相关论文: Simulation of Obstruction Avoidance Generously Mob…
Geographic routing protocols greatly reduce the requirements of topology storage and provide flexibility in the accommodation of the dynamic behavior of mobile ad hoc networks. This paper presents performance evaluations and comparisons of…
This paper investigates a cooperative motion planning problem for large-scale connected autonomous vehicles (CAVs) under limited communications, which addresses the challenges of high communication and computing resource requirements. Our…
We present an innovative framework for traffic dynamics analysis using High-Order Evolving Graphs, designed to improve spatio-temporal representations in autonomous driving contexts. Our approach constructs temporal bidirectional bipartite…
As the traditional resources (frequency, time, space, etc.) are efficiently utilized, it becomes more and more challenging to satisfy the ever-lasting capacity-growing and users-boosting demand in wireless networks. Recently, the…
Integrating unmanned aerial vehicles (UAVs) and non-orthogonal multiple access (NOMA) technology can perform better in $5$G communication systems. To guarantee the fairness of communication services for the sensor nodes deployed in…
Automated optimization modeling (AOM) has evoked considerable interest with the rapid evolution of large language models (LLMs). Existing approaches predominantly rely on prompt engineering, utilizing meticulously designed expert response…
The continuous expansion of the urban construction scale has recently contributed to the demand for the dynamics of traffic intersections that are managed, making adaptive modellings become a hot topic. Existing deep learning methods are…
Data efficiency in robotic skill acquisition is crucial for operating robots in varied small-batch assembly settings. To operate in such environments, robots must have robust obstacle avoidance and versatile goal conditioning acquired from…
Mobile Ad-hoc Network is a temporary network which is the cooperative engagement of a collection of standalone mobile nodes that are not connected to any external network. It is a decentralized network where mobile nodes can be easily…
Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. Traditional techniques of routing are not well adapted. Indeed, their lack of reactivity with respect to the…
Urban transportation of next decade is expected to be disrupted by Autonomous Mobility on Demand (AMoD): AMoD providers will collect ride requests from users and will dispatch a fleet of autonomous vehicles to satisfy requests in the most…
Spatial division multiplexing using conventional orbital angular momentum (OAM) has become a well-known physical layer transmission method over the past decade. The mode-group (MG) superposed by specific single mode plane spiral OAM (PSOAM)…
Resource allocation is investigated for offloading computational-intensive tasks in multi-hop mobile edge computing (MEC) system. The envisioned system has both the cooperative access points (AP) with the computing capability and the MEC…
Trajectory prediction is fundamental to various intelligent technologies, such as autonomous driving and robotics. The motion prediction of pedestrians and vehicles helps emergency braking, reduces collisions, and improves traffic safety.…
The work proposes a new Combined Routing Protocol (CRP) for ad hoc networks that combines the benefits and annihilates the shortcomings of two well-known on-demand routing protocols in ad hoc networks: AODV (which provides a high…
Continuum mechanics simulators, numerically solving one or more partial differential equations, are essential tools in many areas of science and engineering, but their performance often limits application in practice. Recent modern machine…
This paper considers the problem of managing single or multiple robots and proposes a cloud-based robot fleet manager, Adaptive Goal Management (AGM) System, for teams of unmanned mobile robots. The AGM system uses an adaptive goal…
Traffic flow prediction is a typical spatio-temporal prediction problem and has a wide range of applications. The core challenge lies in modeling the underlying complex spatio-temporal dependencies. Various methods have been proposed, and…
Living in a complex world like ours makes it unacceptable that a practical implementation of a machine learning system assumes a closed world. Therefore, it is necessary for such a learning-based system in a real world environment, to be…
Reliable traversable area segmentation in unstructured environments is critical for planning and decision-making in autonomous driving. However, existing data-driven approaches often suffer from degraded segmentation performance in…