scholarly journals Method of controlling innovative articulation for articulated vehicle

2018 ◽  
Vol 157 ◽  
pp. 04005 ◽  
Author(s):  
Mateusz Szumilas ◽  
Sergiusz Łuczak ◽  
Maciej Bodnicki ◽  
Marcin Stożek ◽  
Tomasz Załuski
Keyword(s):  
Control Algorithm ◽  
Diagnostic System ◽  
Lane Change ◽  
Sensor Layer ◽  
Motion Stability ◽  
Labview Software ◽  
Articulated Vehicle ◽  
Vehicle Motion ◽  
Action Taking

Operation of an articulated vehicle is dependent on an appropriate damping action taking place in its rotary articulation. In order to analyse an impact of the control of the articulation on the motion of the vehicle a model of the vehicle with a controllable hydraulic damping system has been developed. A 90 degree turn and lane change manoeuvres were simulated using LabVIEW software. Modification of the damping parameters of the articulation, according to the velocity and articulation angle of the vehicle, proved to have a significant impact on the vehicle motion stability. Moreover, the sensor layer necessary for the control algorithm as well as the diagnostic system is described.

An adaptive sliding mode controller for the lateral control of articulated long vehicles

2018 ◽  
Vol 233 (3) ◽  
pp. 487-515 ◽  
Author(s):  
Naser Esmaeili ◽  
Reza Kazemi ◽  
S Hamed Tabatabaei Oreh
Keyword(s):  
High Speed ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Lane Change ◽  
Lateral Velocity ◽  
Low Speed ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Articulated Vehicle ◽  
The Stability

Today, use of articulated long vehicles is surging. The advantages of using large articulated vehicles are that fewer drivers are used and fuel consumption decreases significantly. The major problem of these vehicles is inappropriate lateral performance at high speed. The articulated long vehicle discussed in this article consists of tractor and two semi-trailer units that widely used to carry goods. The main purpose of this article is to design an adaptive sliding mode controller that is resistant to changing the load of trailers and measuring the noise of the sensors. Control variables are considered as yaw rate and lateral velocity of tractor and also first and second articulation angles. These four variables are regulated by steering the axles of the articulated vehicle. In this article after developing and verifying the dynamic model, a new adaptive sliding mode controller is designed on the basis of a nonlinear model. This new adaptive sliding mode controller steers the axles of the tractor and trailers through estimation of mass and moment of inertia of the trailers to maintain the stability of the vehicle. An articulated vehicle has been exposed to a lane change maneuver based on the trailer load in three different modes (low, medium and high load) and on a dry and wet road. Simulation results demonstrate the efficiency of this controller to maintain the stability of this articulated vehicle in a low-speed steep steer and high-speed lane change maneuvers. Finally, the robustness of this controller has been shown in the presence of measurement noise of the sensors. In fact, the main innovation of this article is in the designing of an adaptive sliding mode controller, which by changing the load of the trailers, in high-speed and low-speed maneuvers and in dry and wet roads, has the best performance compared to conventional sliding mode and linear controllers.

scholarly journals A Study of the Dynamic Parameters Influence over the Behavior of the Two-Section Articulated Vehicle during the Lane Change Manoeuvre

2016 ◽  
Vol 11 (1) ◽  
pp. 29-40 ◽  
Author(s):  
Rusi Rusev ◽  
Rosen Ivanov ◽  
Gergana Staneva ◽  
Georgi Kadikyanov
Keyword(s):  
Lane Change ◽  
Dynamic Parameters ◽  
Articulated Vehicle

A direct yaw moment controller for a four in-wheel motor drive electric vehicle using adaptive sliding mode control

2019 ◽  
Vol 233 (3) ◽  
pp. 549-567 ◽  
Author(s):  
Aria Noori Asiabar ◽  
Reza Kazemi
Keyword(s):  
Sliding Mode Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
Regenerative Braking ◽  
Lane Change ◽  
Unknown Parameters ◽  
Vehicle Handling ◽  
Adaptive Sliding Mode ◽  
Yaw Moment

