モデルベースのトレーラー揺れ抑制による自動運転乗用車の安定化

原文アブストラクト

Trailer sway is a persistent contributor to severe crashes among light passenger vehicles towing trailers, yet it remains largely unaddressed by the autonomous vehicle systems now entering this new era of automation. Improper cargo placement rearward of the trailer axle reduces, and can invert, the tongue load transmitted through the hitch. The resulting loss of vertical load at the tow vehicle's rear axle diminishes the lateral tire force available there and degrades yaw stability of the coupled system, admitting a divergent lateral oscillation of the trailer known as trailer sway. Under adverse combinations of speed and loading, this oscillation can progress to jackknifing, in which the articulation angle diverges rapidly and directional control is lost. This work develops a linear state-space model of the yaw-plane dynamics of a light vehicle-trailer combination, parameterized to expose tongue load as an explicit stability-determining quantity. From this model a linear quadratic regulator is synthesized to suppress articulation-angle divergence. Because consumer trailers carry no sensors, the two trailer states the controller needs, trailer yaw rate and articulation angle, are estimated by a Kalman filter from measurements taken only on the tow vehicle. The controller is then implemented and evaluated in a MuJoCo multibody simulation across a range of longitudinal speeds and tongue-load conditions, including the negative-tongue-load regime. Results show a significant decrease in trailer oscillation when controlling a given vehicle's steering with an LQR using tow-vehicle IMU and LiDAR data. These findings indicate that LQR controlled anti-sway systems are a viable control method for future autonomous vehicles.