Application of Neural Networks to Estimate AADT on Low-Volume Roads

Author:

Sharma Satish1234,Lingras Pawan1234,Xu Fei1234,Kilburn Peter1234

Affiliation:

1. Prof. of Engrg., Univ. of Regina, Regina, SK, Canada, S4S 0A2.

2. Assoc. Prof., Dept. of Mathematics and Computing Sci., Saint Mary's Univ., Halifax, NS, Canada, B3H 3C3.

3. Engrg. Asst., Univ. of Regina, Regina, SK, Canada, S4S 0A2.

4. Traffic Data and Forecasting Engr., Alberta Transp. and Utilities, Twin Atria Build., Edmonton, AB, Canada, T6B 2X3.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Reference22 articles.

1. Albright D. ( 1991). “An imperative for and current progress toward national traffic monitoring standards.” Inst. of Transp. Engrs. 61(6) 22–26.

2. Bodle R. ( 1967). “Evaluation of rural coverage count duration for estimating annual average daily traffic.” Transp. Res. Rec. 199 Transportation Research Board Washington D.C. 67–77.

3. Davis G. A. ( 1996). “Estimation theory approaches to monitoring and updating average daily traffic.” Rep. No. 97-05 . Center of Transportation Studies University of Minnesota Minneapolis.

4. Davis G. A. ( 1997). “Accuracy of estimates of mean daily traffic: A review.” Transp. Res. Rec. 1593 . Transportation Research Board Washington D.C. 12–16.

5. Dougherty M. S. ( 1995). “A review of neural networks applied to transportation.” Transp. Res. Part C 3(4) 247–260.

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