In this paper, a direct yaw moment control algorithm is designed such that the corrective yaw moment is generated through direct control of driving and braking torques of four in-wheel brushless direct current motors located at the empty space of vehicle wheels. The proposed control system consists of a higher-level controller and a lower-level controller. In the upper level of proposed controller, a PID controller is designed to keep longitudinal velocity constant in manoeuvres. In addition, due to probable modelling error and parametric uncertainties as well as adaptation of unknown parameters in control law, an adaptive sliding mode control through adaptation of unknown parameters is presented to yield the corrective yaw moment such that the yaw rate tracks the desired value and the vehicle sideslip angle maintains limited so as to improve vehicle handling stability. The lower-level controller allocates the achieved control efforts (i.e. total longitudinal force and corrective yaw moment) to driving or regenerative braking torques of four in-wheel motors so as to generate the desired tyre longitudinal forces. The additional yaw moment applied by upper-lever controller may saturate the tyre forces. To this end, a novel longitudinal slip ratio controller which is designed based on fuzzy logic is included in the lower-level controller. A tyre dynamic weight transfer-based torque distribution algorithm is employed to distribute the motor driving torque or regenerative braking torque of each in-wheel motor for vehicle stability enhancement. A seven degree-of-freedom non-linear vehicle model with Magic Formula tyre model as well as the proposed control algorithm are simulated in Matlab/Simulink software. Three steering inputs including lane change, double lane change and step-steer manoeuvres in different roads are investigated in simulation environment. The simulation results show that the proposed control algorithm is capable of improving vehicle handling stability and maintaining vehicle yaw stability.

scholarly journals Study on Orchard Vehicle Motion Stability Control System

2016 ◽  
Vol 49 (16) ◽  
pp. 451-456 ◽  
Author(s):  
Wang Xin ◽  
Xu Miao ◽  
Li Weiwei ◽  
Lu Hongsong ◽  
Zhang Shaohong ◽  
...  
Keyword(s):  
Control System ◽  
Stability Control ◽  
Motion Stability ◽  
Stability Control System ◽  
Vehicle Motion

scholarly journals Effect of vehicle motion stability after impact/crash on traffic safety

2018 ◽  
Vol 231 ◽  
pp. 05005
Author(s):  
Eligiusz Mieloszyk ◽  
Anita Milewska ◽  
Sławomir Grulkowski
Keyword(s):  
Dynamical Systems ◽  
Traffic Safety ◽  
Stability Theory ◽  
Road Traffic ◽  
Motion Stability ◽  
General Stability ◽  
Vehicle Motion

The article presents the application of general stability theory to the study of road traffic stability immediately after an impact (crash, collision). It turns out that when modelling a collision, vehicles can be treated as colliding masses and dynamical systems can be assigned to this phenomenon.

scholarly journals Research on the Comfort of Vehicle Passengers Considering the Vehicle Motion State and Passenger Physiological Characteristics: Improving the Passenger Comfort of Autonomous Vehicles

2020 ◽  
Vol 17 (18) ◽  
pp. 6821
Author(s):  
Chang Wang ◽  
Xia Zhao ◽  
Rui Fu ◽  
Zhen Li
Keyword(s):  
Prediction Model ◽  
Autonomous Vehicles ◽  
Control Algorithm ◽  
Short Term Memory ◽  
Autonomous Vehicle ◽  
Physiological Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Analysis Model ◽  
Passenger Comfort ◽  
Vehicle Motion

Comfort is a significant factor that affects passengers’ choice of autonomous vehicles. The comfort of an autonomous vehicle is largely determined by its control algorithm. Therefore, if the comfort of passengers can be predicted based on factors that affect comfort and the control algorithm can be adjusted, it can be beneficial to improve the comfort of autonomous vehicles. In view of this, in the present study, a human-driven experiment was carried out to simulate the typical driving state of a future autonomous vehicle. In the experiment, vehicle motion parameters and the comfort evaluation results of passengers with different physiological characteristics were collected. A single-factor analysis method and binary logistic regression analysis model were used to determine the factors that affect the evaluation results of passenger comfort. A passenger comfort prediction model was established based on the bidirectional long short-term memory network model. The results demonstrate that the accuracy of the passenger comfort prediction model reached 84%, which can provide a theoretical basis for the adjustment of the control algorithm and path trajectory of autonomous vehicles.

A novel decision-making unit for automated maneuver of articulated vehicles in real traffic situations

2019 ◽  
Vol 234 (1) ◽  
pp. 152-171 ◽  
Author(s):  
Saeed Shojaei ◽  
Ali Rahmani Hanzaki ◽  
Shahram Azadi ◽  
Mohammad Amin Saeedi
Keyword(s):  
Decision Making ◽  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Time Range ◽  
Lane Change ◽  
Mode Control ◽  
Articulated Vehicle ◽  
Double Lane Change ◽  
Real Traffic

