Estimating Annual Average Daily Traffic Using Daily Adjustment Factor
نویسنده
چکیده
This study dealt with estimating AADT which serves the important basic data in transportation sector. AADT estimation is fundamental to the analysis of transportation data sets and the management of transportation systems. AADT is estimated using short-term traffic counts at most sites because permanent traffic counts is installed at limited sites. To estimate AADT, an adjustment factor application model was proposed on FHWA's Traffic Monitoring Guide in the United States. This model uses monthly or weekly adjustment factors to estimate AADT. Additionally, grouping with monthly factor, weekly factor and hourly volume pattern was proposed, but these methods don’t reflect characteristics of daily pattern. So this study used daily factor to estimate AADT and compared with advanced research. Daily factor is produced 365 factors on one permanent traffic count. Accuracy of AADT was enhanced using daily factor because it reflects daily characteristics as compared to monthly or weekly factors. But it is most important to assign a site to its similar site, because unsimilar assignment carries the greatest potential for significant estimation error. Assigning a short term traffic count to permanent traffic counts to apply adjustment factor will be investigated as a future study.
منابع مشابه
The Assessment of Applying Chaos Theory for Daily Traffic Estimation
Road traffic volumes in intercity roads are generally estimated by probability functions, statistical techniques or meta-heuristic approaches such as artificial neural networks. As the road traffic volumes depend on input variables and mainly road geometrical design, weather conditions, day or night time, weekend or national holidays and so on, these are also estimated by pattern recognition te...
متن کاملMethodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function
Transportation agencies’ motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic (AADT) adjustment factors, and to estimate AADT volumes. In contrast, bicycle and pedestrian traffic monitoring is an area of work for most transportation agencies. In most agencies, there are a...
متن کاملTraffic volume estimation from short period traffic counts
This paper considers the problem of estimating the yearly traffic volume at a count site, when traffic counts are available for only a limited part of the year, perhaps only a few hours or days. A new method for estimating annual average daily traffic (AADT) based on regression is presented. In addition to being more precise than the traditional factor approach, the new method supplies the prec...
متن کاملEstimating runoff in ungauged catchments from rainfall, PET and the AWBM model
Multiple linear regressions are used to relate average annual runoff to average annual rainfall and areal potential evapotranspiration (PET) using data from 213 catchments grouped according to location in six of the major Drainage Divisions of Australia. A method is presented for estimating daily runoff from daily rainfall data using the AWBM model, which self-calibrates its surface storage par...
متن کاملDrainwat−based Methods for Estimating Nitrogen Transport in Poorly Drained Watersheds
Methods are needed to quantify effects of land use and management practices on nutrient and sediment loads at the watershed scale. Two methods were used to apply a DRAINMOD−based watershed−scale model (DRAINWAT) to estimate total nitrogen (N) transport from a poorly drained, forested watershed. In both methods, in−stream retention or losses of N were calculated with a lumped−parameter model, wh...
متن کامل