Traffic monitoring : automobiles, trucks, bicycles, and pedestrians.

Bibliographic Details
Format: Book
Language:English
Published: Washington, D.C. : Transportation Research Board, 2016.
Series:Transportation research record ; 2593.
Subjects:
Table of Contents:
  • Foreword
  • Identifying Factors to Improve Transportation Asset Management Program Sustainment Applying Implementation Research and Change Management Principles / Margaret-Avis Akofio-Sowah and Adjo Amekudzi-Kennedy
  • Accuracy of Bicycle Counting with Pneumatic Tubes in Oregon / Krista Nordback, Sirisha Kothuri, Taylor Phillips, Carson Gorecki, and Miguel Figliozzi-- Battery-Saving Communication Modes for Wireless Freeway Traffic Sensors / Benjamin Coifman and Manish Jain
  • Toward a Better Estimation of Annual Average Daily Bicycle Traffic Comparison of Methods for Calculating Daily Adjustment Factors / Mohamed El Esawey
  • Online Method to Impute Missing Loop Detector Data for Urban Freeway Traffic Control / Yuwei Bie, Xu Wang, and Tony Z. Qiu
  • Monitoring and Modeling of Urban Trail Traffic Validation of Direct Demand Models in Minneapolis, Minnesota, and Columbus, Ohio / Jueyu Wang, Steve Hankey, Xinyi Wu, and Greg Lindsey
  • Quality Assurance for Traffic Count Data in National Parks Ensuring Quality When Traffic Variability Is High / Shawn Turner, John Wikander, and A. J. Nedzesky
  • Integrating Intersection Traffic Signal Data into a Traffic Monitoring Program / Angshuman Guin, Michael Hunter, Michael Rodgers, James Anderson, Scott Susten, and Kiisa Wiegand
  • Data-Cleaning Technique for Reliable Real-Life Travel Time Estimation Use of Dedicated Short-Range Communications Probes on Rural Highways / Jinhwan Jang
  • Estimating Daily Bicycle Counts in Seattle, Washington, from Seasonal and Weather Factors / Peter Schmiedeskamp and Weiran Zhao
  • Improved Annual Average Daily Traffic Estimation Processes / Steven Jessberger, Robert Krile, Jeremy Schroeder, Frederick Todt, and Jingyu Feng
  • Recommended Procedure to Adjust Inaccurate Weigh-in-Motion Data / Chih-Sheng Chou and Andrew P. Nichols.