Road safety is a very important problem in today’s transportation systems. Rear-end collisions are among the most frequent and dangerous accidents on highways and city streets. The paper proposes a MATLAB based simulation of an intelligent obstacle detection and autonomous lane changing system for collision avoidance. We consider a scenario where an ego vehicle drives on a two-lane road and continuously observes a slower vehicle in front and a fast-approaching vehicle in the adjacent lane. The system features front obstacle detection, blind spot monitoring, adaptive speed control, and smooth lane-change execution based on a rule-based decision-making algorithm. When the vehicle in front enters the pre-set detection range of 45 m, the system checks the side lane for safety before beginning an overtaking maneuver. In case of a detected speed-risk vehicle in the blind spot zone, the lane change is delayed, and a warning alert is issued. Simulation results show successful collision avoidance, safe gap maintenance, and smooth overtaking operations, validating the effectiveness of the system as a simplified Advanced Driver Assistance System (ADAS) prototype. Index Terms — Collision prevention, lane change, blind spot detection, ADAS, V2V communication, obstacle detection, MATLAB simulation.