GASPRO International Journal of Eminent Scholars

ABSTRACT

This study focused on the need for robots in handling real-world driving by discussing the strategies, benefits, challenges, and technological requirements involved in autonomous driving systems. The study explained that robotics and artificial intelligence have become important innovations in modern transportation because of the growing demand for safer, faster, and more efficient mobility systems. Real-world driving involves operating vehicles under normal traffic, weather, and road conditions, which often expose human drivers to errors caused by fatigue, distraction, and poor judgment. The study revealed that robotic driving systems equipped with artificial intelligence, machine learning, sensors, LiDAR, radar, and computer vision technologies can improve road safety, reduce traffic congestion, and enhance transportation efficiency through intelligent decision-making and continuous environmental monitoring. The study further identified important strategies for adopting robots in real-world driving, including sensor fusion, smart transportation infrastructure, testing and simulation, legal regulations, and public awareness programs. However, challenges such as cybersecurity threats, perception degradation, edge-case scenarios, and the black-box nature of deep learning systems were also identified as major limitations affecting the widespread adoption of autonomous vehicles. The study concluded that despite these challenges, continuous technological advancement, improved safety systems, and effective regulatory frameworks can support the successful integration of robotic systems into real-world driving environments for safer and more sustainable transportation systems. One of the recommendations made was that Governments and transportation authorities should invest more in smart road infrastructure, intelligent traffic systems, and vehicle-to-everything (V2X) communication technologies to support the effective operation of autonomous robotic vehicles in real-world driving environments.