Influence of Human Driving Characteristics on Path Tracking Performance of Vehicle

Taheri, Saied; Rakheja, Subhash; Hong, Henry

doi:10.1007/978-3-642-33515-0_21

Cited by 9 publications

(6 citation statements)

References 21 publications

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“…The MPC controllers are designed for each driver, respectively. In controller design, the maximum allowable deviation of trajectory tracking as well as the maximum human capability of steering angle and steering rate constraints are set based on the data given in [25].…”

Section: Simulation Studiesmentioning

confidence: 99%

Path Tracking Control for Active Rear Steering Vehicles Considering Driver Steering Characteristics

2020

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In this paper, a path tracking control for active rear steering vehicles considering driver steering characteristics is proposed to help drivers track the desired vehicle trajectory in a tailored way. Firstly, the driver model is established, and based on the driver steering data, the driver parameters are identified by the least square method. Based on driver model parameter identification, driver and vehicle models are formed for the MPC controller design. In MPC controller design, global objective function, considering the task performance, vehicle stability, driver's physical workloads, mental workloads and actuator performance, is designed to optimize the overall performance of the driver-vehicle system. On the constraint, the driver operating limit, actuator physical limit and vehicle stability performance limit are also considered to make the controller feasible to in the real practice. Simulation results under different conditions show that the controller can significantly improve the system performance and reduce the driver's workloads. INDEX TERMS Path tracking, vehicle dynamics, active steering, model predictive control.

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Section: Simulation Studiesmentioning

confidence: 99%

Path Tracking Control for Active Rear Steering Vehicles Considering Driver Steering Characteristics

2020

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“…In the design of active steering controller, combining Equation (23) and Equation (25), the state equation of vehicle in global coordinate is: (26) where x=[x1, x2, x3, x4, x5, x6], x1=vy, x2=  , x3=ϕ, x4=Y,…”

Section: ) Active Steering Controller Designmentioning

confidence: 99%

“…SMC is a control method that designs the switching hyperplane of the system according to the expected dynamic characteristics of the system [26]- [27]. Then it uses the sliding mode controller to make the system state from the outside of the switching hyperplane to the switching hyperplane.…”

Section: ) Active Brake Controller Design Based On Sliding Mode Varimentioning

confidence: 99%

Control Strategy of Vehicle Anti-Rollover Considering Driver’s Characteristic

Cao

Yan

et al. 2020

IEEE Access

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In the process of vehicle anti-rollover, the driver's behavioral characteristics have a great influence on the vehicle rollover stability. However, the existing researches on anti-rollover rarely consider the driver in the human-vehicle-road closed loop system, which may directly affects the rollover dynamics characteristics of the vehicle. Aiming at this problem, this work analyzes the influence of different driver parameters on vehicle dynamics and establishes a driver model considering the vehicle rollover stability. Based on this, a collaborative control strategy of vehicle anti-rollover considering the driver's characteristics is designed to assist the driving stability requirements of different types of drivers. It includes the upper layer of supervision decision control and the lower layer of cooperative execution control. The supervisory decision control layer sets different rollover constraint boundaries for different types of drivers, and makes six control decision modes combining driver input and vehicle path tracking error. Aiming at different types of drivers, the lower cooperative execution control layer constrains the front wheel angle by the active steering system to reduce yaw rate and the risk of rollover. Moreover, it reasonably distributes the braking force of four tires by the active braking system to reduce the path tracking error while preventing rollover. The simulation results show that, the proposed cooperative control strategy can provide different control effects for different drivers, and ensure the effective anti-rollover control of the vehicle and achieve good path tracking performance. INDEX TERMS Driver model, rollover, parameter identification, active steering, active braking.

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“…Values of T P , T d , a 0 , and G h depend upon the driver's characteristics. [28][29][30]32,33 Different drivers may perform with different characteristics such as steer proportional gain and time delay in an identical scenario. 28 For example, the age may impair one's physical capability, so for an aged driver, he or she needs a longer time for mental signal processing and muscular activation and prefers to react with a smaller G h and a larger T d , while a younger driver has reverse reactions.…”

Section: Driver Modelmentioning

confidence: 99%

A non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of driver’s characteristics

Zhang

Wang

Chen

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of the characteristics of different drivers. The driver–vehicle model considering vehicle dynamics and characteristics of the drivers is used to formulate a vehicle-to-vehicle encountering system. A non-cooperative control algorithm considering each of the driver–vehicle system as a player is employed to plan collision-free trajectories for the encountering vehicles with respective initial driving intentions. The non-cooperative problem is solved with the theory of Nash equilibrium and is ultimately converted to a standard nonlinear Model Predictive Control problem. Simulations are conducted in the scenarios of the lane-exchanging and overtaking with different initial vehicle speeds to verify the effectiveness of the proposed algorithm. Results show that the algorithm can accomplish the trajectory-planning task with consideration of both the safety requirement and the characteristics of drivers. The simulation results also show that the proposed algorithm has effectiveness for trajectory planning in different vehicle-to-vehicle encountering scenarios.

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Influence of Human Driving Characteristics on Path Tracking Performance of Vehicle

Cited by 9 publications

References 21 publications

Path Tracking Control for Active Rear Steering Vehicles Considering Driver Steering Characteristics

Path Tracking Control for Active Rear Steering Vehicles Considering Driver Steering Characteristics

Control Strategy of Vehicle Anti-Rollover Considering Driver’s Characteristic

A non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of driver’s characteristics

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