Abstract
The sensing coverage and accuracy of vehicles are vital for autonomous driving. However, the current sensing capability of a single autonomous vehicle is quite limited in the complicated road traffic environment, which leads to many sensing dead zones or frequent misdetection. In this paper, we propose to develop a Vehicular Fog Computing (VFC) architecture to implement cooperative sensing among multiple adjacent vehicles driving in the form of a platoon. Based on our VFC architecture greedy and Support Vector Machine (SVM) algorithms are adopted respectively to enhance the sensing coverage and accuracy in the platoon. Furthermore, the distributed deep learning is processed for trajectory prediction by applying the Light Gated Recurrent Unit (Li-GRU) neural network algorithm. Simulation results based on real-world traffic datasets indicate the sensing coverage and accuracy by the proposed algorithms can be significantly improved with low computational complexity.
Highlights
Autonomous driving has received wide attention from the academy and industry
Motivated by the above observations, we propose a new Vehicular Fog Computing (VFC) architecture and intelligent algorithms to perform cooperative sensing to improve the sensing coverage and accuracy of autonomous driving vehicles, as well as driving safety
In order to overcome the weakness of traditional VFC architecture, we proposed a new VFC architecture for cooperative sensing in a platoon, which can jointly utilize the sensing and the computational abilities of intelligent vehicles
Summary
Autonomous driving has received wide attention from the academy and industry. Benefiting from the high accuracy, small size and low cost of on-board sensors, the perception ability of intelligent vehicles can be highly improved, making autonomous driving safe and promising [1]. H. Du et al.: New VFC Architecture for Cooperative Sensing of Autonomous Driving among intelligent vehicles, the edge server (RSU) or remote cloud is required to assist the offloading scheduling in the existing VFC architecture. Motivated by the above observations, we propose a new VFC architecture and intelligent algorithms to perform cooperative sensing to improve the sensing coverage and accuracy of autonomous driving vehicles, as well as driving safety. In order to overcome the weakness of traditional VFC architecture, we proposed a new VFC architecture for cooperative sensing in a platoon, which can jointly utilize the sensing and the computational abilities of intelligent vehicles. This architecture takes full advantage of platoon driving.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
