Active Steering Assistance for Lane Keeping and Lane Departure Prevention

Enache, Nicoleta Minoiu; Mammar, Saïd; Lusetti, Benoît; Sebsadji, Yazid

doi:10.1115/1.4003801

Cited by 6 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The track is 3.5-km length with different profiles. The lookahead lateral offset and the relative yaw angle are measured using clustering of a video camera mounted under the mirror of the vehicle and vision algorithms [6], [14]. An inertial unit provides measurement of the yaw rateψ(t) and an optical encoder provides the steering angle δ f (t).…”

Section: Resultsmentioning

confidence: 99%

Takagi-Sugeno Observers: Experimental Application for Vehicle Lateral Dynamics Estimation

Yacine

Ichalal

Ait-Oufroukh

et al. 2015

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

This brief presents a contribution to nonlinear observer design for both the estimation of vehicle lateral dynamics and road curvature. The latter is recovered by a simple algebraic technique and high-order sliding mode differentiator, which allows to estimate exactly the time derivatives of measured signals. For the lateral dynamics of the vehicle, a new approach is developed by the use of a Takagi-Sugeno (TS) model representing exactly, with no loss of information, the nonlinear vehicle behavior in a compact set of the state space. The TS model involves unmeasured premise variables. The proposed new observer starts with the estimation of these premise variables. Second, the design of an observer with weighting functions depending on these estimated premise variables is considered. Theoretically, the proposed observer ensures exponential convergence of the state estimation error toward zero. This convergence is studied by the Lyapunov theory and the obtained stability conditions are expressed in terms of linear matrix inequalities. Finally, experimental results are given for vehicle lateral dynamics and road curvature estimation with real data.Index Terms-Algebraic approach, high-order sliding mode differentiators (HOSMDs), nonlinear observers, TakagiSugeno (TS) systems.

show abstract

Section: Resultsmentioning

confidence: 99%

Takagi-Sugeno Observers: Experimental Application for Vehicle Lateral Dynamics Estimation

Yacine

Ichalal

Ait-Oufroukh

et al. 2015

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

show abstract

“…A steering control approach based on linear matrix inequality and bilinear matrix inequality was proposed to constrain the vehicle states within the prescribed limits. 4 This approach requires the accurate system identification of the vehicle. A fuzzy steering controller was proposed by Wu et al, 5 which performs well but is heuristic due to lack of stability proof.…”

Section: Introductionmentioning

confidence: 99%

Automated steering controller design for vehicle lane keeping combining linear active disturbance rejection control and quantitative feedback theory

Chu

Sepehri

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

In this article, a new automated steering control method is presented for vehicle lane keeping. This method is a combination between the linear active disturbance rejection control and the quantitative feedback theory. The structure of the steering controller is first determined based on the linear active disturbance rejection control, then the controller is tuned in the framework of the quantitative feedback theory to meet the prescribed design specifications on sensitivity and closed-loop stability. The parameter uncertainties of the vehicle system are considered at the tuning stage. The proposed steering controller is simulated and tested on a scale vehicle. Both the simulation and experimental results demonstrate that the scale vehicle controlled by the proposed controller is able to perform the lane keeping. In the experiments, the lateral offset between the scale vehicle and the road centerline is regulated within the acceptable ranges of 60.03 m during straight lane keeping and 60.15 m during curved lane keeping. The proposed controller is easy to be implemented and is simple without requiring complex calculations and measurements of vehicle states. Simulations also show that the control method can be implemented on a full-scale vehicle.

show abstract

“…In the past 10 years, the researchers have employed different control rules including sliding mode control (SMC), [3][4][5][6][7][8][9][10][11][12] HN robust control, 13,14 model predictive control (MPC), [15][16][17][18][19][20] fuzzy control, [21][22][23][24][25][26] backstepping, 27,28 adaptive control, [29][30][31] proportional-integralderivative (PID) controllers, [32][33][34][35] linear-quadratic regulator (LQR), 22,36,37 optimization algorithms 38,39 and solution of linear matrix inequalities (LMI) 40 to design controllers. Sliding mode control as a non-linear control plays an important role against different friction changes of road and different velocities in the presence of parameter uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…In another study, the vehicle tracking control is designed using particle swarm optimization (PSO) algorithm based on PID and LQR controllers. 39 Enache et al 40 applied LMI and bilinear matrix inequality (BMI) optimization methods to design the controller for lane keeping system. The various control methods performed by researchers are mentioned.…”

Section: Introductionmentioning

confidence: 99%

Vehicle lateral control in the presence of uncertainty for lane change maneuver using adaptive sliding mode control with fuzzy boundary layer

Norouzi

Kazemi

Azadi

2017

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

Recent researches on advanced driver-assistance systems indicate great advances in terms of safety and comfort in automated driving. Advanced driver-assistance systems use control systems to perform most of the maneuvers as performed by the driver in the past. One of the useful advanced driver-assistance systems is automatic lane change system in order to avoid accidents. This study designs the controller of an automatic lane change system for an autonomous vehicle. The control law in this study is adaptive sliding mode control. To avoid chattering in adaptive sliding mode control, fuzzy boundary layer is used. Also, adaptive law is used for sliding-based switching gain. This adaptive controlling law is used to avoid the calculation of upper bound of system uncertainties. In this study, based on the boundary conditions, the vehicle lane change path planning and different maneuver periods are evaluated. To simulate the designed controller, CarSim-Simulink joint simulation model is used. This linkage leads to a full non-linear vehicle model. The results of simulation show excellent tracking for dry road conditions and acceptable tracking in icy and wet roads in some maneuvers of above 4-s long.

show abstract

Active Steering Assistance for Lane Keeping and Lane Departure Prevention

Cited by 6 publications

References 12 publications

Takagi-Sugeno Observers: Experimental Application for Vehicle Lateral Dynamics Estimation

Takagi-Sugeno Observers: Experimental Application for Vehicle Lateral Dynamics Estimation

Automated steering controller design for vehicle lane keeping combining linear active disturbance rejection control and quantitative feedback theory

Vehicle lateral control in the presence of uncertainty for lane change maneuver using adaptive sliding mode control with fuzzy boundary layer

Contact Info

Product

Resources

About