From IEEE OJVT: Towards Safe Automated Driving

10 May, 2021 | Publications
Zongdian Li, Tao Yu, Ryuichi Fukatsu, Gia Khanh Tran, and Kei Sakaguchi
Full title: Toward Safe Automated Driving: Design of Software-Defined Dynamic MmWave V2X Networks and PoC Implementation

The technical exploration of safe automated driving has evolved from single-vehicle intelligence to vehicular networking. Therefore, to a certain extent, the safety requirements have been translated into the requirements for network performance.

Although Vehicle-to-Everything (V2X) communication technologies have developed over decades, from the Dedicated Short-Range Communication (DSRC) to the Long Term Evolution V2X (LTE-V2X), the introduction of millimeter wave (mmWave) in the 5G era will achieve an unprecedented leap in V2X performance by empowering multi-gigabit data transmission with ultra-low latency.

Meanwhile, the emergence of Software Defined Networking (SDN) enables centralized network management and allows flexible scheduling of communication resources to match V2X capacities. Their benefits for vehicular networks have been revealed by plenty of studies respectively. Nevertheless, no researchers investigate their combination to improve the safety of automated driving, especially lack of scalable prototype systems for proof-of-concepts (PoCs), not to mention the field test with real traffic.

In this paper, we firstly propose a novel architecture, i.e. software-defined dynamic mmWave V2X network, to support cooperative perception. And then, necessary hardware and software platforms are introduced to compose prototype systems. Step by step, we conduct PoCs from the indoors to the outdoors, which demonstrate the network functions, the prototype scalability and most importantly, the significant enhancement to the vehicle perception for safe automated driving.

Full Article: IEEE Open Journal of Vehicular Technology, January 2021

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