The construction of a route-diversion traffic flow prediction model and potential applications

摘要

This study aims to predict daily traffic volume during a roadwork period on a freeway or expressway network affected by the diversion behavior of road users by the construction of a reverse-S-Curve. This approach not only differs from the static methods in conventional transportation planning, which only obtains one equilibrium traffic volume at one point in time, it also avoids the daily learning and adaptive travel decision behavior theorem. Any variation in daily traffic volumes during the roadwork period are predicted by a simple and accurate method. Real-life traffic data on a roadwork section during long-term maintenance work on #3 National Freeway in Taiwan was provided by the National Taiwan-Area Freeway Bureau. After the data were selected and transformed, a reverse-S-Curve based on the logistic function was applied in the establishment and evaluation of the model. In addition to verification by statistical methods, this model demonstrates high-predictive accuracy based on the mean absolute percentage error (MAPE). This model can be used to predict gradually decreasing daily traffic flows towards another equilibrium level on roadwork sections undergoing long-term maintenance work in freeway or expressway networks. The shortcomings of past prediction methods are addressed with a view to effectively improving the construction of traffic volume forecasting methods. Finally, based on the characteristics of the reverse-S-Curve model, an innovative indicator- 'impact loss' was developed as an evaluation criterion in roadwork plans. The model and the 'impact loss' features are considered in a concluding discussion of potential applications.