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Review of Advanced Driver Assistance Systems and Their Applications for Collision Avoidance in Urban Driving Scenario

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Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) (ICMLBDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 256))

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Abstract

Automobile safety systems have become the most important area of research and development in today’s world. It is observed that due to increased population and heavy traffic, the number of on-road accidents are also increasing. According to the varied road safety reports, most road accidents occur be-cause of driving error, human behavior, traffic congestion and lane change over, etc. Advanced driver-assistance systems (ADAS) are mainly focusing on automating, and enhancing various vehicle related tasks to provide the better driving experience, which ultimately increases the safety of driver, passenger, and road users as well. The intelligent ADAS system takes appropriate measures to solve problems during transmission by providing automatic controls for varying the speed of the vehicle or stop it during emergency situations. This technique monitors distance between a moving-vehicles, obstacles, etc. With the advancements in technology, today’s cars are equipped with many advanced driver assistant systems, which play a significant role in detection of road-side objects including vehicles, cyclist, pedestrians, obstacles, etc. and assist the driver through the navigation. The ADAS system enables safe and comfortable driving, based on intelligent algorithms and sensor technology. ADAS together with a secure human-machine interface, increase both car safety as well as road safety. This paper primarily focusses upon reviewing ADAS and its applications for effective collision avoidance with road objects and users in urban driving scenario.

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Authors and Affiliations

  1. Research Center, E&TC Department, Pimpri Chinchwad College of Engineering Pune, Savitribai Phule Pune University, Pune, India

    Manish M. Narkhede & Nilkanth B. Chopade

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  1. Manish M. Narkhede
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  2. Nilkanth B. Chopade
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Editors and Affiliations

  1. Indian Institute of Technology Patna, Patna, India

    Rajiv Misra

  2. Indian Institute of Technology Bombay, Mumbai, India

    Rudrapatna K. Shyamasundar

  3. Indian Institute of Technology (BHU), Varanasi, India

    Amrita Chaturvedi

  4. Cardiff University, Cardiff, UK

    Rana Omer

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Narkhede, M.M., Chopade, N.B. (2022). Review of Advanced Driver Assistance Systems and Their Applications for Collision Avoidance in Urban Driving Scenario. In: Misra, R., Shyamasundar, R.K., Chaturvedi, A., Omer, R. (eds) Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021). ICMLBDA 2021. Lecture Notes in Networks and Systems, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-030-82469-3_23

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