Stability of Controlled Road Vehicles: A Preliminary Fundamental Study

2015 ◽  
Author(s):  
Fabio della Rossa ◽  
Massimiliano Gobbi ◽  
Giampiero Mastinu ◽  
Carlo Piccardi ◽  
Giorgio Previati
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Preliminary Investigation ◽  
Basin Of Attraction ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Vehicle Speed ◽  
Vehicle Model ◽  
The Stability ◽  
Positive Effect

A comparison of the lateral stability behaviour between an autonomous vehicle, a vehicle with driver and a vehicle without driver (fixed steering wheel) is made by introducing a simple mathematical model of a vehicle running on even road. The mechanical model of the vehicle has two degrees of freedom and the related equations of motion contain the nonlinear tyre characteristics. The driver is described by a well-known model proposed in the literature. The autonomous vehicle has a virtual driver (robot) that behaves substantially like a human, but with its proper reaction time and gain. The road vehicle model has been validated. The study of vehicle stability has to be based on bifurcation analysis and a preliminary investigation is proposed here. The accurate computation of steady-state equilibria is crucial to study the stability of the three kinds of vehicles here compared. The stability of the bare vehicle without driver (fixed steering wheel) is studied in a rather complete way referring to a number of combinations of tyre characteristics. The (known) conclusion is that the understeering vehicle is stable at each lateral acceleration level and at each vehicle speed. The additional (partially unknown) conclusion is that the vehicle (model) with degradated tyres may exhibit a huge number of different bifurcations. The driver has many effects on the stability of the vehicle. One positive effect is to eliminate the many possible different equilibria of the bare vehicle and keep active one single equilibrium only. Another positive effect is to broaden the basin of attraction of stable equilibria (at least at relatively low speed). A negative effect is that, even for straight running, the driver seem introducing a subcritical Hopf bifurcation which limits the maximum forward speed of some understeering vehicles (that could run faster with fixed steering wheel). Both the mentioned positive and negative effects appear to be applicable to autonomous vehicles as well. Further studies could be useful to overcome the limitations on the stability of current autonomous vehicles that have been identified in the present research.

Vision-Based Navigation of Autonomous Vehicles in Roadway Environments with Unexpected Hazards

2019 ◽  
Vol 2673 (12) ◽  
pp. 494-507 ◽  
Author(s):  
Mhafuzul Islam ◽  
Mashrur Chowdhury ◽  
Hongda Li ◽  
Hongxin Hu
Keyword(s):  
Object Detection ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Semantic Segmentation ◽  
Steering Wheel ◽  
Potential Hazard ◽  
Driving System ◽  
Hazardous Object ◽  
Vision Based Navigation ◽  
Navigational System

Vision-based navigation of autonomous vehicles primarily depends on the deep neural network (DNN) based systems in which the controller obtains input from sensors/detectors, such as cameras, and produces a vehicle control output, such as a steering wheel angle to navigate the vehicle safely in a roadway traffic environment. Typically, these DNN-based systems in the autonomous vehicle are trained through supervised learning; however, recent studies show that a trained DNN-based system can be compromised by perturbation or adverse inputs. Similarly, this perturbation can be introduced into the DNN-based systems of autonomous vehicles by unexpected roadway hazards, such as debris or roadblocks. In this study, we first introduce a hazardous roadway environment that can compromise the DNN-based navigational system of an autonomous vehicle, and produce an incorrect steering wheel angle, which could cause crashes resulting in fatality or injury. Then, we develop a DNN-based autonomous vehicle driving system using object detection and semantic segmentation to mitigate the adverse effect of this type of hazard, which helps the autonomous vehicle to navigate safely around such hazards. We find that our developed DNN-based autonomous vehicle driving system, including hazardous object detection and semantic segmentation, improves the navigational ability of an autonomous vehicle to avoid a potential hazard by 21% compared with the traditional DNN-based autonomous vehicle driving system.

scholarly journals Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Flow Model ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transformation Model ◽  
Hydrodynamic Theory ◽  
Traffic Flow Model ◽  
Traffic System ◽  
The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

A novel path tracking approach considering safety of the intended functionality for autonomous vehicles

2021 ◽  
pp. 095440702110205
Author(s):  
Huiran Wang ◽  
Qidong Wang ◽  
Wuwei Chen ◽  
Linfeng Zhao ◽  
Dongkui Tan
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Coordinated Control ◽  
Steering System ◽  
Front Wheel ◽  
Path Tracking ◽  
Hierarchical Architecture ◽  
Automatic Steering ◽  
The Stability ◽  
Control Layer

