As India is a rising country and the roads in India are developing rapidly one of the major challenges is to keep the reads safe and in proper condition. The objective of this study is to design and implementation of an “Autonomous Highway Surveillance Car” to operate without human intervention while continuously monitoring highway conditions in real time. The techniques like Robotics, embedded systems, machine learning, and Internet of Things (IoT) communication are integrated in this system to create an efficient road inspection solution. The vehicle is carrying an ultra- wide-angle camera that will capture road images continuously during movement. Then these images are processed using image processing techniques and trained machine learning models and identify road abnormalities such as potholes, surface damage, obstacles, and edge misalignment. As soon as the problem is detected, the system acquires its exact geographical location using a GPS module and then it sends the information to the concerned authorities through an IoT-based communication system for timely response and prompt action. Autonomous navigation is performed through multiple sensors, obstacle detection mechanisms, and basic path- planning algorithms, helping the vehicle to move safely along the highway without manual control. This system will drastically reduce the dependency on manual monitoring methods and improves response time for maintenance activities while reducing the error. Overall, the model demonstrates a practical, cost- effective, and scalable approach for intelligent highway surveillance and preventive road management.