Advanced Driver-Assistance Systems: Features Journey for Tomorrow
Shreyas Kankoriya1, Manoj kumar Khatal2
1Shreyas Kankoriya, Sn. Design Engineer, Department Chassis Engineering, Tata Technologies, Pune (Maharastra), India.
2Manoj Kumar Khatal, Project Manager, Department Chassis Engineering, Tata Technologies, Pune (Maharastra), India.
Manuscript received on 24 November 2023 | Revised Manuscript received on 11 January 2024 | Manuscript Accepted on 15 January 2024 | Manuscript published on 30 January 2024. | PP: 1-9 | Volume-11 Issue-1, January 2024 | Retrieval Number: 100.1/ijaent.E79680112524 | DOI: 10.35940/ijaent.E7968.11010124
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Intelligent associated vehicles (ICVs) are accepted to completely change people sooner rather than later by making the transportation more secure, cleaner and more agreeable. Albeit numerous models of ICVs have been created to demonstrate the idea of independent driving and the plausibility of further developing traffic effectiveness, there actually exists a critical hole prior to accomplishing large scale manufacturing of undeniable level ICVs. The goal of this study is to introduce an outline of both the cutting edge and future viewpoints of key necessary advances for future ICVs. It is a moving undertaking to survey every connected work and foresee their future viewpoints, particularly for such a perplexing and interdisciplinary area of examination. Advanced driver-assistance systems (ADASs) have become a salient feature for safety in modern vehicles. They are also a key underlying technology in emerging autonomous vehicles. State-of-the-art ADASs are primarily vision based, various type of features for ex. Lane Departure Warning (LDW), Blind Spot Monitoring (BSM), Forward Collision Warning (FCW), Automatic Emergency Braking (AEB), Traffic Sign Recognition, High Beam Assist, Rear Cross Traffic Alert, Driver Drowsiness Detection, Obstacle Aware Acceleration, Auto-steer etc. The paper aims at giving a complete picture focusing on the ADAS features for the user-friendly design of human-machine interfaces between driver and assistance system.
Keywords: Intelligent Connected Vehicles (ICVs), ADAS level, Lane Departure Warning (LDW), Forward Collision Warning (FCW), Driver Drowsiness Detection, and Obstacle Aware Acceleration.
Scope of the Article: Manufacturing IoT