<p>With the popularization and development of intelligent driving, driving safety is becoming increasingly important. Driver monitoring can timely detect safety hazards and provide warnings, which is an important method to improve driving safety. Since the driver's gaze is a crucial aspect of driver monitoring, determining the driver’s gaze in 3D space has become very important. This paper proposes a 3D spatial eye tracking method based on a single camera with a single light source and applies it to a driver monitoring scenario to design and develop a prototype system based on eye tracking for driver monitoring. The system uses a SVM classifier to classify the driver’s intentions and gives the driver a voice warning based on the classification results to avoid possible hazards and improve driving safety. In the experiment, the proposed 3D spatial eye tracking method achieved horizontal and vertical error accuracy of 1.69° and 1.60° respectively. Moreover, the designed driver monitoring system achieved 76% accuracy in recognizing incorrect driving intentions and providing warnings, which proves that the system can improve driving safety through early warnings.</p>