International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 11 | Nov 2024
p-ISSN: 2395-0072
www.irjet.net
“Arduino Uno or Raspberry Pi - Unravelling the Best in Advanced Driver Assistance Systems” Prerna Bharti1, Tanmay Band2, Prajwal Thorat3, Akansha Chauhan4 1Prerna Bharti, Dept. of Computer Engineering, Ajeenkya D Y Patil University, Pune, India
2Tanmay Band, Dept. of Mechanical Engineering, Ajeenkya D Y Patil University, Pune, India
3Prajwal Thorat, Dept. of Mechanical Engineering, Ajeenkya D Y Patil University, Pune, India 4Akansha Chauhan, Dept. of Computer Engineering, Ajeenkya D Y Patil University, Pune, India
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Abstract - This research paper explores the implementation of advanced driver assistance system (ADAS) features in a smallscale car model. The study focuses on the use of Arduino Uno and Raspberry Pi microcontrollers for integrating various ADAS functionalities such as, safe distance monitoring, obstacle avoidance, emergency braking, lane keep assist, and adaptive cruise control. The research outlines the components used in the project and discusses the successes and limitations encountered during the implementation process. Specifically, it highlights the challenges faced with the Arduino Uno boards and the decision to transition to Raspberry Pi for handling more complex ADAS features. The paper concludes with insights into the suitability of different microcontrollers for ADAS applications in small-scale models. Key Words: Advanced Driver Assistance System, Arduino Uno, Raspberry Pi, Microcontroller, Adaptive Cruise Control.
1.INTRODUCTION Advanced Driver Assistance Systems (ADAS) represent a transformative technology in the automotive industry, offering a suite of intelligent functionalities aimed at improving vehicle safety, enhancing driving experience, and reducing the likelihood of accidents. These systems utilize a combination of sensors, actuators, and control algorithms to provide real-time assistance to drivers, thereby mitigating risks associated with human error and environmental factors. In recent years, the integration of ADAS features has gained significant traction not only in full-scale vehicles but also in small-scale car models for educational, research, and prototyping purposes. The implementation of ADAS features in small-scale car models presents a unique set of challenges and opportunities. While scaled-down models lack the complexity and dynamics of full-sized vehicles, they provide a cost-effective platform for testing and validating ADAS functionalities in controlled environments. Moreover, small-scale models offer a practical means for students, researchers, and enthusiasts to gain hands-on experience with ADAS technology, fostering innovation and learning in the field of autonomous and semi-autonomous driving systems. The primary objective of this research is to explore the feasibility of integrating various ADAS functionalities into a small-scale car model using microcontrollers, specifically Arduino Uno and Raspberry Pi. These popular microcontroller platforms offer versatile programming capabilities and ease of use, making them ideal candidates for prototyping ADAS systems in miniature vehicles. By leveraging the capabilities of microcontrollers, we aim to replicate key ADAS features such as safe distance monitoring, obstacle avoidance, emergency braking, lane keep assist, and adaptive cruise control in our small-scale car model. The integration of ADAS features in small-scale car models holds immense educational value, providing students and enthusiasts with hands-on experience in sensor fusion, signal processing, control theory, and software development. Furthermore, it enables researchers to experiment with novel algorithms and techniques for enhancing the performance and robustness of ADAS systems in real-world scenarios. By building and testing a small-scale ADAS-equipped car model, we seek to bridge the gap between theory and practice, empowering individuals to gain insights into the complexities and challenges of autonomous driving technology. In this research, we focus on the implementation of ADAS functionalities using readily available components such as Arduino Uno boards, motor shields, sensors, and actuators. These components offer a cost-effective and accessible solution for constructing small-scale car models with ADAS capabilities. Through a systematic methodology, we integrate each ADAS feature into the car model, ensuring proper functionality and performance under various driving scenarios.
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