Guides for System To Render M-E Traffic Data for Pavement Design: Instructor’s Guide

Details

• Alternative Title:
  Develop System To Render Mechanistic-Empirical Traffic Data for Pavement Design Project Title from Cover
• Creators:
  Walubita, Lubinda F. ; Lee, Sang Ick ; Aldo, Aldo
• Corporate Creators:
  Texas A&M Transportation Institute
• Corporate Contributors:
  United States. Department of Transportation. Federal Highway Administration ; Texas. Dept. of Transportation
• Subject/TRT Terms:
  • Algorithms
  • Cluster analysis
  • Data analysis
  • Data storage
  • Mechanistic-empirical pavement design
  • Traffic data
  • Workshops
• Publication/ Report Number:
  0-6940-P4
• Resource Type:
  Manual
• Geographical Coverage:
  Texas ; United States
• Corporate Publisher:
  Texas A&M Transportation Institute
• Abstract:
  This guideline is to demonstrate the key findings of Texas Department of Transportation (TxDOT) Project 0-6940 Develop System to Render Mechanistic-Empirical Traffic Data for Pavement Design. It can be used as an instructor guide to provide in-depth understanding of site-specific ME-compatible traffic data for pavement design. The training workshop is a half-day course intended to provide the methodologies for generating and utilizing site-specific ME- compatible traffic data for flexible and rigid pavement designs. The course is designed to cover: • Traffic data sources to obtain the applicable M-E traffic data • Traffic data parameters calculated and generated using the collected traffic data such as traffic volume, speed, classification, and weight data • Traffic data inputs required for pavement design (for FPS and ME design software) • The traffic data storage system (The T-DSS) to store and provide ME-compatible traffic data support • Data analysis macros and clustering algorithms to automatically analyze and generate the ME-compatible traffic data.
• Format:
  PDF
• Funding:
  0-6940
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/63042/dot_63042_DS1.pdf
• File Type:
  [PDF - 1.55 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:4f300c675016d83571c949de68f914dfdaf9d469259b55b30eb9f7340932e2fb