Multivehicle Cooperative Driving Using Cooperative Perception: Design and Experimental Validation

Kim, Seong-Woo; Qin, Bo; Chong, Zhuang Jie; Shen, Xiaotong; Liu, Wei; Ang, Marcelo H.; Frazzoli, Emilio; Rus, Daniela

doi:10.1109/tits.2014.2337316

Cited by 211 publications

(121 citation statements)

References 60 publications

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“…Many companies, such as Autotalks, Commsignia, Cohda Wireless, and Denso, are already selling their V2V communication devices at affordable prices to the mass market. Other wireless communication technologies, such as 3G, 4G and WiFi, are also suggested in [293][294][295].…”

Section: Vehicular Communicationmentioning

confidence: 99%

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Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed.

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Section: Vehicular Communicationmentioning

confidence: 99%

“…Since the vehicles are mobile and their locations are uncertain, their perception results may be "unaligned" or inconsistent. Map merging is proposed to align multiple local sensing maps so that the observations are consistent [294]. Nonetheless, transmitting a local sensing map uses substantial communication resources.…”

Section: Cooperative Localizationmentioning

confidence: 99%

Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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“…Cooperative perception is realized by exchanging sensor data between vehicles and Roadside Units (RSUs) and is necessary to widen or enhance the visibility area of HD maps [64], [65]. Sensors within a RSU mounted at a lamppost allow, due to the bird's eye view, a more accurate localization of objects.…”

Section: Scenario/use Cases and Requirementsmentioning

confidence: 99%

Where, When, and How mmWave is Used in 5G and Beyond

Sakaguchi

Haustein

Barbarossa

et al. 2017

IEICE Trans. Electron.

172

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SUMMARYWireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but also an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The first example is a 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang Winter Olympic Games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network (µ-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications. key words: millimeter wave, MEC, 28GHz, 60GHz, mesh network, V2V/V2X, automated driving, future forecast

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“…One example is cooperative perception [65,136]. By sharing images (LIDAR or camera) with neighboring vehicles, image processing algorithms could be applied to create satellite images of the surrounding traffic.…”

Section: Introductionmentioning

confidence: 99%