Cooperative Intelligence for Autonomous Driving
CHENG Xiang1, DUAN Dongliang2, YANG Liuqing3, and ZHENG Nanning4
( 1. State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;
2. Department of Electrical and Computer Engineering, University of Wyoming, Laramie, WY 82071, USA.
3. Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523, USA;
4. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China
Autonomous driving is an emerging technology attracting interests from various sectors in recent years. Most of existing work treats autonomous vehicles as isolated individuals and has focused on developing separate intelligent modules. In this paper, we attempt to exploit the connectivity among vehicles and propose a systematic framework to develop autonomous driving techniques. We first introduce a general hierarchical information fusion framework for cooperative sensing to obtain global situational awareness for vehicles. Following this, a cooperative intelligence framework is proposed for autonomous driving systems. This general framework can guide the development of data collection, sharing and processing strategies to realize different intelligent functions in autonomous driving.
autonomous driving; cooperative intelligence; information fusion; vehicular communications and networking