Towards Autonomous Driving At The Limit Of Friction
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Towards Autonomous Driving at the Limit of Friction
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.
Autonomous Vehicle Maneuvering at the Limit of Friction
Author: Victor Fors
language: en
Publisher: Linköping University Electronic Press
Release Date: 2020-10-23
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.
Unsettled Issues in Determining Appropriate Modeling Fidelity for Automated Driving Systems Simulation
This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the challenges of achieving optimal model fidelity for developing, validating, and verifying vehicles capable of automated driving. Three main issues are outlined that merit immediate interest: First, assuring that simulation models represent their real-world counterparts, how to quantify simulation model fidelity, and how to assess system risk. Second, developing a universal simulation model interface and language for verifying, simulating, and calibrating automated driving sensors. Third, characterizing and determining the different requirements for sensor, vehicle, environment, and human driver models. SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report need to be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed; second, prioritizing the issues requiring resolution; and, third, creating a plan to generate the necessary frameworks, practices, and protocols. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019007