Abstract
For autonomous driving research, using a scaled vehicle platform is a viable alternative compared to a full-scale vehicle. However, using embedded solutions such as small robotic platforms with differential driving or radio-controlled (RC) car-based platforms can be limiting on, for example, sensor package restrictions or computing challenges. Furthermore, for a given controller, specialized expertise and abilities are necessary. To address such problems, this paper proposes a feasible solution, the Ridon vehicle, which is a spacious ride-on automobile with high-driving electric power and a custom-designed drive-by-wire system powered by a full-scale machine-learning-ready computer. The major objective of this paper is to provide a thorough and appropriate method for constructing a cost-effective platform with a drive-by-wire system and sensor packages so that machine-learning-based algorithms can be tested and deployed on a scaled vehicle. The proposed platform employs a modular and hierarchical software architecture, with microcontroller programs handling the low-level motor controls and a graphics processing unit (GPU)-powered laptop computer processing the higher and more sophisticated algorithms. The Ridon vehicle platform is validated by employing it in a deep-learning-based behavioral cloning study. The suggested platform’s affordability and adaptability would benefit broader research and the education community.
Highlights
Most automotive companies have moved their attention in recent years to the development of electric vehicles (EV), since they may give additional capabilities that may be very helpful in the future
It is clear that rapid advances in technology, such as sensors and computing platforms with artificial intelligence, have made autonomous vehicles (AV) a reality, and more attention has been paid in the research community to developing the systematic testing and evaluation of complex perception and control algorithms
This paper illustrates the design and transformation of a ride-on car equipped with various sensors with an affordable budget for testing autonomous vehicle algorithms and/or advanced driver assistance systems (ADAS) systems
Summary
Most automotive companies have moved their attention in recent years to the development of electric vehicles (EV), since they may give additional capabilities that may be very helpful in the future. The majority of the major established automotive businesses, as well as emerging technology players such as Tesla and Waymo, are focusing on the development of self-driving vehicles. It is clear that rapid advances in technology, such as sensors and computing platforms with artificial intelligence, have made autonomous vehicles (AV) a reality, and more attention has been paid in the research community to developing the systematic testing and evaluation of complex perception and control algorithms
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
