Real-Time Data Analytics in Connected Vehicles: Enhancing Telematics Systems for Autonomous Driving and Intelligent Transportation Systems

Authors

  • Rajalakshmi Soundarapandiyan Elementalent Technologies, USA Author
  • Deepak Venkatachalam CVS Health, USA Author
  • Akila Selvaraj iQi Inc, USA Author

Keywords:

Real-time data analytics, connected vehicles

Abstract

Real-time data analytics guarantees safe, effective vehicle operation in autonomous driving and intelligent transportation systems as well as enhances telematics systems. Real-time data analytics in connected cars is covered in this paper along with the challenges and creative approaches to quickly manage vast volumes of data. Telematics systems handling vast sensor, communication network, and V2X data streams are required both for ITS and autonomous driving.
Connected automobiles provide rich LiDAR, radar, camera, and GPS data. Processing real-time data enhances car safety and decision-making. Connected cars reduce collisions, enhance cruise control, and use real-time data analytics to navigate. To negotiate complex driving situations and interact with other drivers, autonomous vehicles must rapidly and precisely grasp data.

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Published

01-01-2023

How to Cite

[1]
Rajalakshmi Soundarapandiyan, Deepak Venkatachalam, and Akila Selvaraj, “Real-Time Data Analytics in Connected Vehicles: Enhancing Telematics Systems for Autonomous Driving and Intelligent Transportation Systems”, Aus. J. of Machine Learning Res. & App., vol. 3, no. 1, pp. 420–460, Jan. 2023, Accessed: Mar. 14, 2025. [Online]. Available: https://ajmlra.org/index.php/publication/article/view/22