相关论文: Representing Realistic Human Driver Behaviors usin…
Cooperative driving, enabled by Vehicle-to-Everything (V2X) communication, is expected to significantly contribute to the transportation system's safety and efficiency. Cooperative Adaptive Cruise Control (CACC), a major cooperative driving…
Data-driven Model Predictive Control (MPC), where the system model is learned from data with machine learning, has recently gained increasing interests in the control community. Gaussian Processes (GP), as a type of statistical models, are…
In this study, we explore an innovative approach to enhance cooperative driving in vehicle platooning systems through the use of vehicle-to-everything (V2X) communication technologies. As Connected and Autonomous Vehicles (CAVs) integrate…
Cellular Vehicle-to-Everything (C-V2X) technology promises to provide ultra-reliable low latency communication (URLLC) framework for connected vehicles. Connected vehicles can help us improve traffic safety, congestion and reduce fatal…
We investigate the capabilities and limitations of Gaussian process models by jointly exploring three complementary directions: (i) scalable and statistically efficient inference; (ii) flexible kernels; and (iii) objective functions for…
As we move towards autonomous vehicles, a reliable Vehicle-to-Everything (V2X) communication framework becomes of paramount importance. In this paper we present the development and the performance evaluation of a real-world vehicular…
Ultra-reliable low-latency Vehicle-to-Everything (V2X) communications are needed to meet the extreme requirements of enhanced driving applications. Millimeter-Wave (24.25-52.6 GHz) or sub-THz (>100 GHz) V2X communications are a viable…
In this paper, we present the downlink coverage and rate analysis of a cellular vehicle-to-everything (C-V2X) communication network where the locations of vehicular nodes and road side units (RSUs) are modeled as Cox processes driven by a…
Gaussian processes (GPs) are ubiquitous tools for modeling and predicting continuous processes in physical and engineering sciences. This is partly due to the fact that one may employ a Gaussian process as an interpolator while facilitating…
Credible microscopic traffic simulation requires car-following models that capture both the average response and the substantial variability observed across drivers and situations. However, most data-driven calibrations remain…
The 3rd Generation Partnership Project (3GPP) defines the first specifications for cellular-based vehicle-to-everything (C-V2X) communications in Release 14. C-V2X extends LTE's device-to-device communication modes by adding two new modes…
As the realization of vehicular communication such as vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) is imperative for the autonomous driving cars, the understanding of realistic vehicle-to-everything (V2X) models is needed.…
Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-time predictions due to its cubic time cost in the data size.…
Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-time predictions due to its cubic time cost in the data size.…
In this paper, performance of an Integrated Sensing and Communication (ISAC) Vehicle-to-Everything (V2X) scenario is evaluated, in which a vehicle simultaneously detects the next vehicle ahead while receiving a communication signal from a…
Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty quantification accuracy, and customizability persists. This is because the vast majority of…
Modeling car-following behavior is fundamental to microscopic traffic simulation, yet traditional deterministic models often fail to capture the full extent of variability and unpredictability in human driving. While many modern approaches…
Data-driven paradigms are well-known and salient demands of future wireless communication. Empowered by big data and machine learning, next-generation data-driven communication systems will be intelligent with the characteristics of…
Vehicular communications are the key enabler of traffic reduction and road safety improvement referred to as cellular vehicle-to-everything (C-V2X) communications. Considering the numerous transmitting entities in next generation cellular…
The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities. These can enable proactive decisions and actions from wireless-network components to sustain quality-of-service…