01334160

Component

https://doi.org/10.3141/2256-17

http://scholar.google.com...dana&publication_year=2011

Vehicle classification and axle load data are required for the structural design of new and rehabilitated flexible and rigid pavements with the new "Mechanistic–Empirical Pavement Design Guide" (MEPDG) developed under NCHRP Project 1-37A. The axle load spectra are determined from traffic data collected at weigh-in-motion (WIM) stations, and vehicle count and class data are recorded by vehicle classification stations. Some preliminary results are presented for an extensive traffic data-processing effort conducted to develop traffic inputs required by the MEPDG to design pavements in New York State. The data collected by classification and WIM sites from 2004 to 2009 were processed with the TrafLoad software developed in NCHRP Project 1-39. The discussion focuses on the variability of the major traffic input variables required by the MEPDG, as obtained from data collected in New York State, and on the differences between the data obtained from individual stations, state average values, and the default values recommended by the MEPDG, where applicable. The effect of variability of the major traffic input variables on the performance predicted by the MEPDG for a typical flexible pavement structure is also discussed.

01362484

11-1128

English

pp 142-150

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309222921

Print

Figures (10) ; References (8) ; Tables (2)

Axle loads; Case studies; Flexible pavements; Pavement design; Traffic data; Vehicle classification; Weigh in motion

Mechanistic-Empirical Pavement Design Guide

New York (State)

Data and Information Technology; Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways

TRIS, TRB

Feb 17 2011 5:41PM

• Algorithm for Finding Optimal Paths in a Public Transit Network with Real-Time Data
• Analysis of Weigh-in-Motion Data for Truck Weight Grouping in "Mechanistic–Empirical Pavement Design Guide"
• Automated Quality Assurance Methodology for Archived Transit Data from Automatic Vehicle Location and Passenger Counting Systems
• Axle Load Distribution for Mechanistic–Empirical Pavement Design in North Carolina: Multidimensional Clustering Approach and Decision Tree Development
• Capturing Transportation Infrastructure Performance: Data Availability, Needs, and Challenges
• Centrality Characteristics of Road Network Patterns of Traffic Analysis Zones
• Counting Motorcycles and Estimating Motorcycle Vehicle Miles of Travel
• Detection and Correction of Inductive Loop Detector Sensitivity Errors by Using Gaussian Mixture Models
• Development of Traffic Inputs for "Mechanistic–Empirical Pavement Design Guide" in Michigan
• Discriminant Analysis for Assigning Short-Term Counts to Seasonal Adjustment Factor Groupings
• Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles
• Estimation of Dynamic Traffic Densities for Official Statistics: Combined Use of Data from Global Positioning System and Loop Detectors
• Evaluation of Nonintrusive Technologies for Traffic Detection, Phase 3
• Forecasting Traffic Loads for Mechanistic–Empirical Pavement Design
• Future Scenarios for Traffic Information and Management
• Identifying and Correcting Pulse-Breakup Errors from Freeway Loop Detectors
• Innovative Real-Time Methodology for Detecting Travel Time Outliers on Interstate Highways and Urban Arterials
• Is Usual Share of Commuting Mode Always Greater Than Its Actual Share?
• License Plate Image Binarization Based on Chromatic Information and Fuzzy C-Mean Approach
• Network Stratification Method by Travel Time Variation
• Travel Time Prediction Using k Nearest Neighbor Method with Combined Data from Vehicle Detector System and Automatic Toll Collection System