873 resultados para Driver feedback
Resumo:
Some motor tasks can be completed, quite literally, with our eyes shut. Most people can touch their nose without looking or reach for an object after only a brief glance at its location. This distinction leads to one of the defining questions of movement control: is information gleaned prior to starting the movement sufficient to complete the task (open loop), or is feedback about the progress of the movement required (closed loop)? One task that has commanded considerable interest in the literature over the years is that of steering a vehicle, in particular lane-correction and lane-changing tasks. Recent work has suggested that this type of task can proceed in a fundamentally open loop manner [1 and 2], with feedback mainly serving to correct minor, accumulating errors. This paper reevaluates the conclusions of these studies by conducting a new set of experiments in a driving simulator. We demonstrate that, in fact, drivers rely on regular visual feedback, even during the well-practiced steering task of lane changing. Without feedback, drivers fail to initiate the return phase of the maneuver, resulting in systematic errors in final heading. The results provide new insight into the control of vehicle heading, suggesting that drivers employ a simple policy of “turn and see,” with only limited understanding of the relationship between steering angle and vehicle heading.
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This project examines the effects of age, experience, and video-based feedback on the rate and type of safety-relevant events captured on video event recorders in the vehicles of three groups of newly licensed young drivers: 1. 14.5- to 15.5-year-old drivers who hold a minor school license (see Appendix A for the provisions of the Iowa code governing minor school licenses); 2. 16-year-old drivers with an intermediate license who are driving unsupervised for the first time; 3. 16-year-old drivers with an intermediate license who previously drove unsupervised for at least four months with a school license. METHODS: The young drivers’ vehicles were equipped with an event-triggered video recording device for 24 weeks. Half of the participants received feedback regarding their driving, and the other half received no feedback at all and served as a control group. The number of safety-relevant events per 1,000 miles (i.e., “event rate”) was analyzed for 90 participants who completed the study. RESULTS: On average, the young drivers who received the video-based intervention had significantly lower event rates than those in the control group. This finding was true for all three groups. An effect of experience was seen for drivers in the control group; the 16-year-olds with driving experience had significantly lower event rates than the 16-year-olds without experience. When the intervention concluded, an increase in event rate was seen for the school license holders, but not for either group of 16-year-old drivers. There is strong evidence that giving young drivers video-based feedback, regardless of their age or level of driving experience, is effective in reducing the rate of safety-relevant events relative to a control group who do not receive feedback. Specific comparisons with regard to age and experience indicated that the age of the driver did not have an effect on the rate of safety-events, while experience did. Young drivers with six months or more of additional experience behind the wheel had nearly half as many safety-relevant events as those without that experience.
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Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. We assess the importance of microphysical processes for the negative optical depth feedback by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. We find that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, we show the existence of a very robust positive relationship between monthly-mean LWP and temperature in CMIP5 models and observations in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. We conclude that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.
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The thesis introduces a system dynamics Taylor rule model of new Keynesian nature for monetary policy feedback in Brazil. The nonlinear Taylor rule for interest rate changes con-siders gaps and dynamics of GDP growth and inflation. The model closely tracks the 2004 to 2011 business cycle and outlines the endogenous feedback between the real interest rate, GDP growth and inflation. The model identifies a high degree of endogenous feedback for monetary policy and inflation, while GDP growth remains highly exposed to exogenous eco-nomic conditions. The results also show that the majority of the monetary policy moves during the sample period was related to GDP growth, despite higher coefficients of inflation parameters in the Taylor rule. This observation challenges the intuition that inflation target-ing leads to a dominance of monetary policy moves with respect to inflation. Furthermore, the results suggest that backward looking price-setting with respect to GDP growth has been the dominant driver of inflation. Moreover, simulation exercises highlight the effects of the new BCB strategy initiated in August 2011 and also consider recession and inflation avoid-ance versions of the Taylor rule. In methodological terms, the Taylor rule model highlights the advantages of system dynamics with respect to nonlinear policies and to the stock-and-flow approach. In total, the strong historical fit and some counterintuitive observations of the Taylor rule model call for an application of the model to other economies.
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Transportation Systems Center, Cambridge, Mass.
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A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.
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In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.
