As the necessity of location information closely related to everyday life has increased, the
use of global navigation satellite systems (GNSS) has gradually increased in populated …

The proliferation of compute-intensive services in next-generation vehicular networks will
impose an unprecedented computation demand to meet stringent latency and resource …

Future generation vehicles equipped with modern technologies will impose unprecedented
computational demand due to the wide adoption of compute-intensive services with …

Cellular vehicle-to-everything (V2X) communication is expected to herald the age of
autonomous vehicles in the coming years. With the integration of blockchain in such …

We propose an end-to-end machine learning model that integrates multi-task (MT) learning,
convolutional neural networks (CNNs), and control algorithms to achieve efficient inference …

Video object detection is a fundamental technology of intelligent video analytics for Internet
of Things (IoT) applications. However, even with extraordinary detection accuracy …

Accurate physical modeling of vehicle dynamics requires extensive a priori knowledge of the
studied vehicle. In contrast, data-driven modeling approaches require only a set of data that …

Multipath and non-line-of-sight (NLOS) signals are the major causes of poor accuracy of a
global navigation satellite system (GNSS) in urban areas. Despite the wide usage of the …

A comprehensive assessment of connected and automated driving is imperative before its
large-scale deployment in reality, which can be economically and effectively implemented …

Conventional infrared transparent materials, including inorganic ceramic, glass, and sulfur-
rich organic materials, are usually processed through thermal or mechanical progress. Here …