238 resultados para autonomous intelligent systems


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In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

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This paper discusses a method to quantify robust autonomy of Uninhabited Vehicles and Systems (UVS) in aerospace, marine, or land applications. Based on mission-vehicle specific performance criteria, we define an system utility function that can be evaluated using simulation scenarios for an envelope of environmental conditions. The results of these evaluations are used to compute a figure of merit or measure for operational efectiveness (MOE). The procedure is then augmented to consider faults and the performance of mechanisms to handle these faulty operational modes. This leads to a measure of robust autonomy (MRA). The objective of the proposed figures of merit is to assist in decision making about vehicle performance and reliability at both vehicle development stage (using simulation models) and at certification stage (using hardware-in-the-loop testing). Performance indices based on dynamic and geometric tasks associated with vehicle manoeuvring problems are proposed, and an example of a two- dimensional y scenario is provided to illustrate the use of the proposed figures of merit.

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This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

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This paper presents an object-oriented world model for the road traffic environment of autonomous (driver-less) city vehicles. The developed World Model is a software component of the autonomous vehicle's control system, which represents the vehicle's view of its road environment. Regardless whether the information is a priori known, obtained through on-board sensors, or through communication, the World Model stores and updates information in real-time, notifies the decision making subsystem about relevant events, and provides access to its stored information. The design is based on software design patterns, and its application programming interface provides both asynchronous and synchronous access to its information. Experimental results of both a 3D simulation and real-world experiments show that the approach is applicable and real-time capable.

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Intelligent Transport System (ITS) technology is seen as a cost-effective way to increase the conspicuity of approaching trains and the effectiveness of train warnings at level crossings by providing an in-vehicle warning of an approaching train. The technology is often seen as a potential low-cost alternative to upgrading passive level crossings with traditional active warning systems (flashing lights and boom barriers). ITS platforms provide sensor, localization and dedicated short-range communication (DSRC) technologies to support cooperative applications such as collision avoidance for road vehicles. In recent years, in-vehicle warning systems based on ITS technology have been trialed at numerous locations around Australia, at level crossing sites with active and passive controls. While significant research has been conducted on the benefits of the technology in nominal operating modes, little research has focused on the effects of the failure modes, the human factors implications of unreliable warnings and the technology adoption process from the railway industry’s perspective. Many ITS technology suppliers originate from the road industry and often have limited awareness of the safety assurance requirements, operational requirements and legal obligations of railway operators. This paper aims to raise awareness of these issues and start a discussion on how such technology could be adopted. This paper will describe several ITS implementation cenarios and discuss failure modes, human factors considerations and the impact these scenarios are likely to have in terms of safety, railway safety assurance requirements and the practicability of meeting these requirements. The paper will identify the key obstacles impeding the adoption of ITS systems for the different implementation scenarios and a possible path forward towards the adoption of ITS technology.

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Safety at railway level crossings (RLX) is one part of a wider picture of safety within the whole transport system. Governments, the rail industry and road organisations have used a variety of countermeasures for many years to improve RLX safety. New types of interventions are required in order to reduce the number of crashes and associated social costs at railway crossings. This paper presents the results of a large research program which aimed to assess the effectiveness of emerging Intelligent Transport Systems (ITS) interventions, both on-road and in-vehicle based, to improve the safety of car drivers at RLXs in Australia. The three most promising technologies selected from the literature review and focus groups were tested in an advanced driving simulator to provide a detailed assessment of their effects on driver behaviour. The three interventions were: (i) in-vehicle visual warning using a GPS/smartphone navigation-like system, (ii) in-vehicle audio warning and; (iii) on-road intervention known as valet system (warning lights on the road surface activated as a train approaches). The effects of these technologies on 57 participants were assessed in a systematic approach focusing on the safety of the intervention, effects on the road traffic around the crossings and driver’s acceptance of the technology. Given that the ITS interventions were likely to provide a benefit by improving the driver’s awareness of the crossing status in low visibility conditions, such conditions were investigated through curves in the track before arriving at the crossing. ITS interventions were also expected to improve driver behaviour at crossings with high traffic (blocking back issue), which were also investigated at active crossings. The key findings are: (i) interventions at passive crossings are likely to provide safety benefits; (ii) the benefits of ITS interventions on driver behaviour at active crossings are limited; (iii) the trialled ITS interventions did not show any issues in terms of driver distraction, driver acceptance or traffic delays; (iv) these interventions are easy to use, do not increase driver workload substantially; (v) participants’ intention to use the technology is high and; (vi) participants saw most value in succinct messages about approaching trains as opposed to knowing the RLX locations or the imminence of a collision with a train.

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This thesis has developed a new approach to trace virtual protection signals in Electrical substation networks. The main goal of the research was to analyse the contents of the virtual signals transferred, using third party software. In doing so, a comprehensive test was done on a distance protection relay, using non-conventional test equipment.

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This paper provides a three-layered framework to monitor the positioning performance requirements of Real-time Relative Positioning (RRP) systems of the Cooperative Intelligent Transport Systems (C-ITS) that support Cooperative Collision Warning (CCW) applications. These applications exploit state data of surrounding vehicles obtained solely from the Global Positioning System (GPS) and Dedicated Short-Range Communications (DSRC) units without using other sensors. To this end, the paper argues the need for the GPS/DSRC-based RRP systems to have an autonomous monitoring mechanism, since the operation of CCW applications is meant to augment safety on roads. The advantages of autonomous integrity monitoring are essential and integral to any safety-of-life system. The autonomous integrity monitoring framework proposed necessitates the RRP systems to detect/predict the unavailability of their sub-systems and of the integrity monitoring module itself, and, if available, to account for effects of data link delays and breakages of DSRC links, as well as of faulty measurement sources of GPS and/or integrated augmentation positioning systems, before the information used for safety warnings/alarms becomes unavailable, unreliable, inaccurate or misleading. Hence, a monitoring framework using a tight integration and correlation approach is proposed for instantaneous reliability assessment of the RRP systems. Ultimately, using the proposed framework, the RRP systems will provide timely alerts to users when the RRP solutions cannot be trusted or used for the intended operation.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

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Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. Such systems, however, will only exert an influence on driving behaviour if they are accepted by the driver. This study aimed at assessing driver acceptance of different ITS interventions designed to enhance driver behaviour at railway crossings. Fifty eight participants, divided into three groups, took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver acceptance of each ITS intervention was assessed in a questionnaire guided by the Technology Acceptance Model and the Theory of Planned Behaviour. Overall, results indicated that the strongest intentions to use the ITS devices belonged to participants exposed to the road-based valet system at passive crossings. The utility of both models in explaining drivers’ intention to use the systems is discussed, with results showing greater support for the Theory of Planned Behaviour. Directions for future studies, along with strategies that target attitudes and subjective norms to increase drivers’ behavioural intentions, are also discussed.

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Adjustable speed induction generators, especially the Doubly-Fed Induction Generators (DFIG) are becoming increasingly popular due to its various advantages over fixed speed generator systems. A DFIG in a wind turbine has ability to generate maximum power with varying rotational speed, ability to control active and reactive by integration of electronic power converters such as the back-to-back converter, low rotor power rating resulting in low cost converter components, etc, DFIG have become very popular in large wind power conversion systems. This chapter presents an extensive literature survey over the past 25 years on the different aspects of DFIG. Application of H8 Controller for enhanced DFIG-WT performance in terms of robust stability and reference tracking to reduce mechanical stress and vibrations is also demonstrated in the chapter.