scholarly journals Assessment of Different Sensor Configurations for Collaborative Driving in Urban Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-16
Author(s):  
Mark G. Petovello ◽  
Kyle O'Keefe ◽  
Phil Wei ◽  
Chaminda Basnayake
Keyword(s):  
Least Squares ◽  
Kalman Filtering ◽  
A Priori ◽  
Urban Environments ◽  
Urban Canyon ◽  
Differential Gps ◽  
Degree Elevation ◽  
Simulation Techniques ◽  
Vehicle To Vehicle ◽  
Almost All

Vehicle-to-vehicle relative navigation of a network of vehicles travelling in an urban canyon is assessed using least-squares and Kalman filtering covariance simulation techniques. Between-vehicle differential GPS is compared with differential GPS augmented with between-vehicle ultrawideband range and bearing measurements. The three measurement types are combined using both least-squares and Kalman filtering to estimate the horizontal positions of a network of vehicles travelling in the same direction on a road in a simulated urban canyon. The number of vehicles participating in the network is varied between two and nine while the severity of the urban canyon was varied from 15-to 65-degree elevation mask angles. The effect of each vehicle’s azimuth being known a priori, or unknown is assessed. The resulting relative positions in the network of vehicles are then analysed in terms of horizontal accuracy and statistical reliability of the solution. The addition of both range and bearing measurements provides protection levels on the order of 2 m at almost all times where DGPS alone only rarely has observation redundancy and often exhibits estimated accuracies worse than 200 m. Reliability is further improved when the vehicle azimuth is assumed to be known a priori.

scholarly journals Penalized partial least squares for pleiotropy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Camilo Broc ◽  
Therese Truong ◽  
Benoit Liquet
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Association Studies ◽  
A Priori ◽  
Simulated Data ◽  
Real Data ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Multiple Traits ◽  
Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

scholarly journals Conditioning and PPP processing of smartphone GNSS measurements in realistic environments

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Ganga Shinghal ◽  
Sunil Bisnath
Keyword(s):  
Single Point ◽  
A Priori ◽  
Density Ratio ◽  
Satellite System ◽  
Quality Parameters ◽  
Urban Environments ◽  
Dual Frequency ◽  
Missing Measurements ◽  
Data Gaps ◽  
Point Positioning

AbstractSmartphones typically compute position using duty-cycled Global Navigation Satellite System (GNSS) L1 code measurements and Single Point Positioning (SPP) processing with the aid of cellular and other measurements. This internal positioning solution has an accuracy of several tens to hundreds of meters in realistic environments (handheld, vehicle dashboard, suburban, urban forested, etc.). With the advent of multi-constellation, dual-frequency GNSS chips in smartphones, along with the ability to extract raw code and carrier-phase measurements, it is possible to use Precise Point Positioning (PPP) to improve positioning without any additional equipment. This research analyses GNSS measurement quality parameters from a Xiaomi MI 8 dual-frequency smartphone in varied, realistic environments. In such environments, the system suffers from frequent phase loss-of-lock leading to data gaps. The smartphone measurements have low and irregular carrier-to-noise (C/N0) density ratio and high multipath, which leads to poor or no positioning solution. These problems are addressed by implementing a prediction technique for data gaps and a C/N0-based stochastic model for assigning realistic a priori weights to the observables in the PPP processing engine. Using these conditioning techniques, there is a 64% decrease in the horizontal positioning Root Mean Square (RMS) error and 100% positioning solution availability in sub-urban environments tested. The horizontal and 3D RMS were 20 cm and 30 cm respectively in a static open-sky environment and the horizontal RMS for the realistic kinematic scenario was 7 m with the phone on the dashboard of the car, using the SwiftNav Piksi Real-Time Kinematic (RTK) solution as reference. The PPP solution, computed using the YorkU PPP engine, also had a 5–10% percentage point more availability than the RTK solution, computed using RTKLIB software, since missing measurements in the logged file cause epoch rejection and a non-continuous solution, a problem which is solved by prediction for the PPP solution. The internal unaided positioning solution of the phone obtained from the logged NMEA (The National Marine Electronics Association) file was computed using point positioning with the aid of measurements from internal sensors. The PPP solution was 80% more accurate than the internal solution which had periodic drifts due to non-continuous computation of solution.

