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A time-series forecast of average daily traffic volume
Abstract This paper presents a procedure for forecasting average daily traffic using a time-series analysis. The procedure assumes a logistic function to model traffic volume over a period of years. Model parameters are estimated using ordinary least-squares regression. The method was tested empirically. Model parameters were found to be significant for each of the three different thoroughfares. Further, time-series forecasts compared favorably to observed traffic and to interpolated forecasts for the same period. The method is simpler to and more economical than the standard demand forecasting procedure and is recommended where land-use patterns are stable and only small modifications to the thoroughfare network are planned.
A time-series forecast of average daily traffic volume
Abstract This paper presents a procedure for forecasting average daily traffic using a time-series analysis. The procedure assumes a logistic function to model traffic volume over a period of years. Model parameters are estimated using ordinary least-squares regression. The method was tested empirically. Model parameters were found to be significant for each of the three different thoroughfares. Further, time-series forecasts compared favorably to observed traffic and to interpolated forecasts for the same period. The method is simpler to and more economical than the standard demand forecasting procedure and is recommended where land-use patterns are stable and only small modifications to the thoroughfare network are planned.
A time-series forecast of average daily traffic volume
Benjamin, Julian (author)
Transportation Research Part A: General ; 20 ; 51-60
1984-10-15
10 pages
Article (Journal)
Electronic Resource
English
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