Advanced driver assistance system is an integral part in autonomous vehicle that not only assists the drivers to run the car smoothly but also enhances the safety of the passengers. This paper presents a smart machine for optimizing the performance of autonomous vehicles via the integration of multiple services and sensor information. Leveraging the strength of Raspberry Pi and Internet of Things (IoT), the machine activates users to visualize actual-time site visitors’ statistics to monitor and modify automobile velocity, with a focal point on minimizing traffic congestion and increasing protection. The system also consists of an emergency alert gadget designed to locate motive force drowsiness, tune alcohol intake, and screen injuries the use of a number of sensor information. By parsing and reading data from person sensors, together with GPS, alcohol, and vibration sensors, the gadget maximizes the efficiency of AI-primarily based self-riding cars. Sensor information is stored and analyzed on ThingSpeak server by MATLAB, supplying real-time valuable insights to the police and hospitals in case of accidents. This paper provides a detailed evaluation of the system’s layout and implementation, in addition to an assessment of its performance. The proposed system represents a practical answer for promoting secure riding practices even as lowering the incidents of accidents happening because of impulsive driving.