Implementation of Real-Time Vehicle Rollover Prevention System

Vehicle Rollover Prevention/Warning Systems have recently been an important topic in Advanced Driver Assistance Systems (ADAS) of automotive electronics field. This paper will propose a rollover-prevention system implementation with vehicle dynamic model, video-detection technique and rollover index to help the driver avoid accidents as driving into a curve. Due to the reason that vehicle rollover motion analysis needs complicated computation and accurate parameters of vehicle stability in real time, in the first stage a vehicle dynamic model based on Extended Kalman Filter (EKF) algorithm is built, which can estimate vehicle roll/yaw motion in the curve by vehicle sensors. And then the image-based technique will be employed in detecting the front road curvature, and combined in the system to predict vehicle steering status. The final stage is to apply the vehicle rollover index with estimated vehicle motion to predict the dangerous level to drivers for warning. In the system validation, a Digital Signal Processor (DSP) with Microcontroller Unit (MCU) hardware structure is equipped and implemented in our vehicle experimental platform. The simulated and experimental results indicate that the proposed vehicle rollover prevention system can work properly and provide a driver an early warning to reduce the rollover accidents happening.