Implementation of an optimised autonomous Arduino-based car

Autonomous vehicles can be a key feature to sustainable mobility since they promise optimised routes, more efficient fuel consumption, safer road transport, and the ability to alter the perception of driving. This paper describes the implementation of a low-cost, self-navigating Arduino-based model car. The model car utilises an Arduino Uno mainboard. Four DC motors with their corresponding wheels are embedded in the model car to ensure its movement. Furthermore, the model car has an ultrasonic sensor to detect and avoid obstacles. Moreover, the model car hosts an action camera to record its environment, and more features may be added later for artificial cognition. Its chassis is designed and optimised to accommodate all the electronic components and ensure movement. Different versions of the chassis were fabricated using 3D printing technology. The performance of the model car was assessed while navigating in three different scenarios, during which the effect of the speed of the model car and the efficiency of its ultrasonic sensor were evaluated. The paper concludes with the topology optimisation of the chassis of the model car to optimise the chassis compliance and consequently improve the navigation characteristics of the model car.

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Publication Details

Journal
Cognitive Sustainability
Published
2025-06-30
DOI
https://doi.org/10.55343/cogsust.150
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28
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article

Implementation of an optimised autonomous Arduino-based car

Clio Vossou, Dimitrios Koulocheris, Ioanna Konstantinou
1 citations
Cognitive Sustainability
Robotic Path Planning Algorithms
1.28
article

Implementation of an optimised autonomous Arduino-based car

Clio Vossou, Dimitrios Koulocheris, Ioanna Konstantinou
article en
1 citations

Abstract

Autonomous vehicles can be a key feature to sustainable mobility since they promise optimised routes, more efficient fuel consumption, safer road transport, and the ability to alter the perception of driving. This paper describes the implementation of a low-cost, self-navigating Arduino-based model car. The model car utilises an Arduino Uno mainboard. Four DC motors with their corresponding wheels are embedded in the model car to ensure its movement. Furthermore, the model car has an ultrasonic sensor to detect and avoid obstacles. Moreover, the model car hosts an action camera to record its environment, and more features may be added later for artificial cognition. Its chassis is designed and optimised to accommodate all the electronic components and ensure movement. Different versions of the chassis were fabricated using 3D printing technology. The performance of the model car was assessed while navigating in three different scenarios, during which the effect of the speed of the model car and the efficiency of its ultrasonic sensor were evaluated. The paper concludes with the topology optimisation of the chassis of the model car to optimise the chassis compliance and consequently improve the navigation characteristics of the model car.

Cognitive SustainabilityVol. 4(2)
National Technical University of Athens (GR)
Openalex Percentile: Top 16%
Robotic Path Planning Algorithms
1.28
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Implementation of an optimised autonomous Arduino-based car — Clio Vossou, Dimitrios Koulocheris, et al. · Cognitive Sustainability (2025) | TGRS Research Map | TGRS