A lane change warning system is proposed, which gets the surrounding vehicle' motion states based on V2V communication. The safe distance between ego-vehicle and rear vehicle in target lane is analyzed according to the goal of both collision avoidance and vehicle following safety. Safe distance between ego-vehicle and front vehicle in target lane is analyzed to ensure safety in emergency collision avoidance. Safe distances between ego-vehicle and front and rear vehicles in original lane are analyzed to realize safe following. Meanwhile, driving style index is proposed to adapt the warning system to different kinds of drivers. Simulation results show that the lane change warning system can make a composite analysis of the collision risk during the lane-changing, and provide an accurate real-time warning to assist drivers. Index Terms-lane change warning, minimum safe distance, collision warning, V2V communication, driver assist system Manuscript received May 4th, 2014. Dang Ruina is with China North Vehicle Research Institute,
Model predictive control (MPC) is a popular technique for the development of active safety systems. However, its high computational cost prevents it from being implemented on lower-cost hardware. This paper presents a computationally efficient predictive controller for lane keeping assistance systems. The controller shares control with the driver, and applies a correction steering when there is a potential lane departure. Using the explicit feedback MPC, a multi-parametric nonlinear programming problem with a human-in-the-loop model and safety constraints is formulated. The cost function is chosen as the difference between the linear state feedback function to be determined and the resultant optimal control sequence of the MPC problem solved off-line given the current state. The piecewise linear feedback function is obtained by solving the parametric programming with an approximation approach. The effectiveness of the controller is evaluated through numerical simulations.
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