To reduce the adverse effect of the functional insufficiency of the steering system on the accuracy of path tracking, a path tracking approach considering safety of the intended functionality is proposed by coordinating automatic steering and differential braking in this paper. The proposed method adopts a hierarchical architecture consisting of a coordinated control layer and an execution control layer. In coordinated control layer, an extension controller considering functional insufficiency of the steering system, tire force characteristics and vehicle driving stability is proposed to determine the weight coefficients of automatic steering and the differential braking, and a model predictive controller is designed to calculate the desired front wheel angle and additional yaw moment. In execution control layer, a H∞ steering angle controller considering external disturbances and parameter uncertainty is designed to track desired front wheel angle, and a braking force distribution module is used to determine the wheel cylinder pressure of the controlled wheels. Both simulation and experiment results show that the proposed method can overcome the functional insufficiency of the steering system and improve the accuracy of path tracking while maintaining the stability of the autonomous vehicle.

Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092110
Author(s):  
Runqiao Liu ◽  
Minxiang Wei ◽  
Nan Sang
Keyword(s):  
Obstacle Avoidance ◽  
Disturbance Rejection ◽  
Autonomous Vehicles ◽  
High Speed ◽  
Autonomous Vehicle ◽  
Angular Frequency ◽  
Vehicle Speed ◽  
Feed Forward ◽  
Yaw Rate ◽  
Active Disturbance Rejection

To solve the problem of understeer and oversteer for autonomous vehicle under high-speed emergency obstacle avoidance conditions, considering the effect of steering angular frequency and vehicle speed on yaw rate for four-wheel steering vehicles in the frequency domain, a feed-forward controller for four-wheel steering autonomous vehicles that tracks the desired yaw rate is proposed. Furthermore, the steering sensitivity coefficient of the vehicle is compensated linearly with the change in the steering angular frequency and vehicle speed. In addition, to minimize the tracking errors caused by vehicle nonlinearity and external disturbances, an active disturbance rejection control feedback controller that tracks the desired lateral displacement and desired yaw angle is designed. Finally, CarSim® obstacle avoidance simulation results show that an autonomous vehicle with the four-wheel steering path tracking controller consisting of feed-forward control and feedback control could not only improve the tire lateral forces but also reduce tail flicking (oversteer) and pushing ahead (understeer) under high-speed emergency obstacle avoidance conditions.

Comparative Analysis of MacAdam Model and PI Control in a Predictive Driver Model

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
C. Dias ◽  
J. Landre ◽  
P. Americo ◽  
M. Campolina ◽  
L. Marino Marino ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Longitudinal Velocity ◽  
Pi Controller ◽  
Driver Model ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Reference Path ◽  
Double Lane Change

Autonomous vehicles are the future of automotive engineering and understanding how this systems work is critical. In these vehicles, controller models are usually needed to generate signals that would normally be imposed by the driver e.g., steering angles, acceleration inputs and braking commands. Intuitively, each control method utilized has its peculiarities and presents different behaviours. In such situation, this paper aims to develop an error comparison between a car displacement and its reference path due the use of two different predictive driver controllers: The proportional-integrative and the MacAdam model. For this purpose, a 14 degrees of freedom vehicle model is used with the aid of MATLAB Simulink, whereas simulations were made using the double-lane change manoeuvre, a commonly used manoeuvre to analyse the vehicle dynamics performance. At the end of this paper, lateral acceleration, displacement and steering wheel angle analysis led the conclusion that the vehicle behaviour is smoother with the use of the proportional-integrative control regardless of longitudinal velocity. Nevertheless, the trajectory error is smaller for MacAdam model than PI controller is and therefore it is easier to follow the reference path with this one, although in aggressive maneuverers it can cause more discomfort and increase the risk of rolling when compared to the PI controller in a vehicle with the same body stiffness.

Application of Error Analysis Method in the Complex Vehicle Model

2012 ◽  
Vol 591-593 ◽  
pp. 584-587
Author(s):  
Shui Rong Liao ◽  
Tao Yang
Keyword(s):  
Error Analysis ◽  
Degrees Of Freedom ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Model Parameters ◽  
Vehicle Model ◽  
Two Degrees Of Freedom ◽  
Input Amplitude ◽  
Sinusoidal Input ◽  
Set Up

A two degree of freedom input vehicle model is set up. Based on driver modeling analytical method of error analysis, step signal is taken as the input of steering angle to complex vehicle model based on CarSim, vehicle lateral acceleration is taken as as output. Meanwhile, the same steering wheel angle is taken as input as equivalent two degrees of freedom vehicle model, vehicle model parameters are optimized based on the minimum objective function. The results show that, in the same kind of speed, for steering wheel angle step input and sinusoidal input , when the input amplitude increases, the equivalent accuracy of the complex vehicle model and two degrees of freedom vehicle model will be reduced.

