Human-like trapezoidal steering angle model on two-lane urban curves

Jiang, Haobin; Zhou, Jie; Li, Aoxue; Zhou, Xinchen; Ma, Shidian

doi:10.1177/1729881419867614

Cited by 3 publications

(3 citation statements)

References 29 publications

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“…Jiang et al [43] proposed a human-like trapezoidal steering angle model to quantitate the relationship between objective road factors and steering wheel angles generated by human drivers. They elaborated the idealized curve described by the straight curve length, the radius of curve R, and curve subtended angle α, constituting three consecutive sections: straight, circular curve, and straight.…”

Section: The Scheme Of Corneringmentioning

confidence: 99%

The Measurement of the Wear of Tie Rod End Components

Woźniak¹,

Rylski²,

Siczek³

2022

sv-jme

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This study aimed to determine the wear intensity of the bearing mating with the ball stud in the tie rod end. The course of the vehicle driving during the period between repairs of the steering assembly was assumed. The modelled scheme of cornering was assumed to be close to the real one. The model of steering mechanism allowing determination of the load of the stud of the tie rod end as a function of the steering angle was elaborated and presented. The model of the ball stud was realized and described. The values of wear intensity for components were calculated and presented.

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Section: The Scheme Of Corneringmentioning

confidence: 99%

The Measurement of the Wear of Tie Rod End Components

Woźniak¹,

Rylski²,

Siczek³

2022

sv-jme

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show abstract

“…The driving trajectory is the specific performance of the driver's strategy and behavior of manipulating the vehicle. The similarity of the trajectory is an important reference index for investigating the steering behavior of the driver [26]. When analyzing the position parameters of the vehicle on the curve, the trajectory similarity model can be used to compare the simulator experiment.…”

Section: Introductionmentioning

confidence: 99%

Validation of Vehicle Driving Simulator from Perspective of Velocity and Trajectory Based Driving Behavior under Curve Conditions

Chen

Xie

et al. 2021

Energies

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With their advantages of high experimental safety, convenient setting of scenes, and easy extraction of control parameters, driving simulators play an increasingly important role in scientific research, such as in road traffic environment safety evaluation and driving behavior characteristics research. Meanwhile, the demand for the validation of driving simulators is increasing as its applications are promoted. In order to validate a driving simulator in a complex environment, curve road conditions with different radii are considered as experimental evaluation scenarios. To attain this, this paper analyzes the reliability and accuracy of the experimental vehicle speed of a driving simulator. Then, qualitative and quantitative analysis of the lateral deviation of the vehicle trajectory is carried out, applying the cosine similarity method. Furthermore, a data-driven method was adopted which takes the longitudinal displacement, lateral displacement, vehicle speed and steering wheel angle of the vehicle as inputs and the lateral offset as the output. Thus, a curve trajectory planning model, a more comprehensive and human-like operation, is established. Based on directional long short-term memory (Bi–LSTM) and a recurrent neural network (RNN), a multiple Bi–LSTM (Mul–Bi–LSTM) is proposed. The prediction performance of LSTM, MLP model and Mul–Bi–LSTM are compared in detail on the validation set and testing set. The results show that the Mul–Bi–LSTM model can generate a trajectory which is very similar to the driver’s curve driving and have a preferable generalization performance. Therefore, this method can solve problems which cannot be realized in real complex scenes in the simulator validation. Selecting the trajectory as the validation parameter can more comprehensively and intuitively reflect the simulator’s curve driving state. Using a speed model and trajectory model instead of a real car experiment can improve the efficiency of simulator validation and lay a foundation for the standardization of simulator validation.

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“…However, they did not reflect the exact human drivers' steering maneuvers. 17 What is more, both the preview driver model and MPC need to set a desired trajectory in advance, 18 which is inconsistent with the actual driving behavior of human drivers.…”

Section: Introductionmentioning

confidence: 99%

Establishment and tracking control of trapezoidal steering wheel angle model for autonomous vehicles

Jiang

Zhou

et al. 2020

International Journal of Advanced Robotic Systems

Self Cite

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Human drivers have rich and diverse driving characteristics on curved roads. Finding the characteristic quantities of the experienced drivers during curve driving and applying them to the steering control of autonomous vehicles is the research goal of this article. We first recruited 10 taxi drivers, 5 bus drivers, and 5 driving instructors as the representatives of experienced drivers and conducted a real car field experiment on six curves with different lengths and curvatures. After processing the collected driving data in the Frenet frame and considering the free play of a real car’s steering system, it was interesting to observe that the shape enclosed by steering wheel angles and the coordinate axis was a trapezoid. Then, we defined four feature points, four feature distances, and one feature steering wheel angle, and the trapezoidal steering wheel angle (TSWA) model was developed by backpropagation neural network with the inputs were vehicle speeds at four feature points, and road curvature and the outputs were feature distances and feature steering wheel angle. The comparisons between TSWA model and experienced drivers, model predictive control, and preview-based driver model showed that the proposed TSWA model can best reflect the steering features of experienced drivers. What is more, the concise expression and human-like characteristic of TSWA model make it easy to realize human-like steering control for autonomous vehicles. Lastly, an autonomous vehicle composed of a nonlinear vehicle model and electric power steering (EPS) system was established in Simulink, the steering wheel angles generated by TSWA model were tracked by EPS motor directly, and the results showed that the EPS system can track the steering angles with high accuracy at different vehicle speeds.

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Human-like trapezoidal steering angle model on two-lane urban curves

Cited by 3 publications

References 29 publications

The Measurement of the Wear of Tie Rod End Components

The Measurement of the Wear of Tie Rod End Components

Validation of Vehicle Driving Simulator from Perspective of Velocity and Trajectory Based Driving Behavior under Curve Conditions

Establishment and tracking control of trapezoidal steering wheel angle model for autonomous vehicles

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