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Author : Thorsten Lajewski
Release : 2022
Genre :
Kind : eBook
Book Rating : 125/5 ( reviews)
Book Synopsis Friction Potential Estimation for Autonomous Driving by : Thorsten Lajewski
Download or read book Friction Potential Estimation for Autonomous Driving written by Thorsten Lajewski. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Victor Fors
Release : 2020-10-23
Genre : Electronic books
Kind : eBook
Book Rating : 706/5 ( reviews)
Book Synopsis Autonomous Vehicle Maneuvering at the Limit of Friction by : Victor Fors
Download or read book Autonomous Vehicle Maneuvering at the Limit of Friction written by Victor Fors. This book was released on 2020-10-23. Available in PDF, EPUB and Kindle. Book excerpt: Without a driver to fall back on, a fully self-driving car needs to be able to handle any situation it can encounter. With the perspective of future safety systems, this research studies autonomous maneuvering at the tire-road friction limit. In these situations, the dynamics is highly nonlinear, and the tire-road parameters are uncertain. To gain insights into the optimal behavior of autonomous safety-critical maneuvers, they are analyzed using optimal control. Since analytical solutions of the studied optimal control problems are intractable, they are solved numerically. An optimization formulation reveals how the optimal behavior is influenced by the total amount of braking. By studying how the optimal trajectory relates to the attainable forces throughout a maneuver, it is found that maximizing the force in a certain direction is important. This is like the analytical solutions obtained for friction-limited particle models in earlier research, and it is shown to result in vehicle behavior close to the optimal also for a more complex model. Based on the insights gained from the optimal behavior, controllers for autonomous safety maneuvers are developed. These controllers are based on using acceleration-vector references obtained from friction-limited particle models. Exploiting that the individual tire forces tend to be close to their friction limits, the desired tire slip angles are determined for a given acceleration-vector reference. This results in controllers capable of operating at the limit of friction at a low computational cost and reduces the number of vehicle parameters used. For straight-line braking, ABS can intervene to reduce the braking distance without prior information about the road friction. Inspired by this, a controller that uses the available actuation according to the least friction necessary to avoid a collision is developed, resulting in autonomous collision avoidance without any estimation of the tire–road friction. Investigating time-optimal lane changes, it is found that a simple friction-limited particle model is insufficient to determine the desired acceleration vector, but including a jerk limit to account for the yaw dynamics is sufficient. To enable a tradeoff between braking and avoidance with a more general obstacle representation, the acceleration-vector reference is computed in a receding-horizon framework. The controllers developed in this thesis show great promise with low computational cost and performance not far from that obtained offline by using numerical optimization when evaluated in high-fidelity simulation.
Author : Sirui Song
Release : 2014
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Towards Autonomous Driving at the Limit of Friction by : Sirui Song
Download or read book Towards Autonomous Driving at the Limit of Friction written by Sirui Song. This book was released on 2014. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous vehicles have become a reality, many vehicles have implemented some features to allow partial or full autonomy; however, full autonomous driving near the limit of friction still presents many obstacles, especially near the limit of friction. Autonomous test vehicles are expensive to build and maintain, running the vehicles usually requires highly specialized training, and testing can be dangerous. Research has shown that small sized scaled vehicles may be used as an alternative to full size vehicle testing. The first part of this thesis presents the construction of a 1=5th scaled vehicle testbed. This testbed is inexpensive to construct, easy to maintain, and safe to test compared to full size vehicles. In the linear region, the dynamic response of the tires also closely mimics full size tires and the Dugoff tire model. The small sized testbed is therefore an ideal alternative to full size vehicles. The interaction between the road and the tires remains a challenge to estimate, but a requirement for eff ective control. Tire dynamics are highly non-linear, and are dependent on many variables. Tire slip angles are di fficult to estimate without expensive sensors set-up. Many linear and non-linear estimation methods have been developed to tackle this problem, but each having its limitations. The second part of the thesis presents a method for slip angle estimation, and proposes an observer design which integrates a linear component with the Dugoff tire model and a pneumatic trail estimator. This design is fast to operate, and does not require expensive sensors. With the addition of the pneumatic trail block, accurate slip angles can be obtained in the tires linear and saturation regions equally. Controlling near the limit of friction requires consistently accurate tire states, which is di fficult to achieve with slip angles. With the margin of error under a degrees, a slight error in slip angle estimates while operating at the limit of friction may result in loss of control. The final contribution of this thesis proposes a simpli ed feedforward lateral controller based on the concept of Centre of Percussion (COP), and a longitudinal controller that operates based on lateral acceleration. This control scheme avoids using slip angles, but still pushes the vehicle performance to the limit of friction. The architecture is validated in high fi delity simulations.
