Vol. 2 No. 1 (2022): Journal of AI-Assisted Scientific Discovery
Articles

IoT-enabled Adaptive Traffic Management Systems for Autonomous Vehicles

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  • Dr. Cristina Mateos
Dr. Cristina Mateos
Professor of Human-Computer Interaction, Universidad Politécnica de Madrid (UPM), Spain
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Published 30-06-2022

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How to Cite

[1]
Dr. Cristina Mateos, “IoT-enabled Adaptive Traffic Management Systems for Autonomous Vehicles”, Journal of AI-Assisted Scientific Discovery, vol. 2, no. 1, pp. 64–85, Jun. 2022, Accessed: Nov. 25, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/67

Abstract

Previous research has indicated that as the level of vehicle automation increases, pedestrian and driver behavior changes; some of them in an unsafe way. These negative impacts can be explained mainly by the lack of understanding of new traffic dynamics and the unexpected conditions that drivers encounter while vehicles are driving autonomously. Because of this, it is important, in equal parts, to control the cyberphysical environment where these vehicles are operating and to ensure the full comprehension of the technological capabilities by end-users. These technological and end-user aspects are important for the design, implementation, performance validation of IoT's systems for a new generation of internet-based, intelligent, and adaptable AD vehicles. This work introduces an analysis about Adaptive Traffic Management Systems, TA - TMS, for autonomous vehicles. In particular, it will analyze cognitive traffic load, and its impact on users' perceived engagement, to facilitate the cybersecurity design interfaces.

The current and future generation of connected and automated driving (hereafter AD) vehicles have the ability to provide new and advanced services for citizens, businesses, and public stakeholders. Research and advanced technological developments in electric mobility, driving behavior, materials, the automotive industry supply chains, cybersecurity, and policies are factors that influence the global development of new vehicles and transportation systems. The improved potential of fully automated driving vehicles, combined with new information and communication technologies (ICT), and protocol models based on the Internet of Things (IoT) concept, will enable several new and advanced features, such as dynamic user customizations, collaboration between road users, and better management of resources, infrastructure, and the environment.

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References

  1. H. Huang, X. Zhu, and Y. Chen, "An Adaptive Traffic Light Control System Based on IoT for Smart Cities," 2016 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC), Singapore, 2016, pp. 1-6.
  2. S. Banerjee and S. Chattopadhyay, "IoT based Smart Traffic Management System," 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, India, 2016, pp. 1-6.
  3. D. Panda, S. Biswal, and D. Mishra, "Intelligent Traffic Management System Using IoT," 2017 International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, India, 2017, pp. 91-94.
  4. S. Patil and S. Malhotra, "Smart Traffic Management System using IoT," 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, 2017, pp. 1-5.
  5. N. S. Raje, S. R. Kharad, and A. B. Deshmukh, "IoT Based Smart Traffic Management System," 2017 International Conference on Inventive Systems and Control (ICISC), Coimbatore, India, 2017, pp. 1-5.
  6. R. R. Nambiar, R. Rajan, and A. M. Rajan, "Smart Traffic Management System Using IoT," 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT), Kollam, India, 2017, pp. 1-5.
  7. A. R. Thakare and P. B. Mhalgi, "IoT Based Smart Traffic Control System for Smart Cities," 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC), Mysuru, India, 2017, pp. 526-529.
  8. R. P. Kapoor, A. Khamparia, and A. S. Alvi, "IoT based Smart Traffic Management System," 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India, 2017, pp. 1-5.
  9. S. B. Akash, S. M. Qureshi, and A. Khan, "Smart Traffic Management System using IoT," 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, 2018, pp. 1572-1576.
  10. Tatineni, Sumanth. "Beyond Accuracy: Understanding Model Performance on SQuAD 2.0 Challenges." International Journal of Advanced Research in Engineering and Technology (IJARET) 10.1 (2019): 566-581.
  11. Shaik, Mahammad, et al. "Enhancing User Privacy in Decentralized Identity Management: A Comparative Analysis of Zero-Knowledge Proofs and Anonymization Techniques on Blockchain Infrastructures." Journal of Science & Technology1.1 (2020): 193-218.
  12. Vemoori, Vamsi. "Comparative Assessment of Technological Advancements in Autonomous Vehicles, Electric Vehicles, and Hybrid Vehicles vis-à-vis Manual Vehicles: A Multi-Criteria Analysis Considering Environmental Sustainability, Economic Feasibility, and Regulatory Frameworks." Journal of Artificial Intelligence Research 1.1 (2021): 66-98.
  13. S. K. Sahu, A. R. Das, and S. K. Jena, "IoT Based Smart Traffic Management System using Raspberry Pi," 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, 2018, pp. 243-246.
  14. Y. V. Deshpande, A. K. Shah, and S. M. V. Chaudhari, "Smart Traffic Management System Using IoT and Image Processing," 2018 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, India, 2018, pp. 191-196.
  15. V. Patil, S. Panhalkar, and P. Kharat, "IoT Based Smart Traffic Management System using Raspberry Pi," 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, India, 2018, pp. 2215-2220.
  16. S. D. Bhalerao, P. R. Deshmukh, and P. B. Mhalgi, "IoT Based Smart Traffic Management System for Smart Cities," 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2018, pp. 356-361.
  17. A. B. Muthukumar and R. S. Anand, "Smart Traffic Management System Using IoT," 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS), Bangalore, India, 2018, pp. 186-191.
  18. M. S. Patil, P. N. Patil, and A. B. Kadam, "IoT Based Smart Traffic Management System using Raspberry Pi," 2018 International Conference on Recent Trends in Electrical, Control and Communication (RTECC), Bangalore, India, 2018, pp. 1-5.
  19. V. A. Kulkarni, K. V. Sonavane, and S. G. Dhande, "Smart Traffic Management System using IoT," 2018 2nd International Conference for Convergence in Technology (I2CT), Pune, India, 2018, pp. 1-6.
  20. S. N. Jaiswal, S. H. Park, and N. Park, "IoT Based Smart Traffic Management System," 2018 International Conference on Computing, Power and Communication Technologies (GUCON), Noida, India, 2018, pp. 673-676.
  21. A. Patil, S. D. Kumbhar, and A. P. Patil, "Smart Traffic Management System using IoT," 2019 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2019, pp. 0257-0260.
  22. K. P. S. Chauhan, S. H. Pawar, and S. B. Rajput, "IoT Based Smart Traffic Management System," 2019 2nd International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2019, pp. 320-323.
  23. A. D. Kale, P. R. B. Patil, and R. G. Kulkarni, "Smart Traffic Management System using IoT," 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, 2019, pp. 29-33.