Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …

Developing autonomous driving technologies necessitates addressing safety and cost
concerns. Both academic research and commercial applications of autonomous driving …

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

Metaverse and intelligent transportation system (ITS) are disruptive technologies that have
the potential to transform the current transportation system by decreasing traffic accidents …

Deep learning has been widely used in intelligent vehicle driving perception systems, such
as 3D object detection. One promising technique is Cooperative Perception, which …

● By March 25, our transaction has received a total of 619 original submissions. Our current
average number of submissions per day (SPD) rate is 7.37. Given this SPD, I would like to …

Reducing vehicle exhaust pollution and energy consumption is of great significance for
improving the sustainability of social development. Currently, most energy-efficient and …

Reliable and efficient validation technologies are critical for the recent development of multi-
vehicle cooperation and vehicle-road-cloud integration. In this paper, we introduce our …

As a key technology to alleviate urban congestion, Cooperative Adaptive Cruise Control
(CACC) requires testing and evaluation before being commercialized. To evaluate CACC …