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Authors: Giuseppe Parrotta ; Mauro Tropea and Floriano De Rango

Affiliation: DIMES Department, University of Calabria, via P. Bucci 39c, 87036 Rende (CS), Italy

Keyword(s): Autonomous Vehicles, Autonomous Guide, Computer Vision, Interpolation Technique, Machine Learning.

Abstract: Autonomous vehicle (AV) is a kind of intelligent car, which is mainly based on the computer and sensor system inside the car to realize driverless guide. The AVs are cars that recognize the driving environment without human intervention, assess the risk, plan the driving route and operate on their own. These vehicles are integrated with a series of sensors and other devices and software like automatic control, artificial intelligence, visual computing in order to be able to perform driving inside a road. Calculate the correct distance between vehicle and objects inside its trajectory is important to allow an autonomous guide in safety. So, in this paper we describe our proposal of predicting this distance in a real scenario through an on-board camera and with the support of rover, arm platforms and sensors. The proposal is to use an interpolation technique that permits to predict distance with a good accuracy.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Parrotta, G.; Tropea, M. and De Rango, F. (2022). A Computer Vision Approach to Predict Distance in an Autonomous Vehicle Environment. In Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH; ISBN 978-989-758-578-4; ISSN 2184-2841, SciTePress, pages 348-355. DOI: 10.5220/0011318400003274

@conference{simultech22,
author={Giuseppe Parrotta. and Mauro Tropea. and Floriano {De Rango}.},
title={A Computer Vision Approach to Predict Distance in an Autonomous Vehicle Environment},
booktitle={Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH},
year={2022},
pages={348-355},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011318400003274},
isbn={978-989-758-578-4},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH
TI - A Computer Vision Approach to Predict Distance in an Autonomous Vehicle Environment
SN - 978-989-758-578-4
IS - 2184-2841
AU - Parrotta, G.
AU - Tropea, M.
AU - De Rango, F.
PY - 2022
SP - 348
EP - 355
DO - 10.5220/0011318400003274
PB - SciTePress