相关论文: Collaborative Threat-Aware Autonomy (CTAA)

This paper addresses the challenge of navigating unmanned aerial vehicles in contested environments by introducing a cooperative multi-agent framework that increases the likelihood of safe UAV traversal. The approach involves two types of…

Active traffic management with autonomous vehicles offers the potential for reduced congestion and improved traffic flow. However, developing effective algorithms for real-world scenarios requires overcoming challenges related to…

In future intelligent transportation systems, autonomous cooperative planning (ACP), becomes a promising technique to increase the effectiveness and security of multi-vehicle interactions. However, multiple uncertainties cannot be fully…

Cooperative platooning, enabled by cooperative adaptive cruise control (CACC), is a cornerstone technology for connected automated vehicles (CAVs), offering significant improvements in safety, comfort, and traffic efficiency over…

Autonomous cooperative planning (ACP) is a promising technique to improve the efficiency and safety of multi-vehicle interactions for future intelligent transportation systems. However, realizing robust ACP is a challenge due to the…

Collaborative perception holds great promise for improving safety in autonomous driving, particularly in dense traffic where vehicles can share sensory information to overcome individual blind spots and extend awareness. However, deploying…

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…

Autonomous Vehicles (AVs) rely on individual perception systems to navigate safely. However, these systems face significant challenges in adverse weather conditions, complex road geometries, and dense traffic scenarios. Cooperative…

Connected and Autonomous Vehicles (CAVs) are transforming modern transportation by enabling cooperative applications such as vehicle platooning, where multiple vehicles travel in close formation to improve efficiency and safety. However,…

Multi-Agent Path-Finding (MAPF) focuses on the collaborative planning of paths for multiple agents within shared spaces, aiming for collision-free navigation. Conventional planning methods often overlook the presence of other agents, which…

This paper addresses a critical aerial defense challenge in contested airspace, involving three autonomous aerial vehicles -- a hostile drone (the pursuer), a high-value drone (the evader), and a protective drone (the defender). We present…

In this paper we address the problem of 'weaponeering', i.e., placing the weapon engagement zone (WEZ) of a vehicle on a moving target, while simultaneously avoiding the target's WEZ. A WEZ describes the lethality region of a range-limited…

Cooperative Adaptive Cruise Control (CACC) is one of the driving applications of vehicular ad-hoc networks (VANETs) and promises to bring more efficient and faster transportation through cooperative behavior between vehicles. In CACC,…

Multi-robot systems are integral to modern logistics, but their capabilities are often limited to tasks executable by individual agents. This paper addresses a critical gap in existing frameworks like Multi-Agent Path Finding (MAPF) and…

For an autonomous vehicle to operate reliably within real-world traffic scenarios, it is imperative to assess the repercussions of its prospective actions by anticipating the uncertain intentions exhibited by other participants in the…

We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisions and traffic jams.…

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,…

This paper addresses the problem of Multi-robot Coverage Path Planning (MCPP) for unknown environments in the presence of robot failures. Unexpected robot failures can seriously degrade the performance of a robot team and in extreme cases…

Communication technologies enable coordination among connected and autonomous vehicles (CAVs). However, it remains unclear how to utilize shared information to improve the safety and efficiency of the CAV system in dynamic and complicated…

Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current autonomous driving systems are mostly based on a single…