J. Reviejo

Adaptive fuzzy control for inter-vehicle gap keeping

There is a broad range of diverse technologies under the generic topic of intelligent transportation systems (ITS) that holds the answer to many of the transportation problems. In this paper, one approach to ITS is presented. One of the most important research topics in this field is adaptive cruise control (ACC). The main features of this kind of controller are the adaptation of the speed of the car to a predefined one and the keeping of a safe gap between the controlled car and the preceding vehicle on the road. We present an ACC controller based on fuzzy logic, which assists the speed and distance vehicle control, offering driving strategies and actuation over the throttle of a car. The driving information is supplied by the car tachometer and a RTK differential GPS, and the actuation over the car is made through an electronic interface that simulates the electrical signal of the accelerator pedal directly to the onboard computer. This control is embedded in an automatic driving system installed in two testbed mass-produced cars instrumented for testing the work of these controllers in a real environment. The results obtained in these experiments show a very good performance of the gap controller, which is adaptable to all the speeds and safe gap selections.

Vision-based adaptive cruise control for intelligent road vehicles

There is a broad range of robotics technologies that are currently being applied to the generic topic of intelligent transportation systems (ITS). One of the most important research topics in this field is adaptive cruise control (ACC), aiming at adapting the vehicle speed to a predefined value while keeping a safe gap with regard to potential obstacles. For this purpose, a monocular vision system provides the distance between the ego vehicle and the preceding vehicle on the road. The complete system can be understood as a vision-based ACC controller, based on fuzzy logic, which assists the velocity vehicle control offering driving strategies and actuation over the throttle of a car. This controller is embedded in an automatic driving system installed in two testbed mass-produced cars operating in a real environment. The results obtained in these experiments show a very good performance of the vision-based gap controller, which is adaptable to all speeds and safe gap selections.

Frontal and lateral control for unmanned vehicles in urban tracks

This paper presents techniques, related experiments and real results (not simulations) performed with two unmanned vehicles. The test zone is a private circuit with the characteristics of an urban track. The vehicles are common mass-produced cars, provided with automatic actuators operating on the car controls (power-assisted steering and accelerator). These actuators work commanded by a fuzzy logic based control system. The input information to the control system is provided by three elements: high precision GNSS, car tachometer and a wireless network environment.

Fuzzy logic based lateral control for GPS map tracking

The automatic control of the speed and the steering of a vehicle are two of the main steps in order to develop autonomous intelligent vehicles. In this paper, a development of steering control for automated cars based on fuzzy logic and its related field tests are presented. Artificial intelligence techniques are used for controlling a broad range of systems, trying to emulate the human behaviour when classical control models are too much complex and require a lot of design time. Particularly, fuzzy logic control techniques are well proved success methods for managing systems where there appear to be limitations for classical control. Our control system has been installed in two Citroen Berlingo testbed vans whose steering wheel has been automated and can be controlled from a computer. The main sensorial input is a RTK DGPS that gives us positioning with one-centimeter precision. The results of the realized experiments show a human like system performance with adaption capability to any kind of track.

Vehicle fuzzy driving based on DGPS and vision

This document presents a fuzzy control application in the unmanned driving field. Two electric cars have been conveniently instrumented in order to transform them into platforms for automatic driving experiments. Onboard speed and steering fuzzy controllers are the core of the guiding system. Navigation is essentially DGPS-based providing obstacles detection and avoidance by means of artificial vision in a reactive manner.

A Throttle and Brake Fuzzy Controller: Towards the Automatic Car

It is known that the techniques under the topic of Soft Computing have a strong capability of learning and cognition, as well as a good tolerance to uncertainty and imprecision. Due to these properties they can be applied successfully to Intelligent Vehicle Systems. In particular Fuzzy Logic is very adequate to build qualitative (or linguistic) models, of many kinds of systems without an extensive knowledge of their mathematical models. The throttle and brake pedal and steering wheel, are the most important actuators for driving. The aim of this paper is to integrate in a qualitative model the vehicle operation and the driver behavior in such a way that an unmanned guiding system can be developed around it [1] [2]. The automation of both pedals permits to direct the speed control from a computer and so, to automate several driving functions such as speed adaption, emergency brake, optimum speed selection, safe headway maintenance, etc. The building and design of fuzzy controllers for automatic driving is based on the drivers’ know-how and experience and the study of their behavior in maneuvers. The use of fuzzy controllers allows achieving a human like vehicle operation. The results of this research show a good performance of fuzzy controllers that behave in a very human way, adding the precision data from a DGPS source, and the safety of a driver without human lacks such as tiredness, sensorial defects or aggressive standings.

A new manipulator structure for power‐assist devices

Purpose – The purpose of this paper is to introduce a new manipulator structure to configure power‐assist devices in order to protect the operator from suffering musculoskeletal disorders. The mechanical structure and the control system along with their main features are presented.Design/methodology/approach – The new structure was designed under the criterion of minimizing the torques required for handling payloads up to 75 kg as well as to configure a system to be controlled easily.Findings – A new structure based on electrical AC motors and capable of handling high payloads exerting low motor torque is provided.Originality/value – The paper describes how application of the criterion of minimizing the required torques to handle heavy payload produced a new manipulator structure. This structure is patent protected.

Attitude and altitude control using discontinuous gaits for walking machines

Principles of legged locomotion have been established in the previous years. At present, many mathematical problems have been studied and solved; but in the implementation of this knowledge, new real problems have appeared. Flexion on links and joints and terrain compression introduce some undesirable characteristics in the system. These phenomena are not easy to model; therefore, sensors should be used. This paper deals with the implementation of attitude/altitude control on a walker. The main scope is to perform control using non-sophisticated sensors such as contact sensors, inclinometers, and joint position sensor. This paper describes the algorithms and the experimental results obtained working on a four legged walking machine.<<ETX>>

An open frame to test techniques and equipment for autonomous vehicles

Abstract In order to develop techniques, strategies, equipment, etc. for autonomous vehicles, an infrastructure consisting of a private street network, two electric cars with onboard computer, sensors and actuators, an aerial communications network, a very accurate DGPS, and software modules, such as the fuzzy control processor, has been mounted at the Instituto de Automatica Industrial. This paper concerns such infrastructure and its application.

Automatic Control of a Large Articulated Vehicle

This work presents the development of the automatic control of an articulated bus. It is describes the most relevant concepts of the architecture of perception and actuation implemented on a large wheeled vehicle, Volvo B10M articulated bus of 18.75m in length. In this work, some experimental results of strategies for lateral and longitudinal control of the bus are shown, when it travels on a guide rail through a guiding mechatronics box. Additionally, this article presents the concepts of the guiding rail detection and obstacle detection by means of two Lidar systems for the test lane detection in advance, and for the pedestrians’ safety, respectively. Several experimental results are presented in this manuscript.