Road departures remain a major cause of fatal accidents in passenger vehicles, especially on highways, driving the demand for robust and affordable active safety technologies. Conventional Road Departure Mitigation Systems (RDMS) typically depend on camera- or LiDAR-based sensing, which can be cost-prohibitive and challenging to integrate across diverse vehicle platforms. The available RDMS technologies in the market focuses on road departure detection, and lacks the mitigation strategy. Although existing RDMS solutions have enhanced vehicle safety, their dependency on expensive, specialized sensors limits broader adoption, particularly in cost-sensitive market segments. This study introduces a sensor-less, cost-effective RDMS technology which has two parts, detection and mitigation. The technology utilizes existing vehicle sensors accessed through vehicle CAN channels. A decision tree based logic algorithm processes key parameters such as vehicle speed, steering angle, yaw rate, and lateral acceleration to detect potential unintentional road departure events. Upon detection, the system initiates a two-stage mitigation strategy: a driver alert followed by automatic corrective steering through the Electric Power Assisted Steering (EPAS) system, ensuring the vehicle remains within lane boundaries. The proposed methodology has been validated both digitally and at vehicle level, demonstrating functional robustness across a variety of driving conditions. This approach offers a scalable, affordable, and easily deployable solution for enhancing vehicle safety without the need for additional hardware investments.