Author:
Bijalwan Jyotsna Ghildiyal,Singh Jagendra,Ravi Vinayakumar,Bijalwan Anchit,Alahmadi Tahani Jaser,Singh Prabhishek,Diwakar Manoj
Abstract
Introduction/Background
This study explores the limitations of conventional encryption in real-world communications due to resource constraints. Additionally, it delves into the integration of Deep Reinforcement Learning (DRL) in autonomous cars for trajectory management within Connected And Autonomous Vehicles (CAVs).
This study unveils the resource-constrained real-world communications, conventional encryption faces challenges that hinder its feasibility. This introduction sets the stage for exploring the integration of DRL in autonomous cars and the transformative potential of Blockchain technology in ensuring secure data transfer, especially within the dynamic landscape of the transportation industry.
Materials and Methods
The research methodology involves implementing DRL techniques for autonomous car trajectory management within the context of connected and autonomous CAVs. Additionally, a detailed exploration of Blockchain technology deployment, consensus procedures, and decentralized data storage mechanisms.
Results
Results showcase the impracticality of conventional encryption in resource-constrained real-world communications. Moreover, the implementation of DRL and Blockchain technology proves effective in optimizing autonomous car subsystems, reducing training costs, and establishing secure, globally accessible government-managed transportation for enhanced data integrity and accessibility.
Discussion
The discussion delves into the implications of the study's findings, emphasizing the transformative potential of DRL in optimizing autonomous car subsystems. Furthermore, it explores the broader implications of Blockchain technology in revolutionizing secure, decentralized data transfer within the transportation industry.
Conclusion
In conclusion, the study highlights the impracticality of conventional encryption in real-world communications and underscores the significant advancements facilitated by DRL in autonomous vehicle trajectory management. The integration of Blockchain technology not only ensures secure data transfer but also paves the way for a globally accessible transportation blockchain, reshaping the future landscape of the industry.
Publisher
Bentham Science Publishers Ltd.
Reference49 articles.
1. Chen T-M, Li Y, Zhao W.
Building a secure and trustworthy intelligent transportation system: A blockchain-based architecture and consensus mechanism design.
IEEE Trans Intell Transp Syst
2023;
25
(8)
: 5982-95.
2. Chinaei MH, Rashidi TH, Waller T.
Digitally transferable ownership of mobility-as-a-service systems using blockchain and smart contracts.
Transp Lett
2022;
15
(1)
: 54-61.
3. Chen M-Y, Wu H-T.
An automatic-identification-system-based vessel security system.
IEEE Trans Industr Inform
2023;
19
(1)
: 870-9.
4. Zhang C, Liu X, Zhang Y.
An attribute-based encryption scheme for secure and traceable data sharing in intelligent transportation systems.
Comput Secur
2023;
136
: 102924.
5. Habib K, Li Z, Rizvi SH.
Trustworthy intelligent transportation systems: A privacy-preserving and verifiable framework for data sharing.
IEEE Trans Vehicular Technol
2023;
72
(10)
: 10206-17.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献