A path-following driver/vehicle model with optimized lateral dynamic controller

Mashadi, Behrooz; Mahmoudi-Kaleybar, Mehdi; Ahmadizadeh, Pouyan; Oveisi, Atta

doi:10.1590/s1679-78252014000400004

Cited by 45 publications

(25 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This kind of controller is very popular in industry due to its stability and low online computation, but its parameters may suffer from over-tuning [ 1 ], and such a controller takes no consideration of vehicle dynamic forces. The dynamic properties of a vehicle can be handled by a dynamic controller [ 13 ], in which both wheel slip and wheel cornering are considered. The optimal controller, especially the linear quadratic regulator (LQR) with discrete linear model, is widely reported [ 14 ], where the feedback gain is determined by linear quadratic optimization, and it can be computed offline without need of high-cost hardware.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Liu

et al. 2018

Sensors

View full text Add to dashboard Cite

Vision-based sensors are widely used in lateral control of autonomous vehicles, but the large computational cost of the visual algorithms often induces uneven time delays. In this paper, a hierarchical vision-based lateral control scheme is proposed, where the upper controller is designed by robust H∞-based linear quadratic regulator (LQR) algorithm to compensate sensor-induced delays, and the lower controller is based on logic threshold method, in order to achieve strong convergence of the steering angle. Firstly, the vehicle lateral model is built, and the nonlinear uncertainties induced by time delays are linearized with Taylor expansion. Secondly, the state space of the system is augmented to describe such uncertainties with polytopic inclusions, which is controlled by an H∞-based LQR controller with a low cost of online computation. Then, a lower controller is designed for the control of the steering motor. According to the results of the vehicle experiment as well as the hardware-in-the-loop (HIL) experiment, the proposed control scheme shows good performance in vehicle’s lateral control task, and exhibits better robustness compared with a conventional LQR controller. The proposed control scheme provides a feasible solution for the lateral control of autonomous driving.

show abstract

Section: Introductionmentioning

confidence: 99%

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Liu

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…They can be used as desert transporters or carriers of passengers on the snow or sand terrains. They can also be used as forest fire tracked vehicles [3]. In addition to the reasons and as the most important reason, they can be used invaluable in the field of military vehicles for pulling tracked trailers and towing knocked out tanks from the battlefield [4].…”

Section: Introductionmentioning

confidence: 99%

Optimal Control of the Vehicle Path Following by Using Image Processing Approach

Pourasad

2018

IJE

View full text Add to dashboard Cite

Nowadays, the importance of the vehicles and its dramatic effects on transportation system is obvious. The use of trailers with multiple axels for transporting bulky and heavy equipment is essential. Stability and steerability of trailers with multiple axels and wheels is one of the main concerns in the transportation system. Therefore, in this paper dynamic modeling and control of a 5 axial trailer was studied. As well as to increase maneuverability and speed up, 3 axles was considered to be steered. Also, by using image processing trailer path following in desired path with the highest accuracy was achieved. In this study, first a 14 DoF model for a 5 axial trailer with 3 steering axles was considered and its dynamic was formulated. For this purpose, dynamic equations including kinematic and kinetic of trailer was obtained. Then, with evaluating trailers response, a linear quadratic optimal control algorithm was designed. In order to evaluate the performance of the control algorithm, control problem simulation for single lane change and overtaking was done. The results confirmed the performance of designed control algorithm and image processing accuracy in trailer path following.

show abstract

“…The problem of path tracking control is one of the core control problems of unmanned vehicles. From the viewpoint of control theory, path tracking control strategies can be understood as the driver's attempt to diminish the lateral error [1]. The modeling of driver's steering behavior has developed for more than half a century, and, based on different applications and methods, there have been a lot of driver models published [2,3].…”

Section: Introductionmentioning

confidence: 99%

A Fractional Derivative-Based Lateral Preview Driver Model for Autonomous Automobile Path Tracking

Wang

et al. 2018

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The concept of focus point preview is proposed, and fractional calculus is introduced to driver model to build focus point preview driver model. A formula for calculating lateral error is given, where the weight coefficients of fractional calculus are designed to imitate the driver’s focus preview property. The relationship between the speed and the order of fractional calculus is studied. A driver-vehicle-road simulation system is set up to illustrate the performances of the proposed preview model. The S-type road is used to test the model in the case of continuous small curvature turns and the Shanghai F1 track model is used as the case that automobile passing large curvature curve. The performances are evaluated from two aspects: path tracking effect and vehicle dynamic responses. It is concluded that, as the speed of the vehicle increases, the optimal order of fractional integral increases, so that the order is seen as the degree of driver’s attention. What is more, in the case of large curvature, the path tracking performance is improved by increasing the corresponding fractional order. Simulations results also show that, compared with the single-point preview model, the performances of the focus point preview model are better. On the one hand, the proposed driver model can be used to control the vehicle steering and path tracking. On the other hand, fractional calculus is used to reveal the driver preview property and the order is given a certain physical meaning, which is conducive to the development of fractional calculus applications.

show abstract

A path-following driver/vehicle model with optimized lateral dynamic controller

Cited by 45 publications

References 15 publications

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Optimal Control of the Vehicle Path Following by Using Image Processing Approach

A Fractional Derivative-Based Lateral Preview Driver Model for Autonomous Automobile Path Tracking

Contact Info

Product

Resources

About