Optimal control of vehicle dynamics for the prevention of road departure on curved roads

Gao, Yangyan and Gordon, Timothy (2019) Optimal control of vehicle dynamics for the prevention of road departure on curved roads. IEEE Transactions on Vehicular Technology . ISSN 0018-9545

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Optimal control of vehicle dynamics for the prevention of road departure on curved roads
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Abstract

Run-off-Road crashes are often associated with excessive speed in curves, which may happen when a driver is distracted or fails to compensate for reduced surface friction. This work introduces an Automated Emergency Cornering (AEC) system to protect against the major effects of over-speeding on curves, especially lateral deviation leading to lane or road departure. The AEC architecture has two levels: an upper level to perform motion planning, based on the optimal control of a nonlinear particle model, and a lower level to distribute the resulting two-dimensional acceleration reference to the available actuators. The lower level adopts the recently introduced Modified Hamiltonian Algorithm (MHA), which continuously adjusts the priority between mass-centre acceleration and yaw moment demands derived from lateral stability targets. AEC makes use of a high precision map and triggers control interventions based on vehicle kinematic states and detailed road geometry. To avoid false-positive interventions, AEC is triggered only when excessive road departure is predicted for the optimal particle motion. AEC then takes control of steering and individual wheel brake actuators to perform autonomous motion control for speed and path curvature at the limits of available friction. The AEC system is tested and evaluated.

Keywords:Vehicle Dynamics and Control, Autonomous Vehicles, Active Safety, Optimal Control, Collision Avoidance, Lane Departure Prevention
Subjects:H Engineering > H330 Automotive Engineering
H Engineering > H660 Control Systems
H Engineering > H300 Mechanical Engineering
H Engineering > H331 Road Vehicle Engineering
Divisions:College of Science > School of Engineering
ID Code:36300
Deposited On:25 Jun 2019 15:35

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