A Grid-Based Framework for Collective Perception in Autonomous Vehicles
Centre for Automation and Robotics (CSIC-UPM), Ctra. M300 Campo Real, Km 0.200, Arganda del Rey, 28500 Madrid, Spain
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Academic Editor: Miguel Sepulcre
Sensors 2021, 21(3), 744; https://doi.org/10.3390/s21030744
Received: 22 December 2020
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Revised: 15 January 2021
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Accepted: 19 January 2021
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Published: 22 January 2021
(This article belongs to the Special Issue Cooperative Perception for Intelligent Vehicles)
Today, perception solutions for Automated Vehicles rely on sensors on board the vehicle, which are limited by the line of sight and occlusions caused by any other elements on the road. As an alternative, Vehicle-to-Everything (V2X) communications allow vehicles to cooperate and enhance their perception capabilities. Besides announcing its own presence and intentions, services such as Collective Perception (CPS) aim to share information about perceived objects as a high-level description. This work proposes a perception framework for fusing information from on-board sensors and data received via CPS messages (CPM). To that end, the environment is modeled using an occupancy grid where occupied, and free and uncertain space is considered. For each sensor, including V2X, independent grids are calculated from sensor measurements and uncertainties and then fused in terms of both occupancy and confidence. Moreover, the implementation of a Particle Filter allows the evolution of cell occupancy from one step to the next, allowing for object tracking. The proposed framework was validated on a set of experiments using real vehicles and infrastructure sensors for sensing static and dynamic objects. Results showed a good performance even under important uncertainties and delays, hence validating the viability of the proposed framework for Collective Perception.
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Keywords:
autonomous driving; connected vehicles; cooperative perception; collective perception service; V2X; occupancy grid
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MDPI and ACS Style
Godoy, J.; Jiménez, V.; Artuñedo, A.; Villagra, J. A Grid-Based Framework for Collective Perception in Autonomous Vehicles. Sensors 2021, 21, 744. https://doi.org/10.3390/s21030744
AMA Style
Godoy J, Jiménez V, Artuñedo A, Villagra J. A Grid-Based Framework for Collective Perception in Autonomous Vehicles. Sensors. 2021; 21(3):744. https://doi.org/10.3390/s21030744
Chicago/Turabian StyleGodoy, Jorge, Víctor Jiménez, Antonio Artuñedo, and Jorge Villagra. 2021. "A Grid-Based Framework for Collective Perception in Autonomous Vehicles" Sensors 21, no. 3: 744. https://doi.org/10.3390/s21030744
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