Christian Roberto Kelber

A Predictive Controller for Autonomous Vehicle Path Tracking

This paper presents a model predictive controller (MPC) structure for solving the path-tracking problem of terrestrial autonomous vehicles. To achieve the desired performance during high-speed driving, the controller architecture considers both the kinematic and the dynamic control in a cascade structure. Our study contains a comparative study between two kinematic linear predictive control strategies: The first strategy is based on the successive linearization concept, and the other strategy combines a local reference frame with an approaching path strategy. Our goal is to search for the strategy that best comprises the performance and hardware-cost criteria. For the dynamic controller, a decentralized predictive controller based on a linearized model of the vehicle is used. Practical experiments obtained using an autonomous ldquoMini-Bajardquo vehicle equipped with an embedded computing system are presented. These results confirm that the proposed MPC structure is the solution that better matches the target criteria.

Lane following and lane departure using a linear-parabolic model

This paper proposes a technique for unwanted lane departure detection. Initially, lane boundaries are detected using a combination of the edge distribution function and a modified Hough transform. In the tracking stage, a linear-parabolic lane model is used: in the near vision field, a linear model is used to obtain robust information about lane orientation; in the far field, a quadratic function is used, so that curved parts of the road can be efficiently tracked. For lane departure detection, orientations of both lane boundaries are used to compute a lane departure measure at each frame, and an alarm is triggered when such measure exceeds a threshold. Experimental results indicate that the proposed system can fit lane boundaries in the presence of several image artifacts, such as sparse shadows, lighting changes and bad conditions of road painting, being able to detect in advance involuntary lane crossings.

A lane departure warning system based on a linear-parabolic lane model

We propose a new lane departure warning system based on a linear-parabolic lane boundary model. A linear function is used to fit the near vision field, and a quadratic function fits the far field. The linear part of the model provides robust information about the orientation of the vehicle with respect to both lane boundaries, while the parabolic part is flexible enough to fit curved parts of the road. The orientation of both lane boundaries is then computed and used to anticipate lane crossings.

A robust linear-parabolic model for lane following

In this paper we address the problem of lane detection and lane tracking. A linear model is used to approximate lane boundaries in the first frame of a video sequence, using a combination of the edge distribution function and the Hough transform. A new linear-parabolic model is used in the subsequent frames: the linear part of the model is used to fit the near vision field, while the parabolic model fits the far field. The proposed technique demands low computational power and memory requirements, and showed to be robust in the presence of noise, shadows, lack of lane painting and change of illumination conditions.

A lane departure warning system using lateral offset with uncalibrated camera

In this paper, we propose an automatic method for determining the lateral offset of the vehicle with respect to the center of the lane. Initially, a linear-parabolic model is used to detect lane boundaries. The linear part of the model is then used to obtain an estimation of the lateral offset, without the knowledge of any intrinsic or extrinsic camera parameter. Finally, the analysis the offset across time is then used to determine a lane departure measure, allowing lane crossings to be detected in advance.

SEVA3D: Using Arti cial Neural Networks to Autonomous Vehicle Parking Control

This paper describes the simulation system proposed in order to study and to implement intelligent autonomous vehicle control. The developed system can automatically drive a vehicle, implementing a robust control system capable of simulating in a realistic way autonomous parking in a parallel parking space. The system controls the vehicles based on the reading of sonar sensors and uses a neural network to automatically generate acceleration and steering commands, parking it in a parallel parking space. The controller was implemented using a Jordan-Net based neural network, and the results obtained in our simulations demonstrated that the proposed controller is perfectly able to correctly park the vehicle in different situations.

An Improved Linear-Parabolic Model for Lane Following and Curve Detection

In this paper, we propose a new model for lane tracking and curve detection. We use a linear-parabolic model for each lane boundary, and apply constraints to link both lane boundaries based on the expected geometry of the road. The parabolic part of the model, which fits the far field, is then used to analyze the geometry of the road ahead (straight, right curve or left curve), with applications in driver’s assistance systems and road inspection. Experimental results indicate that introduced geometric constraints result in a more consistent fit if compared to the individual fitting of each lane boundary, and that the parabolic part of the model can be effectively used to keep the driver informed about the geometry of the road in front of him/her.

Electrical Drives in Intelligent Vehicles: Basis for Active Driver Assistance Systems

Drive-by-wire systems have been establishing the technological basis that is opening opportunities for the development of new driver assistance and safety systems, making it possible even for a computer to drive or park a car. Electrical drives represent the heart of such systems and are also becoming a trend in relation to distributed electrical traction systems in hybrid and electrical vehicles. This work presents an overview of electrical drives in intelligent vehicles. The article brings also a discussion about the reliability, production and maintenance costs of different types of electrical drives that can be used in such automotive applications.

Assistance controller for driving backwards and parking an articulated vehicle

Driving backwards and parking articulated vehicles represent a hard procedure also for skilled drivers. If a vehicle is semi-automated in a way that a computer can command the steering wheel, a driver assistance system may help the conductor to perform such maneuvers easily. This work presents a solution for this problem. A self constructed prototype was developed to analyze the effectiveness of the proposed control strategies that include a stabilizing controller for the joint angle and a path tracking controller. The results show that the stabilizing controller permits an untrained driver to steer the vehicle backwards by setting up the joint angle reference signal with an external human machine interface while the path tracking controller allows the vehicle to follow a predetermined route autonomously.

Project USO-unidentified swimming objects-using aquatic mobile robots in engineering education

In engineering education hands on teaching is becoming more and more important. To implement their knowledge obtained in different disciplines of the electrical engineering course such as analog and digital electronics, instrumentation and control systems, students from the 7/sup th/ semester and above have to implement the theoretical principles in an interdisciplinary laboratory prototype. Following this idea, some students projected and implemented the steering control of an unidentified swimming object (USO) constructed by themselves. In order to encourage creativity it was not necessary to construct a conventional boat but any kind of autonomous aquatic mobile robot that should follow a predetermined route on the lake situated on the campus. Interdisciplinary work and teamwork were encouraged. The assembled aquatic mobile robots, the mathematical analysis of the system plants and the development of a linear steering control strategy for these prototypes are presented in this article. Simulation and experimental results are also included.