Revised Procedures For Factoring Short Traffic Counts To Average Annual Daily Traffic

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Revised Procedures For Factoring Short Traffic Counts To Average Annual Daily Traffic

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Author : John H. Lemmerman
language : en
Publisher:
Release Date : 1982

Revised Procedures For Factoring Short Traffic Counts To Average Annual Daily Traffic written by John H. Lemmerman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Traffic flow categories.

Group Assignment And Annual Average Daily Traffic Estimation Of Short Term Traffic Counts Using Gaussian Mixture Modeling And Neural Network Models

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Author : Sunil Kumar Madanu
language : en
Publisher:
Release Date : 2016

Group Assignment And Annual Average Daily Traffic Estimation Of Short Term Traffic Counts Using Gaussian Mixture Modeling And Neural Network Models written by Sunil Kumar Madanu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Gaussian processes categories.

The grouping of similar traffic patterns and cluster assignment process represent the most critical steps in AADT estimation from short-term traffic counts. Incorrect grouping and assignment often become a significant source of AADT estimation errors. For instance, grouping a commuter traffic trend pattern into a recreational traffic trend may produce an erroneous AADT value. The traditional knowledge-based methods, often aided with visual interpretation, introduce subjective bias while grouping traffic patterns. In addition, the grouping requires personnel resources to process large amounts of data and remains inefficient with unapparent traffic patterns. The functional class grouping, a traditional method, also produces larger errors. Under limited resources and constraints, better methods and techniques may group sites with similar characteristics. The study uses Gaussian Mixture Modeling (GMM) for clustering and an enhanced neural network model (OWO-Newton or ONN) for classification of continuous count data. The researchers compare this modified approach with volume factor grouping and a traditional approach. The study uses Automatic Traffic Recorder (ATR) data from the Oregon Department of Transportation (ODOT) as a comparative case study. Overall, the proposed two-step approach, GMM-ONN, exhibits improved performance. The study observes an error difference of 6% to 27%, which is statistically significant at 5 percent level, between the GMM-ONN and other methods. The GMM-ONN method produces less than five percent error for urban interstates and less than ten percent for urban arterials and freeways. The study method meets the FHWA recommended AADT forecasting error of less than ten percent for commuter patterns. The GMM-ONN also produces less error when compared to studies based on the national average and Minnesota and Florida DOT count data. The lower AADT estimation errors and its distribution show an effective and reliable approach for AADT estimation using short-term traffic counts. Moreover, the lower standard deviation of errors shows the satisfactory accuracy of the AADT estimates. The study recommends the improved two-step process due to its accuracy, economical approach by using daily patterns, and ability to meet the agency's need for a low-cost traffic counting program. The GMM-ONN method not only minimizes judgment errors but also supplements the FHWA guidelines on recommending clustering techniques for grouping the traffic patterns.

Guide For Traffic Volume Counting Manual

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Author :
language : en
Publisher:
Release Date : 1970

Guide For Traffic Volume Counting Manual written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Traffic flow categories.

Guide For Traffic Volume Counting Manual

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Author : United States. Bureau of Public Roads
language : en
Publisher:
Release Date : 1963

Guide For Traffic Volume Counting Manual written by United States. Bureau of Public Roads and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1963 with Traffic flow categories.

Streamlining The Collection And Processing Of Traffic Count Statistics

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Author : David T. Hartgen
language : en
Publisher:
Release Date : 1982

Streamlining The Collection And Processing Of Traffic Count Statistics written by David T. Hartgen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Traffic flow categories.

Code Of Federal Regulations

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Author :
language : en
Publisher:
Release Date : 1997

Code Of Federal Regulations written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Administrative law categories.

Code Of Federal Regulations Title 23 Highways Revised As Of April 1 2012

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Author :
language : en
Publisher: Government Printing Office
Release Date : 2012-06-28

Code Of Federal Regulations Title 23 Highways Revised As Of April 1 2012 written by and has been published by Government Printing Office this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-28 with categories.

