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

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.

Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior

Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, effectively improves the performance of distracted drivers. Recently, adaptive shared steering control based on the forearm muscle activity of the driver has been developed, although its effect on distracted driver behavior remains unclear. To this end, a high-fidelity driving simulator experiment was conducted involving 18 participants performing double lane change tasks. The experimental conditions comprised two driver states: attentive and distracted. Under each condition, evaluations were performed on three types of haptic guidance: none (manual), fixed authority, and adaptive authority based on feedback from the forearm surface electromyography of the driver. Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority. Moreover, there was a tendency for distracted drivers to reduce grip strength on the steering wheel to follow the haptic guidance with fixed authority, resulting in a relatively shorter double lane change duration.

Designing LQR Controllers for an Active Anti-roll Bar System with a Flexible Frame Model of a Single Unit Heavy Vehicle

Rollover accidents of heavy vehicles often cause serious consequences both in terms of vehicle and environmental damage as well the loss or injury of drivers, passengers and ordinary civilians. Currently, the active anti-roll bar system is considered as the most effective solution in enhancing vehicle roll stability. In this paper, we firstly investigated the role of a flexible frame of a single unit heavy vehicle in the rollover process. This approach is an important step forward in the research of the active anti-roll bar system. Then, the LQR control method is applied in designing controllers for the active anti-roll bar control system with this frame model. The active torque of the anti-roll bar system is considered as the control signal. The simulation results in the frequency and time domains with a double lane change maneuver show that the vehicle’s roll stability is improved by over 30 % compared to a vehicle using a passive anti-roll bar system.

Lane-deviation penalty formulation and analysis for autonomous vehicle avoidance maneuvers

Autonomous vehicles hold promise for increased vehicle and traffic safety, and there are several developments in the field where one example is an avoidance maneuver. There it is dangerous for the vehicle to be in the opposing lane, but it is safe to drive in the original lane again after the obstacle. To capture this basic observation, a lane-deviation penalty (LDP) objective function is devised. Based on this objective function, a formulation is developed utilizing optimal all-wheel braking and steering at the limit of road–tire friction. This method is evaluated for a double lane-change scenario by computing the resulting behavior for several interesting cases, where parameters of the emergency situation such as the initial speed of the vehicle and the size and placement of the obstacle are varied, and it performs well. A comparison with maneuvers obtained by minimum-time and other lateral-penalty objective functions shows that the use of the considered penalty function decreases the time that the vehicle spends in the opposing lane.

Robust trajectory tracking control for autonomous vehicle subject to velocity-varying and uncertain lateral disturbance

Autonomous vehicles are the most advanced intelligent vehicles and will play an important role in reducing traffic accidents, saving energy and reducing emission. Motion control for trajectory tracking is one of the core issues in the field of autonomous vehicle research. According to the characteristics of strong nonlinearity, uncertainty and chang-ing longitudinal velocity for autonomous vehicles at high speed steering condition, the robust trajectory tracking control is studied. Firstly, the vehicle system models are established and the novel target longitudinal velocity planning is carried out. This velocity planning method can not only ensure that the autonomous vehicle operates in a strong nonlinear coupling state in bend, but also easy to be constructed. Then, taking the lateral location deviation minimiz-ing to zero as the lateral control objective, a robust active disturbance rejection control path tracking controller is designed along with an extended state observer which can deal with the varying velocity and uncertain lateral dis-turbance effectively. Additionally, the feedforward-feedback control method is adopted to control the total tire torque, which is distributed according to the steering characteristics of the vehicle for additional yaw moment to enhance vehicle handing stability. Finally, the robustness of the proposed controller is evaluated under velocity-varying condi-tion and sudden lateral disturbance. The single-lane change maneuver and double-lane change maneuver under vary longitudinal velocity and different road adhesions are both simulated. The simulation results based on Matlab/Simulink show that the proposed controller can accurately observe the external disturbances and have good performance in trajectory tracking and handing stability. The maximum lateral error reduces by 0.18 meters compared with a vehicle that controlled by a feedback-feedforward path tracking controller in the single-lane change maneuver. The lateral deviation is still very small even in the double lane change case of abrupt curvature. It should be noted that our proposed control algorithm is simple and robust, thus provide great potential for engineering application.