Generalised DOPs with Consideration of the Influence Function of Signal-in-Space Errors

2011 ◽  
Vol 64 (S1) ◽  
pp. S3-S18 ◽  
Author(s):  
Yuanxi Yang ◽  
Jinlong Li ◽  
Junyi Xu ◽  
Jing Tang
Keyword(s):  
Least Squares ◽  
Stochastic Models ◽  
Influence Function ◽  
A Priori ◽  
Functional Model ◽  
Global Navigation Satellite Systems ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Integrated Navigation ◽  
Satellite Systems

Integrated navigation using multiple Global Navigation Satellite Systems (GNSS) is beneficial to increase the number of observable satellites, alleviate the effects of systematic errors and improve the accuracy of positioning, navigation and timing (PNT). When multiple constellations and multiple frequency measurements are employed, the functional and stochastic models as well as the estimation principle for PNT may be different. Therefore, the commonly used definition of “dilution of precision (DOP)” based on the least squares (LS) estimation and unified functional and stochastic models will be not applicable anymore. In this paper, three types of generalised DOPs are defined. The first type of generalised DOP is based on the error influence function (IF) of pseudo-ranges that reflects the geometry strength of the measurements, error magnitude and the estimation risk criteria. When the least squares estimation is used, the first type of generalised DOP is identical to the one commonly used. In order to define the first type of generalised DOP, an IF of signal–in-space (SIS) errors on the parameter estimates of PNT is derived. The second type of generalised DOP is defined based on the functional model with additional systematic parameters induced by the compatibility and interoperability problems among different GNSS systems. The third type of generalised DOP is defined based on Bayesian estimation in which the a priori information of the model parameters is taken into account. This is suitable for evaluating the precision of kinematic positioning or navigation. Different types of generalised DOPs are suitable for different PNT scenarios and an example for the calculation of these DOPs for multi-GNSS systems including GPS, GLONASS, Compass and Galileo is given. New observation equations of Compass and GLONASS that may contain additional parameters for interoperability are specifically investigated. It shows that if the interoperability of multi-GNSS is not fulfilled, the increased number of satellites will not significantly reduce the generalised DOP value. Furthermore, the outlying measurements will not change the original DOP, but will change the first type of generalised DOP which includes a robust error IF. A priori information of the model parameters will also reduce the DOP.

scholarly journals Estimation of the mean normal measure from flat sections

2008 ◽  
Vol 40 (01) ◽  
pp. 31-48
Author(s):  
Markus Kiderlen
Keyword(s):  
A Priori ◽  
The Other ◽  
Consistent Estimator ◽  
Random Set ◽  
Normal Measure ◽  
Mild Assumption ◽  
The Mean ◽  
Vertical Sections ◽  
Almost All

We discuss the determination of the mean normal measure of a stationary random set Z ⊂ ℝ d by taking measurements at the intersections of Z with k-dimensional planes. We show that mean normal measures of sections with vertical planes determine the mean normal measure of Z if k ≥ 3 or if k = 2 and an additional mild assumption holds. The mean normal measures of finitely many flat sections are not sufficient for this purpose. On the other hand, a discrete mean normal measure can be verified (i.e. an a priori guess can be confirmed or discarded) using mean normal measures of intersections with m suitably chosen planes when m ≥ ⌊d / k⌋ + 1. This even holds for almost all m-tuples of k-dimensional planes are viable for verification. A consistent estimator for the mean normal measure of Z, based on stereological measurements in vertical sections, is also presented.

scholarly journals Solar Access Assessment in Dense Urban Environments: The Effect of Intersections in an Urban Canyon

Energies ◽  
2016 ◽  
Vol 9 (10) ◽  
pp. 796 ◽  
Author(s):  
Elena Garcia-Nevado ◽  
Anna Pages-Ramon ◽  
Helena Coch
Keyword(s):  
Urban Environments ◽  
Urban Canyon ◽  
Solar Access

scholarly journals Bounding the Practical Error of Path Loss Models

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Caleb Phillips ◽  
Douglas Sicker ◽  
Dirk Grunwald
Keyword(s):  
A Priori ◽  
Path Loss ◽  
Urban Environments ◽  
Production Networks ◽  
Modeling Error ◽  
Propagation Models ◽  
Performance Accuracy ◽  
Rural And Urban ◽  
Standard Models ◽  
Loss Models

