising due to their potential safety and efficiency benefits and have attracted massive investment and interest from government agencies, industry, and academia. With more computing and…
Safe overtaking, especially in a bidirectional mixed-traffic setting, remains a key challenge for Connected Autonomous Vehicles (CAVs). The presence of human-driven vehicles (HDVs), behavior unpredictability, and blind spots resulting from…
In this work, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal offloading) via V2V communication, in order to increase the…
Cooperative perception between vehicles is poised to offer robust and reliable scene understanding. Recently, we are witnessing experimental systems research building testbeds that share raw spatial sensor data for cooperative perception.…
Accurate positioning is known to be a fundamental requirement for the deployment of Connected Automated Vehicles (CAVs). To meet this need, a new emerging trend is represented by cooperative methods where vehicles fuse information coming…
Connected and Automated Vehicles (CAVs) offer significant potential for improving energy efficiency and lowering vehicle emissions through eco-driving technologies. Control algorithms in CAVs leverage look-ahead route information and…
Environmental perception in Automated Valet Parking (AVP) has been a challenging task due to severe occlusions in parking garages. Although Collaborative Perception (CP) can be applied to broaden the field of view of connected vehicles, the…
Due to the complexity of the natural world, a programmer cannot foresee all possible situations, a connected and autonomous vehicle (CAV) will face during its operation, and hence, CAVs will need to learn to make decisions autonomously. Due…