The purpose of this project is to use electronic on-board recorder data to develop a public sector decision-support tool that has the capability of predicting patterns of commercial vehicle tours, incorporating dynamics of business operations over time.
A new source of Global Positioning System (GPS) data from 30,000 trucks tracked by a partnering fleet management firm is being used to estimate dynamic integrated models of shipment frequency, stop dwell time, and tour formation. Novel techniques are being developed for processing GPS data for model estimation, modelling dynamic tour behaviour, and microsimulating truck operations using parallel computing. Decision-support software are being developed to assess parking policy, truck route restrictions and incentives for off-peak deliveries. Robust policy analysis, using inexpensive GPS data, has strong potential to reduce congestion and improve the competitiveness of Ontario’s urban economies.
Principal Investigator: M. J. Roorda