Trailer-mounted radar extends rear field of view blocked by a towed trailer, reducing interference and improving object detection for driver assistance.
Temporary excitation acceleration updates vehicle mass and handling estimates from sensor data, helping ADAS adapt to changing conditions.
Using level-sensor motion and a suspension-damping model, this case estimates vehicle payload mass more accurately during movement.
Driver trajectory prediction and risk evaluation shift control weight between human and automation to preserve safe intervention in intelligent vehicles.
A self-supervised RNN replaces manual MPC tuning by adapting vehicle control to unknown road friction, tire wear, and new actuators.
By predicting actuator limits and converting them into acceleration bounds, the planner avoids non-executable trajectories and controller windup.