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ZENODO
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Data sources: Datacite
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Dataset . 2020
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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https://doi.org/10.5281/zenodo...
Dataset . 2020
License: CC BY
Data sources: Sygma
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Livorno, Urban driving, pothole detection

Authors: AVR; CNIT; LINKS; TIM;

Livorno, Urban driving, pothole detection

Abstract

Scenario description: Test session for connected car detecting potholes using the combination of one or more of the following sensors: smartphone, 6LoWPAN vibration sensor, IMU. The information is sent to the cloud and can be sent back to other connected vehicles for warning. The information is also transmitted via V2V to AD cars that can automatically adapt the speed. Session description: Test session with only a connected car with 6LoWPAN based pothole detector, lap of 1,9 km on the harbour's public road. Goal is to record data for the technical evaluation. Datasets descriptions: AUTOPILOT_Livorno_UrbanDriving_Vehicle_all: Data generated from the vehicle sensors This dataset refers to the vehicle datasets generated from the vehicle sensors during Urban Driving in Livorno. This includes the data coming from the CAN bus and GPS. It includes following kind of dataset: Vehicle: general data (speed, battery); PositioningSystem: data from GPS; VehicleDynamics: data about dynamic (acceleration...); LateralControl: steering and lane control data AUTOPILOT_Livorno_UrbanDriving_V2X_all: V2V messages during platooning sessions This dataset refers to the V2V messages exchanged between ITS stations (vehicles and RSUs) during the Urban Drining in Livorno. AUTOPILOT_Livorno_UrbanDriving_IoT_all: Data extracted from IoT oneM2M platform This dataset refers to messages exchanged by Urban Driving devices, applications and services across the oneM2M platform.

Keywords

IoT, 6LoWPAN, oneM2M, Urban Driving, Road Hazards, Automated Driving

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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