1,531 research outputs found

    Corbett, Clausewitz, and Sun Tzu

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    Mahan integrates and synthesizes Jomini’s work with his own; Corbett uses Clausewitz’s On War as a heuristic point of departure. Mahan, in his own words, remains loyal to Jomini’s ideas. In contrast, Corbett, although inspired by On War, develops ideas different from and sometimes contradictory to those of Clausewitz

    Smartphone-based vehicle telematics: a ten-year anniversary

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordJust as it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about automotive insurance, vehicle safety systems, and traffic research. This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone. Notable academic and industrial projects are reviewed, and system aspects related to sensors, energy consumption, and human-machine interfaces are examined. Moreover, we highlight the differences between traditional and smartphone-based automotive navigation, and survey the state of the art in smartphone-based transportation mode classification, vehicular ad hoc networks, cloud computing, driver classification, and road condition monitoring. Future advances are expected to be driven by improvements in sensor technology, evidence of the societal benefits of current implementations, and the establishment of industry standards for sensor fusion and driver assessment

    Inertial sensor array processing with motion models

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordBy arranging a large number of inertial sensors in an array and fusing their measurements, it is possible to create inertial sensor assemblies with a high performance-to-price ratio. Recently, a maximum likelihood estimator for fusing inertial array measurements collected at a given sampling instance was developed. In this paper, the maximum likelihood estimator is extended by introducing a motion model and deriving a maximum a posteriori estimator that jointly estimates the array dynamics at multiple sampling instances. Simulation examples are used to demonstrate that the proposed sensor fusion method have the potential to yield significant improvements in estimation accuracy. Further, by including the motion model, we resolve the sign ambiguity of gyro-free implementations, and thereby open up for implementations based on accelerometer-only arrays

    Fusion of OBD and GNSS Measurements of Speed

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    This is the author accepted manuscript. The final version is available from Institute of Electrical and Electronics Engineers (IEEE) via the DOI in this record.There are two primary sources of sensor measurements for driver behavior profiling within insurance telematics and fleet management. The first is the on-board diagnostics system, typically found within most modern cars. The second is the global navigation satellite system, whose associated receivers commonly are embedded into smartphones or off-the-shelf telematics devices. In this paper, we present maximum likelihood and maximum a posteriori estimators for the problem of fusing speed measurements from these two sources to jointly estimate a vehicle's speed and the scale factor of the wheel speed sensors. In addition, we analyze the performance of the estimators by use of the Cramér-Rao bound, and discuss the estimation of model parameters describing measurement errors and vehicle dynamics. Last, simulations and real-world data are used to show that the proposed estimators yield a substantial performance gain compared to when employing only one of the two measurement sources

    IMU-based smartphone-to-vehicle positioning

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordIn this paper, we address the problem of using inertial measurements to position a smartphone with respect to a vehicle-fixed accelerometer. Using rigid body kinematics, this is cast as a nonlinear filtering problem. Unlike previous publications, we consider the complete three-dimensional kinematics, and do not approximate the angular acceleration to be zero. The accuracy of an estimator based on the unscented Kalman filter is compared with the Cramer-Rao bound. As is illustrated, the estimates can be expected to be better in the horizontal plane than in the vertical direction of the vehicle frame. Moreover, implementation issues are discussed and the system model is motivated by observability arguments. The efficiency of the method is demonstrated in a field study which shows that the horizontal RMSE is in the order of 0.5 [m]. Last, the proposed estimator is benchmarked against the state-of-the-art in left/right classification. The framework can be expected to find use in both insurance telematics and distracted driving solutions

    Alternative EM algorithms for nonlinear state-space models

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordThe expectation-maximization algorithm is a commonly employed tool for system identification. However, for a large set of state-space models, the maximization step cannot be solved analytically. In these situations, a natural remedy is to make use of the expectation-maximization gradient algorithm, i.e., to replace the maximization step by a single iteration of Newton’s method. We propose alternative expectationmaximization algorithms that replace the maximization step with a single iteration of some other well-known optimization method. These algorithms parallel the expectation-maximization gradient algorithm while relaxing the assumption of a concave objective function. The benefit of the proposed expectation-maximization algorithms is demonstrated with examples based on standard observation models in tracking and localization

    On the exchange of intersection and supremum of sigma-fields in filtering theory

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    We construct a stationary Markov process with trivial tail sigma-field and a nondegenerate observation process such that the corresponding nonlinear filtering process is not uniquely ergodic. This settles in the negative a conjecture of the author in the ergodic theory of nonlinear filters arising from an erroneous proof in the classic paper of H. Kunita (1971), wherein an exchange of intersection and supremum of sigma-fields is taken for granted.Comment: 20 page

    Map-aided dead-reckoning using only measurements of speed

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordWe present a particle-based framework for estimating the position of a vehicle using map information and measurements of speed. The filter propagates the particles’ position estimates by means of dead-reckoning, and then updates the particle weights using two measurement functions. The first measurement function is based on the assumption that the lateral force on the vehicle does not exceed critical limits derived from physical constraints. The second is based on the assumption that the driver approaches a target speed derived from the speed limits along the upcoming trajectory. Assuming some prior knowledge of the initial position, performance evaluations of the proposed method indicate that end destinations often can be estimated with an accuracy in the order of 100 [m]. These results expose the sensitivity and commercial value of speed data collected in many of today’s insurance telematics programs, where the data is used to adjust premiums and provide driver feedback. We end by discussing the strengths and weaknesses of different methods for anonymization and privacy preservation in telematics programs

    The β-model—maximum likelihood, Cramér–Rao bounds, and hypothesis testing

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordWe study the maximum-likelihood estimator in a setting where the dependent variable is a random graph and covariates are available on a graph level. The model generalizes the well-known β-model for random graphs by replacing the constant model parameters with regression functions. Cramer-Rao bounds are derived for special cases of the undirected β-model, the directed β-model, and the covariate-based β-model. The corresponding maximum-likelihood estimators are compared with the bounds by means of simulations. Moreover, examples are given on how to use the presented maximum-likelihood estimators to test for directionality and significance. Finally, the applicability of the model is demonstrated using temporal social network data describing communication among healthcare workers

    In vitro fermentation of different ratios of alfalfa and starch or inulin incubated with an equine faecal inoculum

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    The aim of this work was to assess the impact of substituting starch (S) or inulin (I) with high-temperature dried alfalfa (HTDA) as substrates for in vitro fermentation with an equine faecal inoculum. A series of experiments were conducted to assess the fermentation kinetics of HTDA (chopped [CA] or ground [GA]) and either S or I mixed in the following ratios; 100:0, 80:20, 60:40, 40:60 and 20:80S/I: CA/GA, respectively. For each experiment, a further set of bottles containing identical ratios of S/I: CA/GA were also prepared, with the exception that the alfalfa received a simulated foregut digestion treatment (SFD) as prior to incubation. Total gas production increased (P<0.05) as the ratio of S/I to alfalfa increased. Total gas production was lower in bottles containing SFD-treated alfalfa (P<0.001). Dry matter loss decreased proportionately with increasing level of alfalfa substitution of S/I (P<0.001). Values for pH were lower in bottles containing S or I, with pH values in bottles containing S alone falling to almost 6 and those with I dropping to pH 5 and under. However, the substitution of S or I with 40% alfalfa produced pH values above 6.7, which is within physiological levels encountered in the large intestine of the horse. Consequently, there appears to be considerable potential to buffer the deleterious effects of high-starch/fructan diets with the substitution of these substrates with high-temperature dried alfalfa
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