We seek to provide practical lower bounds on the prediction accuracy of path loss models. We describe and implement 30 propagation models of varying popularity that have been proposed over the last 70 years. Our analysis is performed using a large corpus of measurements collected on production networks operating in the 2.4 GHz ISM, 5.8 GHz UNII, and 900 MHz ISM bands in a diverse set of rural and urban environments. We find that the landscape of path loss models is precarious: typical best-case performance accuracy of these models is on the order of 12–15 dB root mean square error (RMSE) and in practice it can be much worse. Models that can be tuned with measurements and explicit data fitting approaches enable a reduction in RMSE to 8-9 dB. These bounds on modeling error appear to be relatively constant, even in differing environments and at differing frequencies. Based on our findings, we recommend the use of a few well-accepted and well-performing standard models in scenarios wherea prioripredictions are needed and argue for the use of well-validated, measurement-driven methods whenever possible.

scholarly journals Analysis of Small-Scale Fading Distributions in Vehicle-to-Vehicle Communications

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Vicent M. Rodrigo-Peñarrocha ◽  
Juan Reig ◽  
Lorenzo Rubio ◽  
Herman Fernández ◽  
Susana Loredo
Keyword(s):  
Goodness Of Fit ◽  
Urban Environments ◽  
The Other ◽  
Small Scale ◽  
Channel Measurements ◽  
Experimental Distribution ◽  
Vehicle To Vehicle ◽  
Kolmogorov Smirnov ◽  
Inference Techniques ◽  
The City

This work analyzes the characteristics of the small-scale fading distribution in vehicle-to-vehicle (V2V) channels. The analysis is based on a narrowband channel measurements campaign at 5.9 GHz designed specifically for that purpose. The measurements were carried out in highway and urban environments around the city of Valencia, Spain. The experimental distribution of the small-scale fading is compared to several analytical distributions traditionally used to model the fast fading in wireless communications, such as Rayleigh, Nakagami-m, Weibull, Rice, andα-μdistributions. The parameters of the distributions are derived through statistical inference techniques and their goodness-of-fit is evaluated using the Kolmogorov-Smirnov (K-S) test. Our results show that theα-μdistribution exhibits a better fit compared to the other distributions, making its use interesting to model the small-scale fading in V2V channels.

A Rural Perspective on COVID-19 Responses: Access, Interdependence and Community

2021 ◽  
Author(s):  
Margaret Sloan ◽  
Laura Trull ◽  
Maureen Malomba ◽  
Emily Akerson ◽  
Kelly Atwood ◽  
...  
Keyword(s):  
Qualitative Research ◽  
Rural Communities ◽  
A Priori ◽  
Urban Environments ◽  
Rural Populations ◽  
Nonprofit Leadership ◽  
The Press ◽  
Economic Infrastructure ◽  
Nonprofit Education ◽  
Health Complications

Much of the press on the pandemic has been focused on urban environments where the virus was quick to spread and the numbers of cases are high. Beyond the greater risk for COVID-19-related health complications, rural populations are particularly susceptible to disruptions in the economic infrastructure of their communities. This study explores the impacts of COVID-19 on rural communities and the responses of nonprofit and other community infrastructures. Using a strengths-based approach and mixedmethods design, this qualitative research asked rural residents and nonprofit leaders about their needs, challenges, and assets as a result of COVID-19. Themes relative to access, interdependence, and community emerged from a priori categories. The research offers implications for both nonprofit education and rural nonprofit leadership.

Pricing for Hill Tourism Destination

2019 ◽  
pp. 163-175
Author(s):  
Debasish Batabyal
Keyword(s):  
A Priori ◽  
Specific Model ◽  
Linear Regression Equation ◽  
Landscape Value ◽  
Capita Spending ◽  
Per Capita ◽  
Basic Characteristics ◽  
Almost All ◽  
Tangible Product ◽  
Tour Operator

Pricing an alpine tourism is unlike pricing a tangible product. As a part of overall marketing strategy pricing a destination has lot of intricate issues that starts from the basic characteristics of the destination elements to the changing demand aspects. At the time of packaging, an alpine destination by a tour operator or destination promotion organization (DPO), a simplified model, is used that is not essentially limited to an absurd analysis of attraction features through FAM trips a priori. In almost all Indian leisure destinations, tourists are found to be price sensitive and per capita spending is not so high. So, an Indian alpine destination-specific model, based on simple linear regression equation, largely explaining the spending of tourists and thereby implying a modified landscape value has been explained here.

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