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Collision Imminent Steering at High Speed Using Nonlinear Model Predictive Control

delete2020-08-01
delete29
PRE
AI
J
John Wurts
J
Jeffrey L. Stein
T
Tulga Ersal *
DOI:10.1109/TVT.2020.2999612delete
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摘要

摘要

En 中文
Collision imminent steering is an automotive active safety feature designed to perform an aggressive lane change to avoid a forward collision in the event that the system determines there is insufficient distance to avoid a collision by braking alone.In this paper, a collision imminent steering system is developed using nonlinear model predictive control to perform a lane change at high speed in a highway environment. Two formulations are presented: one formulation to show the theoretical minimum lane change distance within which a safe lane change can be performed, and a second formulation to find the minimum aggressive maneuver for a given lane change distance. The nonlinear model predictive control formulation is posed as a constrained optimization problem, where solutions obey hard safety constraints of the highway environment. Constraint aggregation techniques are analyzed and introduced to monitor the peak tire slip throughout the maneuver. Numerical simulations of a typical luxury sedan in a highway setting show that minimum distance required to change lanes is about half the limit braking distance. Hence, there is a window of feasibility where the vehicle cannot avoid collision by braking alone, but can change lanes safely and maintain a safe trajectory throughout the maneuver. Additional simulations show that an active four wheel steering architecture improves performance over front only steering.
Keyword:
Trajectory
Safety
Road transportation
Collision avoidance
Predictive control
Optimization
Vehicle dynamics
Advanced driver assistance systems
autonomous vehicles
nonlinear control systems
trajectory optimization
vehicle dynamics
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期刊

IEEE Transactions on Vehicular Technology 封面图
IEEE Transactions on Vehicular Technology
IF:
7.1
论文数:
1.8W
被引数:
6.6W

机构

U
university of michigan system
学者数:
9.1W
论文数: 8.6W
被引数: 133
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