Implementation of an optimised autonomous Arduino-based car

Clio Vossou (), Ioanna Konstantinou and Dimitrios Koulocheris
Additional contact information
Clio Vossou: Vehicles Laboratory, National Technical University of Athens, Athens, Greece

Cognitive Sustainability, 2025, vol. 4, issue 2, 34-51

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.

Keywords: autonomous vehicle; sustainability; Arduino; ultrasound sensor; topology optimisation (search for similar items in EconPapers)
JEL-codes: L91 R41 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ojs.mtak.hu/index.php/CogSust/article/view/20507/16910 (application/pdf)
-

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bcy:issued:cognitivesustainability:v:4:y:2025:i:2:p:34-51

Ordering information: This journal article can be ordered from
https://www.CogSust.com/

DOI: 10.55343/CogSust.150

Access Statistics for this article

Cognitive Sustainability is currently edited by Prof. Mate ZOLDY

More articles in Cognitive Sustainability from Cognitive Sustainability Ltd.
Bibliographic data for series maintained by Prof. Mate ZOLDY ().