Millimeter-Wave V2V Communications with Cooperative Perception for Automated Driving

Fukatsu, Ryuichi; Sakaguchi, Kei

doi:10.1109/vtcspring.2019.8746344

Cited by 23 publications

(9 citation statements)

References 3 publications

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“…However, the recognition method did not consider the density of lasers from a LiDAR sensor, so that a vehicle would recognize an object even if many lasers were emitted on a very small area of the object. In [15], the minimum data rate required for safe overtaking was derived. However, safe overtaking was discussed only for comfortable braking.…”

Section: Related Workmentioning

confidence: 99%

Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking

Fukatsu

Sakaguchi

2021

Sensors

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The combination of onboard sensors on vehicles with wireless communication has great advantages over the conventional driving systems in terms of safety and reliability. This technique is often called cooperative perception. Cooperative perception is expected to compensate for blind spots in dynamic maps, which are caused by obstacles. Few blind spots in dynamic maps can improve the safety and reliability of driving thanks to the additional information beyond the sensing of the onboard sensors. In this paper, we analyzed the required sensor data rate to be exchanged for the cooperative perception in order to enable a new level of safe and reliable automated driving in overtaking scenario. The required sensor data rate was calculated by the combination of recognition and vehicle movement to adopt realistic assumptions. In the end of the paper, we compared the required sensor data rate with the outage data rate realized by the conventional V2V communication and millimeter-wave communication. The results showed the indispensability of millimeter-wave communications in automated driving systems.

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Section: Related Workmentioning

confidence: 99%

Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking

Fukatsu

Sakaguchi

2021

Sensors

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“…For a LiDAR-generated HD map, the total data volume collected for the duration of one hour is about 1 TB, which corresponds to a 2.2 Gbps data output [65]. The required data rate for cooperative perception is analyzed based on an overtaking scenario, which reveals that over 1 Gbps LiDAR information per is needed on V2V links to ensure safety for vehicle velocities above 70 km/h [66]. Hence, an estimation of 1 Gbps can be reasonably considered as the typical data rate requirement for exchanging HD information via V2X links.…”

Section: A Safety Requirementsmentioning

confidence: 99%

Towards Safe Automated Driving: Design of Software-Defined Dynamic MmWave V2X Networks and PoC Implementation

Tao

Fukatsu

et al. 2021

IEEE Open J. Veh. Technol.

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“…MmWave, in fact, allows big data transmissions at gigabit per second transmission rates which might support CAVs gathering nearly 1 GB of sensor data per second [2]. Thinking to cooperative perception, mmWave can also help to cope with accuracy degradation of position estimation, especially at high vehicle speed [7], [19]. Compared to the sub-6 GHz channels, however, mmWave bands suffer of higher propagation losses and attenuation [10].…”

Section: Millimeter Waves and Higher Frequenciesmentioning

confidence: 99%

How to deal with data hungry V2X applications?

Bazzi

Campolo

Masini

et al. 2020

Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Netw

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Current vehicular communication technologies were designed for a so-called phase 1, where cars needed to advise of their presence. Several projects, research activities and field tests have proved their effectiveness to this scope. But entering the phase 2, where awareness needs to be improved with non-connected objects and vulnerable road users, and even more with phases 3 and 4, where also coordination is foreseen, the spectrum scarcity becomes a critical issue. In this work, we provide an overview of various 5G and beyond solutions currently under investigation that will be needed to tackle the challenge. We first recall the undergoing activities at the access layer aimed to satisfy capacity and bandwidth demands. We then discuss the role that emerging networking paradigms can play to improve vehicular data dissemination, while preventing congestion and better exploiting resources. Finally, we give a look into edge computing and machine learning techniques that will be determinant to efficiently process and mine the massive amounts of sensor data.

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Millimeter-Wave V2V Communications with Cooperative Perception for Automated Driving

Cited by 23 publications

References 3 publications

Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking

Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking

Towards Safe Automated Driving: Design of Software-Defined Dynamic MmWave V2X Networks and PoC Implementation

How to deal with data hungry V2X applications?

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