Embedded Automotive Systems: A Review of ADAS Technologies and Autonomous Driving Integration

Neha Jain

Neha Jain Student, Department of Electrical and Electronics Engineering, Jiwaji University, Gwalior, India

Abstract

Embedded automotive systems have revolutionized vehicle functionalities, enabling the transition from conventional driving to advanced driver assistance systems (ADAS) and ultimately toward autonomous driving. These systems rely on a combination of hardware, software, and intelligent algorithms to improve safety, efficiency, and comfort in modern vehicles. ADAS features such as adaptive cruise control, lane departure warning, automatic emergency braking, and parking assistance have significantly reduced accident rates and enhanced the driving experience. However, the path toward full autonomy requires advanced computing, robust sensor fusion, artificial intelligence (AI), and seamless integration of vehicle-to-everything (V2X) communication. This article provides an extensive review of embedded automotive systems, focusing on ADAS technologies, autonomous driving integration, key hardware and software components, challenges, and future directions.

References

Steckhan L, Spiessl W, Quetschlich N, Bengler K. Beyond SAE J3016: New design spaces for human-centered driving automation. InInternational Conference on Human-Computer Interaction 2022 Jun 16 (pp. 416- 434). Cham: Springer International Publishing.
2. Zainuddin Z, Akhir EA. Systematic Literature Review of Data Quality in Open Government Data: Trend, Methods, and Applications. IEEE Access. 2024 Oct 7.
3. Paden B, Čáp M, Yong SZ, Yershov D, Frazzoli E. A survey of motion planning and control techniques for self-driving urban vehicles. IEEE Transactions on intelligent vehicles. 2016 Mar;1(1):33-55.
4. Hossain MN, Rahim MA, Rahman MM, Ramasamy D. Artificial Intelligence Revolutionising the Automotive Sector: A Comprehensive Review of Current Insights, Challenges, and Future Scope. Computers, Materials & Continua. 2025 Mar 1;82(3).
5. Rizaldi A, Althoff M. Formalising traffic rules for accountability of autonomous vehicles. In2015 IEEE 18th international conference on intelligent transportation systems 2015 Sep 15 (pp. 1658-1665). IEEE.
6. Yeong DJ, Velasco-Hernandez G, Barry J, Walsh J. Sensor and sensor fusion technology in autonomous vehicles: A review. Sensors. 2021 Mar 18;21(6):2140.
7. Bendiab G, Hameurlaine A, Germanos G, Kolokotronis N, Shiaeles S. Autonomous vehicles security: Challenges and solutions using blockchain and artificial intelligence. IEEE Transactions on Intelligent Transportation Systems. 2023 Jan 20;24(4):3614-37.
8. Alahmed Y, Abadla R, Al Ansari MJ. Enhancing Safety in Autonomous Vehicles through Advanced AI-Driven Perception and Decision-Making Systems. In2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA) 2024 Sep 24 (pp. 208-217). IEEE.
9. Rajamani R. Vehicle dynamics and control. Springer Science & Business Media; 2011 Dec 21.
10. Bimbraw K. Autonomous cars: Past, present and future a review of the developments in the last century, the present scenario and the expected future of autonomous vehicle technology. In2015 12th international conference on informatics in control, automation and robotics (ICINCO) 2015 Jul 21 (Vol. 1, pp. 191-198). IEEE.
11. Anderson JM, Nidhi K, Stanley KD, Sorensen P, Samaras C, Oluwatola OA. Autonomous vehicle technology: A guide for policymakers. Rand Corporation; 2014 Jan 10.
12. Alfaifi YH. Recommender Systems Applications: Data Sources, Features, and Challenges. Information. 2024 Oct 21;15(10):660.

Ahmed HU, Huang Y, Lu P, Bridgelall R. Technology developments and impacts of connected and
autonomous vehicles: An overview. Smart Cities. 2022 Mar 17;5(1):382-404.
14. Thrun S. Toward robotic cars. Communications of the ACM. 2010 Apr 1;53(4):99-106.
15. Zhang J, Singh S. LOAM: Lidar odometry and mapping in real-time. InRobotics: Science and systems 2014 Jul 12 (Vol. 2, No. 9, pp. 1-9).
16. Geiger A, Lenz P, Urtasun R. Are we ready for autonomous driving? the kitti vision benchmark suite. In2012 IEEE conference on computer vision and pattern recognition 2012 Jun 16 (pp. 3354-3361). IEEE.
17. Sonko S, Etukudoh EA, Ibekwe KI, Ilojianya VI, Daudu CD. A comprehensive review of embedded systems in autonomous vehicles: Trends, challenges, and future directions. World Journal of Advanced Research and Reviews. 2024;21(1):2009-20.