This paper endeavors to accomplish Level 4 and Level 5 self-driving by devising a design architecture for cloud-based self-driving vehicles. It incorporates a hybrid positioning navigation method [24, 25] and diverse sensing systems [9, 5, 7, 27] to capture precise environmental information, along with Inertial Measurement Unit (IMU) sensors and wheel odometry to complement other sensors and improve positioning accuracy and stability [26, 27, 25]. The architecture utilizes a combination of Vehicular Ad hoc Network (VANET), Internet of Vehicles (IoV), and in-vehicle millimeter wave systems for high-level information communication [9, 8]. To enable real-time monitoring, analysis, and application of vehicle data, the architecture leverages cloud computing, particularly the Amazon Web Services (AWS) platform [10, 11], and takes into account data security risks. The research in this paper is important for promoting the development of autonomous driving technology and provides valuable references for research and practical applications in related fields.
Enhancing Self-Driving Capabilities: A Design Architecture Leveraging Sensor Systems and Cloud Computing
2023-08-25
527726 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Enhancing Performance of Cloud Computing Data Center Networks by Hybrid Switching Architecture
British Library Online Contents | 2014
|Cloud Drive: A Computing Architecture for a Scalable Driving Safety Management System
British Library Conference Proceedings | 2011
|Leveraging Existing FAA Terminal Automation Systems for NextGen Terminal/Tower Capabilities
British Library Conference Proceedings | 2009
|Cloud Drive: A Computing Architecture for a Scalable Driving Safety Management System
Springer Verlag | 2011
|Architecture Design of Urban Intelligent Transportation Using Cloud Computing
Trans Tech Publications | 2012
|