Citation

Kavaiya, Sagar and Chauhan, Dharmendra and Chang, Yoong Choon and Alias, Mohamad Yusoff and Hai, Nguyen Tri and Phung, Bui Minh and Chauhan, Narendrakumar and Dalal, Purvang (2025) A Neuro-Evolutionary Framework for Enhancing Communication, Safety, and Decision-Making in Connected Car Ecosystems. Soft Computing and Its Engineering Applications, 2431. pp. 359-374. ISSN 1865-0929

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Abstract

The rapid development of connected car technology imposes vital requirements to develop adaptive and robust intelligent computational models to help enhance communication, safety, and autonomous decision-making for vehicles. This paper deals with how to incorporate neuro-evolutionary computing-the hybrid paradigm of neural networks and evolutionary algorithms-into the connected car ecosystem. We thus propose a holistic framework that harnesses the adaptive learning capabilities of neural networks and the optimization strengths of evolutionary algorithms to ensure optimal real-time decision-making processes for efficient traffic management and safe passage by passengers. The framework houses a multi-agent system, wherein every connected vehicle is an intelligent agent in itself-learning and evolving toward dynamic traffic surroundings. We present simulations and experimental results showing the effectiveness of our neuro-evolutionary approach to reduce communications latencies and lead to better optimization of routes through proactive collision avoidance. From these results, it is suggested that there exists significant promise for neuro-evolutionary computing to address computational challenges in connected car networks, paving the way to safe, resilient, and efficient intelligent transportation systems.

Item Type:	Article
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-484 Motor vehicles. Cycles
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	26 Jun 2025 06:26
Last Modified:	26 Jun 2025 06:26
URII:	http://shdl.mmu.edu.my/id/eprint/14088

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