Prototype Decision Support System for Optimally Routing Border Crossing Traffic Based on Predicted Border Crossing Times

摘要

The economic vitality of the 'Golden Horseshoe', a densely populated and industrialized region which encompasses Southern Ontario, Canada and parts of New York State including the Buffalo-Niagara Region, is heavily dependent upon the ability to move goods freely and efficiently across the Canadian-US border. This highlights the critical importance of the Niagara Frontier International border crossing, one of North America's busiest portals for travel and trade. This study had two primary objectives. The first objective was to develop a forecasting method for the on-line, short-term prediction of hourly traffic volumes at the Niagara Frontier border crossings. The second objective of the study was to develop queueing models which would use the predicted traffic volume to estimate the future border delay. As a case study, the project considers the Peace Bridge border crossing, which is one of the busiest Niagara Frontier border crossings, serving over 4.76 million cars annually. For the short-term prediction of hourly volumes at the Peace Bridge, a novel method was developed, which combines forecasts from traditional time series analysis, specifically the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, with forecasts made by Support Vector Regression (SVR).