Author : Kalyana Veluvolu
Release : 2020-12-01
Genre : Technology & Engineering
Kind : eBook
Book Rating : 174/5 ( reviews)
Book Synopsis Adaptive Vehicle Estimation and Control for Dynamic Road Conditions by : Kalyana Veluvolu
Download or read book Adaptive Vehicle Estimation and Control for Dynamic Road Conditions written by Kalyana Veluvolu. This book was released on 2020-12-01. Available in PDF, EPUB and Kindle. Book excerpt: Document from the year 2020 in the subject Engineering - Automotive Engineering, grade: 2, , language: English, abstract: Global chassis controller (GCC) design for autonomous vehicles relies on the information of the environmental factors, weather conditions, vehicle dynamics, actuation bandwidth, among others. Typically, various sensors and actuators are employed to provide such information. Challenges such as cost of sensors, actuator complexity and constraints, fail-safe operations, control authority allocation, and adaptability to a wide range of driving scenarios such as acceleration/ deceleration at set speed, double lane change, and driving on a circular path among others persist for design of such GCC architectures. Specifically for longitudinal-vertical vehicle controllers tuned to achieve safety and comfort objectives, the performance is significantly affected by the precise knowledge of road conditions i.e., tire friction and road elevation in the presence of nonlinearities such as aerodynamic drag, rolling resistance, spring and damper nonlinearities. For the longitudinal vehicle motion, tire-road friction conditions, aerodynamic forces, engine friction, and rolling nonlinearities critically affect the design of safety controllers such as traction control or active cruise control. Similarly, for vertical vehicle motion control using active suspension, the random road roughness and road defects, spring and damper nonlinearities, hydraulic actuator nonlinearities, and multi-objective design criteria, make design of controller a challenging task. With that motivation, the use cost effective virtual sensors to detect such external inputs and subsequent output feedback control solutions for the longitudinal-vertical autonomous vehicle motion is proposed in this book. The focus lies on adaptability of designed controllers and estimators to road friction conditions such as road conditions such as asphalt, snow, ice and the road elevation based on various rough roads and road defects.
Author : Juqi Hu
Release : 2021
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Tire-Road Friction Coefficient Estimation and Control of Autonomous Vehicles by : Juqi Hu
Download or read book Tire-Road Friction Coefficient Estimation and Control of Autonomous Vehicles written by Juqi Hu. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: This thesis aims to design and develop trajectory planning and tracking strategies integrating with the estimated tire-road friction coefficient (TRFC) so as to enhance the safety and reliability of the autonomous vehicles (AVs) under varying road friction conditions. A two-stage hierarchical framework is firstly developed for estimating TRFC in a computationally efficient manner considering vehicle's lateral dynamic responses to double (DLC) and single (SLC) lane-change maneuvers. An alternate two-stage TRFC estimation framework is developed further on the basis of the longitudinal dynamics of the vehicle. A sequence of braking pressure pulses is designed in the first stage to identify desired minimal pulse pressure needed for reliable estimation of TRFC with minimal interference with the vehicle motion. In the second stage, a constrained unscented Kalman filter (CUKF) algorithm is subsequently proposed to identify the precise TRFC for achieving rapid convergence and enhanced estimation accuracy. A trajectory planning scheme integrating the estimated TRFC is subsequently developed for path-change maneuvers considering both the maneuver safety and the occupant's comfort. For this purpose, a 7th-order polynomial function is constructed to ensure continuity up to the derivative of the acceleration (jerk). The friction-adaptive acceleration and speed-adaptive jerk limits are further defined and integrated in the framework to enhance occupant's comfort and acceptance. Both numerical simulation and Quanser self-driving car (QCar) experimental results have revealed the effectiveness and practicability of the proposed lane change trajectory planning scheme. An adaptive model predictive control (MPC) tracking scheme is proposed for tracking the desired lane-change path considering wide variations in vehicle speed and TRFC. With integrated consideration of output weights in the cost function together with constraints on the magnitude of the outputs, the proposed MPC scheme required only lateral position for tracking the planned path. An interesting way of integrating adaptive control gains with consideration of steering saturation by using the backstepping technique is also designed for low-speed AVs to enhance trajectory tracking, while respecting to the input boundaries. The effectiveness of the proposed tracking control scheme is verified experimentally using the QCar test platform.