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This paper analyzes the convergence of the constant modulus algorithm (CMA) in a decision feedback equalizer using only a feedback filter. Several works had already observed that the CMA presented a better performance than decision directed algorithm in the adaptation of the decision feedback equalizer, but theoretical analysis always showed to be difficult specially due to the analytical difficulties presented by the constant modulus criterion. In this paper, we surmount such obstacle by using a recent result concerning the CM analysis, first obtained in a linear finite impulse response context with the objective of comparing its solutions to the ones obtained through the Wiener criterion. The theoretical analysis presented here confirms the robustness of the CMA when applied to the adaptation of the decision feedback equalizer and also defines a class of channels for which the algorithm will suffer from ill-convergence when initialized at the origin.
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This paper considers two aspects of the nonlinear H(infinity) control problem: the use of weighting functions for performance and robustness improvement, as in the linear case, and the development of a successive Galerkin approximation method for the solution of the Hamilton-Jacobi-Isaacs equation that arises in the output-feedback case. Design of nonlinear H(infinity) controllers obtained by the well-established Taylor approximation and by the proposed Galerkin approximation method applied to a magnetic levitation system are presented for comparison purposes.
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Although the formulation of the nonlinear theory of H(infinity) control has been well developed, solving the Hamilton-Jacobi-Isaacs equation remains a challenge and is the major bottleneck for practical application of the theory. Several numerical methods have been proposed for its solution. In this paper, results on convergence and stability for a successive Galerkin approximation approach for nonlinear H(infinity) control via output feedback are presented. An example is presented illustrating the application of the algorithm.
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This work summarizes some results about static state feedback linearization for time-varying systems. Three different necessary and sufficient conditions are stated in this paper. The first condition is the one by [Sluis, W. M. (1993). A necessary condition for dynamic feedback linearization. Systems & Control Letters, 21, 277-283]. The second and the third are the generalizations of known results due respectively to [Aranda-Bricaire, E., Moog, C. H., Pomet, J. B. (1995). A linear algebraic framework for dynamic feedback linearization. IEEE Transactions on Automatic Control, 40, 127-132] and to [Jakubczyk, B., Respondek, W. (1980). On linearization of control systems. Bulletin del` Academie Polonaise des Sciences. Serie des Sciences Mathematiques, 28, 517-522]. The proofs of the second and third conditions are established by showing the equivalence between these three conditions. The results are re-stated in the infinite dimensional geometric approach of [Fliess, M., Levine J., Martin, P., Rouchon, P. (1999). A Lie-Backlund approach to equivalence and flatness of nonlinear systems. IEEE Transactions on Automatic Control, 44(5), 922-937]. (C) 2008 Elsevier Ltd. All rights reserved.
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Control of chaos in the single-mode optically pumped far-infrared (NH3)-N-15 laser is experimentally demonstrated using continuous time-delay control. Both the Lorenz spiral chaos and the detuned period-doubling chaos exhibited by the laser have been controlled. While the laser is in the Lorenz spiral chaos regime the chaos has been controlled both such that the laser output is cw, with corrections of only a fraction of a percent necessary to keep it there, and to period one. The laser has also been controlled while in the period-doubling chaos regime, to both the period-one and -two states.
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The free running linewidth of an external cavity grating feedback diode laser is on the order of a few megahertz and is limited by the mechanical and acoustic vibrations of the external cavity. Such frequency fluctuations can be removed by electronic feedback. We present a hybrid stabilisation technique that uses both a Fabry-Perot confocal cavity and an atomic resonance to achieve excellent short and long term frequency stability. The system has been shown to reduce the laser linewidth of an external cavity diode laser by an order of magnitude to 140 kHz, while limiting frequency excursions to 60 kHz relative to an absolute reference over periods of several hours. The scheme also presents a simple way to frequency offset two lasers many gigahertz apart which should find a use in atom cooling experiments, where hyperfine ground-state frequency separations are often required.
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The current study was designed to confirm that female drivers sit closer to the steering wheel than do male drivers and to investigate whether this expected difference in sitting position is attributable to differences in the physical dimensions of men and women. Driver body dimensions and multiple measures of sitting distance from the steering wheel were collected from a sample of 150 men and 150 women. The results confirmed that on average, women sit closer to the steering wheel than men do and that this difference is accounted for by variations in body dimensions, especially height. This result suggests that driver height may provide a good surrogate for sitting distance from the steering wheel when investigating the role of driver position in real-world crash outcomes. The potential applications of this research include change to vehicle design that allows independent adjustment of the relative distance among the driver's seat, the steering wheel, and the floor pedals.
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This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.