MPC-based path tracking with PID speed control for high-speed autonomous vehicles considering time-optimal travel

AbstractIt is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions. In this study, an adaptive path tracking control strategy that coordinates active front wheel steering and direct yaw moment is proposed based on model predictive control algorithm. The recursive least square method with a forgetting factor is used to identify the rear tire cornering stiffness and update the path tracking system prediction model. To adaptively adjust the priorities of path tracking accuracy and vehicle stability, an adaptive strategy based on fuzzy rules is applied to change the weight coefficients in the cost function. An adaptive control strategy for coordinating active front steering and direct yaw moment is proposed to improve the path tracking accuracy under high-speed and large-curvature conditions. To ensure vehicle stability, the sideslip angle, yaw rate and zero moment methods are used to construct optimization constraints based on the model predictive control frame. It is verified through simulation experiments that the proposed adaptive coordinated control strategy can improve the path tracking accuracy and ensure vehicle stability under high-speed and large-curvature conditions.

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High speed path tracking application in harsh conditions: Predictive speed control to restrict the lateral deviation to some threshold

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2016.7759478 ◽

2016 ◽

Author(s):

Jean-Baptiste Braconnier ◽

Roland Lenain ◽

Benoit Thuilot ◽

Vincent Rousseau

Keyword(s):

High Speed ◽

Speed Control ◽

Path Tracking ◽

Lateral Deviation ◽

Harsh Conditions

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An Improved Kinematic Model Predictive Control for High-Speed Path Tracking of Autonomous Vehicles

IEEE Access ◽

10.1109/access.2020.2980188 ◽

2020 ◽

Vol 8 ◽

pp. 51400-51413 ◽

Cited By ~ 3

Author(s):

Luqi Tang ◽

Fuwu Yan ◽

Bin Zou ◽

Kewei Wang ◽

Chen Lv

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Autonomous Vehicles ◽

High Speed ◽

Kinematic Model ◽

Path Tracking

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Multi-fidelity black-box optimization for time-optimal quadrotor maneuvers

The International Journal of Robotics Research ◽

10.1177/02783649211033317 ◽

2021 ◽

pp. 027836492110333

Author(s):

Gilhyun Ryou ◽

Ezra Tal ◽

Sertac Karaman

Keyword(s):

Real World ◽

High Speed ◽

Analytical Approximation ◽

Black Box ◽

Bayesian Optimization ◽

Optimization Framework ◽

Quadrotor Aircraft ◽

Time Optimal ◽

Feasibility Constraints ◽

Generation Problem

We consider the problem of generating a time-optimal quadrotor trajectory for highly maneuverable vehicles, such as quadrotor aircraft. The problem is challenging because the optimal trajectory is located on the boundary of the set of dynamically feasible trajectories. This boundary is hard to model as it involves limitations of the entire system, including complex aerodynamic and electromechanical phenomena, in agile high-speed flight. In this work, we propose a multi-fidelity Bayesian optimization framework that models the feasibility constraints based on analytical approximation, numerical simulation, and real-world flight experiments. By combining evaluations at different fidelities, trajectory time is optimized while the number of costly flight experiments is kept to a minimum. The algorithm is thoroughly evaluated for the trajectory generation problem in two different scenarios: (1) connecting predetermined waypoints; (2) planning in obstacle-rich environments. For each scenario, we conduct both simulation and real-world flight experiments at speeds up to 11 m/s. Resulting trajectories were found to be significantly faster than those obtained through minimum-snap trajectory planning.

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

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/09544070211020535 ◽

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.

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Prototype Design and Experimental Evaluation of Autonomous Collaborative Communication System for Emerging Maritime Use Cases

Sensors ◽

10.3390/s21113871 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3871

Author(s):

Jiri Pokorny ◽

Khanh Ma ◽

Salwa Saafi ◽

Jakub Frolka ◽

Jose Villa ◽

...

Keyword(s):

Communication System ◽

Autonomous Vehicles ◽

High Speed ◽

High Capacity ◽

Workplace Safety ◽

Unmanned Vehicles ◽

Use Cases ◽

Automated Systems ◽

Collaborative Communication ◽

Wide Range

Automated systems have been seamlessly integrated into several industries as part of their industrial automation processes. Employing automated systems, such as autonomous vehicles, allows industries to increase productivity, benefit from a wide range of technologies and capabilities, and improve workplace safety. So far, most of the existing systems consider utilizing one type of autonomous vehicle. In this work, we propose a collaboration of different types of unmanned vehicles in maritime offshore scenarios. Providing high capacity, extended coverage, and better quality of services, autonomous collaborative systems can enable emerging maritime use cases, such as remote monitoring and navigation assistance. Motivated by these potential benefits, we propose the deployment of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV) in an autonomous collaborative communication system. Specifically, we design high-speed, directional communication links between a terrestrial control station and the two unmanned vehicles. Using measurement and simulation results, we evaluate the performance of the designed links in different communication scenarios and we show the benefits of employing multiple autonomous vehicles in the proposed communication system.

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