RMS: Real-time Motion Segmentation over the Internet of Vehicles

Lei Zhan1; Kai Hu1; Longhao Zou2; Zhenhui Yuan3; Gabriel-Miro Muntean4

10.1109/BMSB58369.2023.10211233

2023

2155-5044

979-8-3503-2153-1

2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

2023-June

1-7

14-16 June 2023

Beijing, China

In the context of autonomous driving, moving objects such as vehicles and pedestrians are of critical importance as they primarily influence the maneuvering and braking of cars. Unfortunately, due to the limited detection range of sensors, some distant and blocked objects cannot be detected, leading to slow responses when some unexpected situations occur during driving. To address this problem, a real-time motion segmentation multi-task model (RMS), running on an individual vehicle, is introduced to provide motion segmentation of moving objects within its field of view. RMS consists of a shared encoder, a multi-modal fusion module, and a dual decoder. An enhanced High Definition (HD) map constructed with the proposed RMS in line with the recommendations of the 3rd Generation Partnership Project (3GPP) Vehicle-to-everything (V2X) communication standard is produced. Extensive experiments demonstrate how RMS outperforms existing state-of-the-art motion segmentation methods in terms of multiple metrics, including mean Intersection over Union (mIoU). Additionally, Internet of Vehicles (IoV) simulation experiments show how the time required to update the map is better than the times achieved when using other methods.

autonomous driving motion segmentation HD map Internet of Vehicles

第一

EI

20233614670792

Digital television ; Maneuverability ; Motion analysis ; Object detection ; Vehicle to Everything ; Vehicle to vehicle communications

Highway Transportation:432 ; Radio Systems and Equipment:716.3 ; Television Systems and Equipment:716.4 ; Data Processing and Image Processing:723.2 ; Robot Applications:731.6

IEEE

1.Institue of Future Networks, Southern University of Science and Technology, Shenzhen, China
2.Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China
3.Department of Computer and Information Sciences, Northumbria University, Newcastle, UK
4.School of Electronic Engineering, Dublin City University, Dublin, Ireland

Lei Zhan,Kai Hu,Longhao Zou,et al. RMS: Real-time Motion Segmentation over the Internet of Vehicles[C],2023:1-7.