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Full-Text Articles in Engineering

Transportation Safety Performance Of Us Bus Transit Agencies And Population Density: A Cross-Sectional Analysis (2008-2014), Ilker Karaca, Peter T. Savolainen Jul 2019

Transportation Safety Performance Of Us Bus Transit Agencies And Population Density: A Cross-Sectional Analysis (2008-2014), Ilker Karaca, Peter T. Savolainen

Ilker Karaca

The paper examines the transportation safety performance of transit agencies providing public bus service in the US by using data from the National Transit Database (NTD)

Uses NTD data for a seven-year period from 2008 to 2014 • 3,853 observations for 651 public transportation agencies in 50 states

Seven types of bus transit fatalities and injuries (including passengers, operators, pedestrians, bicyclists)

Main explanatory variable: urban density obtained from the US Census figures

Other explanatory variables: total agency revenue miles, unlinked passenger trips, agency fleet size, and urban population


Nchrp Synthesis 499: Alternate Design/Alternate Bid Process For Pavement-Type Selection. A Synthesis Of Highway Practice, Douglas D. Gransberg, Ashley F. Buss, Ilker Karaca, Michael C. Loulakis Jul 2019

Nchrp Synthesis 499: Alternate Design/Alternate Bid Process For Pavement-Type Selection. A Synthesis Of Highway Practice, Douglas D. Gransberg, Ashley F. Buss, Ilker Karaca, Michael C. Loulakis

Ilker Karaca

Highway administrators, engineers, and researchers often face problems for which information already exists, either in documented form or as undocumented experience and practice. This information may be fragmented, scattered, and unevaluated. As a consequence, full knowledge of what has been learned about a problem may not be brought to bear on its solution. Costly research findings may go unused, valuable experience may be overlooked, and due consideration may not be given to recommended practices for solving or alleviating the problem. There is information on nearly every subject of concern to highway administrators and engineers. Much of it derives from research …


Top-Down Construction Cost Estimating Model Using An Artificial Neural Network, Douglas D. Gransberg, H. David Jeong, Ilker Karaca, Brendon Gardner Jun 2019

Top-Down Construction Cost Estimating Model Using An Artificial Neural Network, Douglas D. Gransberg, H. David Jeong, Ilker Karaca, Brendon Gardner

Ilker Karaca

This report contains the information and background on top-down cost estimating using artificial neural networks (ANN)_to enhance the accuracy of MDT early estimates of construction costs. Upon conducting an extensive review of MDT’s budgeting and cost estimating efforts, and following a survey of agency experts on the identification of the most salient project attributes with the dual-objectives of low effort and high accuracy, a rational method for top-down variable selection is proposed. Selected variables were further tested in their explanatory power of construction costs through the application of two cost estimating methodologies—multiple regression and artificial neural network methodologies. Both methods …