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Input-Output and Hybrid Techniques for Real-Time Prediction of Delay and Maximum Queue Length at Signalized Intersections
Civil Engineering Faculty Publications
  • Anuj Sharma, University of Nebraska - Lincoln
  • Darcy M. Bullock, Purdue University
  • James A. Bonneson, Texas A & M University - College Station
Date of this Version
1-1-2007
Disciplines
Citation

Transportation Research Record: Journal of the Transportation Research Board, No. 2035 (2007): 69-80. DOI: 10.3141/2035-08.

Comments

Copyright 2007, Transportation Research Board of the National Academies. Used by permission.

Abstract

Vehicle delay and queue length are quantitative measures of intersection performance. The technological advancement in the field of vehicle sensors and traffic controllers has reached a point where it has enabled efficient measurement of these performance measures. Two techniques are presented for real-time measurement of vehicle delay and queue length at a signalized Intersection, and these automated delay and queue estimates are compared with manually ground-truthed measurement. These techniques were evaluated at an instrumented intersection in Noblesville, Indiana. The root-mean-square error by both techniques was below 0.7 veh-s for-estimation of average delay and less than 0.15 vehicle for estimation of average maximum queue length, both on a cycle-by-cycle basis.

Citation Information
Anuj Sharma, Darcy M. Bullock and James A. Bonneson. "Input-Output and Hybrid Techniques for Real-Time Prediction of Delay and Maximum Queue Length at Signalized Intersections" (2007)
Available at: http://works.bepress.com/anuj_sharma1/15/