scholarly journals Contingency Model Predictive Control for Automated Vehicles

Author(s):  
John P. Alsterda ◽  
Matthew Brown ◽  
J. Christian Gerdes
2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986761 ◽  
Author(s):  
Haobin Jiang ◽  
Jie Zhou ◽  
Aoxue Li ◽  
Xinchen Zhou ◽  
Shidian Ma

With the rapid development of automated vehicles, there is currently a significant amount of automated driving research. Giving automated vehicles capabilities similar to those of experienced drivers will allow them to share the road harmoniously with manned vehicles, especially on two-lane urban curves. To represent the steering behavior of experienced drivers, a series of curve feature distances are proposed, which is determined by multi-regression. These series of curve feature distances are used to generate a trapezoidal steering angle model which imitates the steering behavior of the experienced test drivers. To verify the feasibility and human-likeness of the proposed trapezoidal steering angle model, the model is used with constant vehicle speed to plan a human-like trajectory which is tracked using model predictive control. The simulation results show that the proposed trapezoidal steering angle model is human-like and could be used to give automated vehicles human-like driving capability when driving on two-lane curves.


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