A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving

This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper, we develop two frameworks to solve this problem based on distributed model predictive control (MPC). The first approach solves a single nonlinear MPC problem. The general idea is to introduce a collision cost function in the optimization problem at the planning task to achieve a smooth and bounded collision function, and thus to prevent the need to implement tight hard constraints. The second method uses a hierarchical scheme with two main units: a trajectory-planning layer based on mixed-integer quadratic program (MIQP) computes an on-line collision-free trajectory using simplified motion dynamics, and a tracking controller unit to follow the trajectory from the higher level using the nonlinear vehicle model. Connected and automated vehicles (CAVs) sharing their planned trajectories lay the foundation of the cooperative behavior. In the tests and evaluation of the proposed methodologies, matlab-carsim cosimulation is utilized. carsim provides the high-fidelity model for the multibody vehicle dynamics. matlab-carsim conjoint simulation experiments compare both approaches for a cooperative double lane change maneuver of two vehicles moving along a one-way three-lane road with obstacles.

Optimization of vehicle suspension parameters based on ride comfort and stability requirements

The use of optimization methods in engineering is growing, allowing the best possible way to fulfill the requirements of the project. For vehicle suspensions, there are various conditions, which involve comfort, safety, stability, maneuverability, among others. A safety and stability evaluation is carried out by several tests, including Double Lane Change. In this maneuver, the vehicle must change lanes quickly twice, allowing it to be assessed for stability in sudden movements. For ride comfort, it is common for the design to be based on the vehicle’s natural vibration frequencies. In this context, this work aims to present a methodology for optimizing the suspension parameters of a vehicle, based on the natural frequencies of vibration and the simulation of a Double Lane Change maneuver. For that, it is employed vertical and lateral dynamics mathematical models, with hypotheses that allow the adequate adaptation to the represented phenomena. Finally, Particle Swarm Optimization (PSO) is used, which is a stochastic algorithm, based on nature. It has low computational cost, with reasonable results, allowing the parameters to be estimated and comprising the two objectives simultaneously.

Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control (MPC) schemes and robust A state feedback control (RSC) method for trajectory tracking, is proposed in this paper. Both MPC-based and RSC-based tracking controllers are designed on the basis of a 3-DOF vehicle model, including longitudinal, lateral and yaw motions. The main objective of this paper is to compare both controllers’ performance in tracking expected trajectory under different scenarios. Therefore, three cases, namely, verification test, double lane change test and curve test, were built in Carsim-Simulink joint platform. The simulation results indicate that MPC controller performed better in terms of accuracy and responding time under well driving conditions. However, in the test of double lane change manoeuvre where the road adhesion was set as 0.2, the maximum velocity RSC can execute was 14m/s, while that for MPC was 10m/s. In addition, in the curve test, the maximum velocity MPC can carry out was only 9m/s and that for RSC was 12m/s. In conclusion, RSC was robust and stable when the driving conditions was worse, while MPC was prone to be unstable.

Self-weight and Durability Analysis of Bus Body Structure using Finite Element Analysis

Self-weight and durability analysis of non-airconditioned sleeper bus has been carried in present work. Automotive industry standards (052 and 119) are used to freeze bus dimensions. Generative surface design is used in preparation to compute model. The bus superstructure behaviour is simulated for load on cant and waist rails for self-weight analysis. Bump analysis is carried out considering total failure of suspension system. Behaviour of bus during bump is simulated for two situations i.e. bump focre applied to front left wheel suspension location and all other suspension locations are fixed and force applied to front two wheel suspension locations and rear two wheel suspension locations are fixed. Behaviour of bus under torsional load for two cases viz first, force is applied to left of front suspension location in upward direction and other on to right suspension location in downward direction while the rear wheel suspension points are fixed and in second case, force is applied to left of front suspension in upward direction while the second one is applied to right in rear suspension location. Braking and double lane change load conditions are simulated with a braking efficiency of 80% and a lateral load of magnitude 0.4g is evaluated. Durability of the bus based on outcomes from braking, bump, torsional and double-lane change road-load situations is evaluated. The stress and deflection magnitudes are in good agreement with the results available in literature.