Effect of Tractor-Semitrailer Velocity on Cornering Braking Stability

2014 ◽  
Vol 697 ◽  
pp. 334-339
Author(s):  
Chen Li ◽  
Shang Bin Song ◽  
Ge Teng Tang ◽  
Hui Qi Shi
Keyword(s):  
Dynamic Model ◽  
Model Simulation ◽  
Lateral Acceleration ◽  
Vehicle Speed ◽  
Initial Speed ◽  
Model Output ◽  
Yaw Rate ◽  
Braking Distance ◽  
Braking Process ◽  
The Stability

A dynamic model of tractor-semitrailer cornering braking was established in this paper. The accuracy of the model was tested and verified by comparing model output with data of tractor-semitrailer test. By model simulation of the cornering braking process, initial speed such as 20km/h, 25km/h, 30km/h, 35km/h, 40km/h was chosen to analyzed the changing curve of braking distance, articulation angle, yaw rate and lateral acceleration. The result shows that during cornering braking of tractor-semitrailer, with the increasing of initial speed, braking distance greatly increased, articulation angle, yaw rate and lateral acceleration are all increasing. Thus, when braking in a turn, the vehicle speed must be reduced to ensure the stability of tractor-semitrailer cornering braking.

Research on Stability Simulation for Four-Wheel Independent Steering Electric Vehicle

2012 ◽  
Vol 512-515 ◽  
pp. 2657-2661
Author(s):  
Zhi Jun Deng ◽  
Zhu Rong Dong
Keyword(s):  
Electric Vehicle ◽  
Feedforward Control ◽  
Dynamics Simulation ◽  
Lateral Acceleration ◽  
Vehicle Speed ◽  
Vehicle Model ◽  
Sideslip Angle ◽  
Yaw Rate ◽  
Tracking Ability ◽  
Approximate Zero

Handling dynamic model is established for the four-wheel independent steering electric vehicle (4WISEV) that has been developed by our research group. Handling dynamics simulation is conducted under Matlab environment with the parameters of the vehicle model, including the yaw rate, the lateral acceleration and the vehicle sideslip angle time domain and frequency domain characteristic simulation. Through analyzing the simulation results, it is indicated that, by adopting the feedforward control of the front steer angle and the feedback control of the yaw rate and vehicle speed which enable the vehicle sideslip angle to approximate zero, 4WISEV can effectively increase the handling stability of the vehicle and the tracking ability during steering process.

Research on Variable Steering Ratio of Vehicle Steer-by-Wire System Based on Joystick

2013 ◽  
Vol 336-338 ◽  
pp. 1037-1040 ◽  
Author(s):  
Hong Yu Zheng ◽  
Bing Yu Wang ◽  
Chang Fu Zong
Keyword(s):  
High Speed ◽  
Control Algorithm ◽  
Steering Wheel ◽  
Vehicle Speed ◽  
Vehicle Model ◽  
Steering Angle ◽  
Low Speed ◽  
Steer By Wire ◽  
Wire System

In the steer by wire system of vehicle, a joystick can instead of the steering wheel. A control algorithm based on variable steering ratio is developed on the basis of vehicle speed and joystick steering angle. By verifying the control algorithm with the vehicle model from CarSim, it shows that this proposed algorithm can effective carry out steering intention of drivers, which enhance the steer comfort in low speed driving and steer handling in high speed driving and effectively improve the vehicle maneuverability.

A Prototype Steering Weave Stabilizer for Automobiles

1991 ◽  
Vol 113 (1) ◽  
pp. 138-142 ◽  
Author(s):  
J. C. Whitehead
Keyword(s):  
High Speed ◽  
Steering System ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Phase Lag ◽  
Vehicle Speed ◽  
Control Torque ◽  
Concentrated Mass ◽  
Wheel Rim ◽  
The Difference

A prototype high-speed steering stabilizer for automobiles applies transient steering torques so that the sum of natural steering restoring torque and the control torque is more nearly in phase with steer angle than the natural restoring torque alone. The resulting reduction in the phase lag from steer angle to restoring torque mitigates the steering weave mode. Since steering restoring torque is nearly proportional to vehicle lateral acceleration, weave controller circuitry could subtract instantaneous lateral acceleration from expected steady-state lateral acceleration calculated from steer angle and vehicle speed, and thence command a steering torque actuator depending on the difference signal. The prototype performs the same function using a concentrated mass on the lower steering wheel rim which is passively sensitive to both steer angle and lateral acceleration, thereby applying only transient steering torques in the desired manner at a vehicle speed of 30 m/s. The additional steering system inertia alone affects the weave mode, so a non-stabilizing configuration with the same mass distributed around the steering wheel rim is tested for direct comparison. The experimental data show a dramatic stabilization of weave for the configuration which applies control torque.

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