A Unified Lateral Preview Driver Model for Road Vehicles

Zhu, Shenjin; He, Yuping

doi:10.1109/tits.2019.2949227

Cited by 14 publications

(6 citation statements)

References 31 publications

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“…18 Meanwhile, the high-speed lateral stability of AHVs is usually assessed by rearward amplification method (RWA), which is defined as the ratio of the peak lateral acceleration at CoG of the tractor to that of the semi-trailer unit during a lane change maneuver. 6,22,31 The effectiveness of LQR active trailer steering (ATS) controller is verified based on TruckSim and MATLAB/Simulink closed-loop simulation environment. The 2A Cab-over + 1A Flatbed Trl model in TruckSim is selected as the baseline model, with application of the built-in driver, three previewed points driver model and LQR ATS controller.…”

Section: Simulation and Resultsmentioning

confidence: 99%

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A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

Deng

Jin

Gao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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To improve the directional performance of articulated heavy vehicles (AHV), three previewed points driver model and LQR active trailer steering (ATS) strategy are proposed and examined using closed-loop driver/vehicle dynamics simulation. Firstly, a simplified linear three-degree-of-freedom (3-DOF) yaw plane model for AHV is established and validated. Secondly, based on the multi-point preview-predictor following strategy, the weighted-average error of three previewed points of the tractor is defined as the final lateral previewed displacement error. According to the assumption of constant yaw rate and the trajectory prediction of AHV, and three previewed points driver model has been configured, it’s path-following performance is verified. Thirdly, instead of using the idea of minimization, a linear quadratic regulator (LQR) controller is proposed based on the linear 3-DOF yaw plane model of AHV to make the control variables to keep following the desired responses. Through joint simulations using MATLAB/Simulink and TruckSim, the effectiveness of the built-in driver model, three-previewed point driver model and three-previewed point driver model + LQR ATS control methods on improving vehicle orientation performance were compared and analyzed through closed-loop driver/vehicle dynamics simulations. The significant effectiveness of the proposed method in improving maneuverability and stability is verified through low-speed 360° trajectory tracking tests and high-speed double lane change maneuver simulations. Finally, a hardware-in-the-loop (HIL) platform is used to further verify the effectiveness of the designed strategy.

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Section: Simulation and Resultsmentioning

confidence: 99%

Section: Simulation and Resultsmentioning

confidence: 99%

A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

Deng

Jin

Gao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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show abstract

“…The operating parameters (or operating uncertainties) may include vehicle forward speed (U), trailer payload, road conditions, etc. Considering different drivers with various driving skills and habits, the parameters characterizing human drivers' driving behaviors, such as, reaction time (t) and preview time, may be treated as a subset of the overall parameter set of the vehicle system [23,24]. Under varied operating conditions and considering different drivers with various driving skills and habits, the LQR controller's gain matrix may be adaptively adjusted [25].…”

Section: Proposed 2-layer Design Optimization Methodsmentioning

confidence: 99%

Optimization of Gain Scheduled Controller for an Active Trailer Steering System Using an Evolutionary Algorithm

Qureshi

Liscano

2022

Machines

Self Cite

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Car–trailer combinations can experience unstable motion modes such as trailer-sway, jackknifing and rollover that can lead to fatal accidents. These unstable motions can be mitigated with the use of an active trailer steering (ATS) system. Prior studies in ATS have leveraged the linear quadratic regulator (LQR) as an ATS controller but for many of these designs it was assumed that the vehicle and operating parameters were constant. In reality, vehicle and operating parameters may vary and have an impact on the stability of a car–trailer combination. In this paper, the weighting matrices of the LQR controller are determined using the GDE3 evolutionary optimization algorithm with the objective of addressing the design trade off between minimizing the car–trailer’s path-following performance for low vehicle speeds and minimizing the rearward amplification for high vehicle speeds. The effectiveness of the approach is demonstrated using a numerical simulation car–trailer model developed in the CarSim simulator. Our results show that the multi-objective tuned gain scheduling controller outperforms a non-tuned gain scheduling controller in terms of improving the lateral stability and the path following performance of car–trailer combinations in driver in the loop single lane-change maneuvers at a constant vehicle forward speed.

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“…δ f is the wheel angle of the front axle. With reference to the modeling methods in previous studies [23,28] and considering the necessary dynamic response characteristics, the multi-axle system is simplified to a single-axle system. The following assumptions are made: (1) forward speed is a constant value and is guaranteed by a PID algorithm embedded in the software; (2) dynamics of the tire are ignored, and the linear tire model is adopted; (3) the articulation angle and the tire slip angle are small, and sin δ f ≈ δ f , sin θ ≈ θ, cos δ f ≈ 1, cos θ ≈ 1; and (4) ignore the influence of steering system, suspension system, etc., vehicle parameters remain unchanged.…”

Section: Vehicle Modelsmentioning

confidence: 99%

“…Li Xiansheng added the real-time motion state information of the semitrailer into the calculation of vehicle steering control, proposed a semitrailer Path-Following Algorithm based on the Quasi-Newton optimization method and studied the influence of semitrailer load, speed and a driver’s inherent time delay on vehicle behavior [ 22 ]. In order to improve the lateral stability of articulated vehicles (AVs), Yuping He proposed the Lateral Position Deviation Preview (LPDP) model based on LQR [ 23 ]. This model was composed of a tractor tracker and a trailer tracker.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Articulation Angle Preview-Based Path-Following Algorithm for Tractor-Semitrailer Using Optimal Control

Tang

Wang

et al. 2022

Sensors

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Most existing Path-Following Algorithms (PFAs) are developed for single-unit vehicles (SUVs) and rarely for articulated vehicles (AVs). Since these PFAs ignore the motion of the trailer, they may cause large tracking deviations and ride stability issues when cornering. To this end, an Adaptive Articulation Angle Preview-based Path-Following Algorithm (AAAP-PFA) is proposed for AVs. Different from previous PFAs, in this model, a simple linear vehicle dynamics model is used as the prediction model, and an offset distance calculated by an articulation angle is used as part of the preview distance. An adaptive posture control strategy is designed to trade off the trajectory tracking performance and lateral stability performance during the path-following process. Considering a large prediction mismatch caused by using a linear vehicle dynamics model, a feedback correction method is proposed to improve the robustness of the steering control. In the comparison simulation experiment with SUV-PFA, it is confirmed that the novel PFA has better adaptability to the contradictory relationship between tracking performance and lateral stability and has strong steering control robustness.

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A Unified Lateral Preview Driver Model for Road Vehicles

Cited by 14 publications

References 31 publications

A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

Optimization of Gain Scheduled Controller for an Active Trailer Steering System Using an Evolutionary Algorithm

Adaptive Articulation Angle Preview-Based Path-Following Algorithm for Tractor-Semitrailer Using Optimal Control

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