Determination Of Seasonal Adjustment Factors And Assignment Of Short Term Counts To Factor Groupings

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Author : Ioannis Tsapakis
language : en
Publisher:
Release Date : 2009

Determination Of Seasonal Adjustment Factors And Assignment Of Short Term Counts To Factor Groupings written by Ioannis Tsapakis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Averaging method (Differential equations) categories.

The traffic volume of a roadway segment is of significant importance for several public and private sections of the industry. This volume is represented by the Annual Average Daily Traffic (AADT). The AADT expresses the average number of vehicles that travel daily on this particular roadway section within a year. The traditional method of estimating AADT is examined along with new methods in order to improve the accuracy of the predictions. The literature review conducted at the beginning of this study comprises the theoretical background to develop the research methodology. The study data are provided from 2002 to 2007 by the Ohio Department of Transportation (ODOT). The first type of data is obtained from traffic counters that perform continuously throughout a year. The second type of data is generated by portable counters that record traffic volumes for a short-period of time. The prediction of the AADT is based on the combination of both types of data using several mathematical methods and newly developed statistical approaches. The determination of seasonal adjustment factors (SAF) is the first step of the AADT estimation. Seven SAFs and five approaches of estimating the AADT are examined for thirteen individual vehicle classes and groups of classes. The most effective SAFs are selected based on the mean absolute error (MAE) and the standard deviation (SD) of the predictions. Two analyses are conducted for each step of the study: the first is based on SAFs estimated from the sum of the two directional volumes of a roadway, and; the second on SAFs calculated for each direction of the traffic. The continuous counters are grouped together using eight different combinations of traditional grouping techniques and cluster analysis. The k-means algorithm, a non-hierarchical clustering method, is used to group the continuous counters based on their monthly SAFs. Furthermore, a statistical-based method for determining the optimal number of clusters was developed. The results are consistent over time and show a significant improvement in the accuracy of the AADT when clustering is used. Based on the performance, the applicability and the practicality of the examined methods, geographical classification and cluster analysis were selected to generate the final factor groupings. The assignment of short-term counts to counter groups includes the investigation of three methods: the traditional method; discriminant analysis, and; a new approach based on statistical similarities of traffic and temporal characteristics between a short-period count and factor groups. In total, fifty six assignment models were developed and compared. The analysis based on directional SAFs is more effective than the total volume analysis by 15% to 40%. The final results indicate that the statistical approach developed in this study results in a MAE and SD improvement over the traditional method by 51.75% and 67.73% correspondingly. In addition to the traditional method, regression and Bayesian negative binomial techniques are examined to predict AADT. In total twelve models are developed with a training data set and the results are compared using a validation data set. Parameters of significance include the HPMS roadway functional classification, population density, spatial location and the average daily traffic. The results show a full Bayesian negative binomial model with a coefficient offset was the most efficient model framework for all four seasons of the year. This model was able to describe between 87% and 92% of the variability within the data set.

Estimation Theory Approach To Monitoring And Updating Average Daily Traffic

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Author : Gary A. Davis
language : en
Publisher:
Release Date : 1997

Estimation Theory Approach To Monitoring And Updating Average Daily Traffic written by Gary A. Davis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Bayesian statistical decision theory categories.

This report describes the application of Bayesian statistical methods to several related problems arising in the estimation of mean daily traffic for roadway locations lacking permanent automatic traffic recorders. A lognormal regression model is fit to daily count data obtained from automatic traffic recorders, and this model is then used to develop (1) a heuristic algorithm for developing traffic sampling plans which minimize the likelihood of assigning a site to an incorrect factor group, (2) an empirical Bayes method for assigning a short-count site to a factor group using the information in a sample of traffic counts, and (3) an empirical Bayes estimator of mean daily traffic which allows for uncertainty concerning the appropriate factors to be used in adjusting a sample count.

Code Of Federal Regulations Title 23 Highways Revised As Of April 1 2011

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Author :
language : en
Publisher: Government Printing Office
Release Date : 2011-06-22

Code Of Federal Regulations Title 23 Highways Revised As Of April 1 2011 written by and has been published by Government Printing Office this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-22 with categories.

The Code of Federal Regulations is a codification of the general and permanent rules published in the Federal Register by the Executive departments and agencies of the United States Federal Government.