In this paper, a new decision-making algorithm for double lane change maneuver of an articulated vehicle in real dynamic circumstances is studied. A novel method for determining the decision conditions is used based on the articulated vehicle kinematics and dynamics. Through this method, several points of the articulated vehicle are considered in various situations when conducting double lane change maneuver, and the critical points are determined. A new realistic dynamic method is used based on a 16-degrees of freedom dynamic model of the articulated vehicle. The sliding mode control method is utilized to increase the method efficiency. Therefore, the least safe time to perform the double lane change maneuver is extracted based on the sliding mode control method as tracking control. A new Articulated Vehicle Least safe time formulation is determined for dynamic circumstances. Based on the results of simulated test, the acceptable time range is also established for conducting the lane change maneuver. The lane change maneuver is generalized to the double lane change maneuver. Decision-making algorithm is introduced based on real traffic situations. The dynamic approach and the decision-making algorithm are verified. Results show the validity of the reflected method meaning that the decision-making algorithm is acceptable.

Nonlinear Stability Analysis of Vehicle Lateral Motion With a Hybrid Physical/Dynamic Tire/Road Friction Model

2009 ◽  
Author(s):  
Jingang Yi ◽  
Eric H. Tseng
Keyword(s):  
Friction Model ◽  
Lateral Motion ◽  
Nonlinear Stability Analysis ◽  
Friction Forces ◽  
Motion Stability ◽  
Road Friction ◽  
Vehicle Motion ◽  
Longitudinal Slip ◽  
Estimation And Control ◽  
And Control

We present a nonlinear analysis of vehicle motion using a hybrid physical/dynamic tire/road friction model. The advantage of the proposed LuGre dynamic tire/road friction model is the simple and attractive structural properties for real-time friction estimation and control. Moreover, the model provides a property of capturing coupling effects between the longitudinal and lateral friction forces. We take advantages of these properties and analyze the vehicle lateral motion stability. We have shown that the existence of longitudinal slip affects the lateral motion stability. The quantitative analysis and relationship are also demonstrated through numerical simulation examples.

Control and Validation of Automated Lane Centering and Lane Changing Maneuver

2009 ◽  
Author(s):  
Jin-Woo Lee ◽  
Bakhtiar Litkouhi
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Lateral Displacement ◽  
Lateral Acceleration ◽  
Lane Change ◽  
Time Step ◽  
Lane Changing ◽  
Current Time ◽  
On The Road ◽  
Lateral Offset

This paper describes an automated lane changing control system that has been developed at General Motors Research and Development. This system uses a single monochrome camera to recognize lane markings on the road ahead and uses multiple short range radars to detect surrounding traffic and objects. A sensing unit calculates the host vehicle’s lateral displacement and the heading angle from the center of its lane as well as the relative distance and relative speed of each object. Since the smoothness and comfort of lane change maneuvering are important measures of the control performance, the vehicle dynamic model is integrated into the desired path generation and vehicle’s controller design to reduce the vehicle lateral acceleration and the lateral offset overshoot during the lane change maneuvering. To avoid heavy computation, a simplified model predictive control algorithm is proposed. The control algorithm calculates a steering angle command at the current time step to drive the vehicle to the desired path. The control method and algorithms are implemented on a demonstration vehicle and validated at straight roads and various curve roads of up to 0.001 [1/m] curvature for different vehicle speeds up to 100 [km/hr]. The results show that lane change maneuvering is successfully completed with lateral offset error less than 20 cm.

scholarly journals Intelligent vehicle lane change trajectory control algorithm based on weight coefficient adaptive adjustment

2021 ◽  
Vol 13 (3) ◽  
pp. 168781402110033
Author(s):  
Junnian Wang ◽  
Fei Teng ◽  
Jing Li ◽  
Liguo Zang ◽  
Tianxin Fan ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Lateral Displacement ◽  
Weight Coefficient ◽  
Intelligent Vehicles ◽  
Slip Angle ◽  
Lane Change ◽  
Predictive Controller ◽  
Adaptive Control Algorithm ◽  
Fuzzy Control Algorithm

In order to improve the trajectory smoothness and the accuracy of lane change control, an adaptive control algorithm based on weight coefficient was proposed. According to lane change trajectory constraint conditions, the sixth-order polynomial lane change trajectory applied to intelligent vehicles was constructed. Based on the vehicle model and the model predictive control theory, the time-varying linear variable path vehicle predictive model was derived by combining soft constraint of the side slip angle. Combined with fuzzy control algorithm, the weight coefficient of the deviation of the lateral displacement was dynamically adjusted. Finally, the FMPC (model predictive controller based on fuzzy control) and MPC controller were compared and analyzed by co-simulation of CarSim and Simulink under different speeds. The simulation results show that the designed FMPC controller can track the lane change trajectory better, and the controller has better robustness when the vehicle changes lanes at different speeds.

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