Modeling and Evaluation of Freeway Travel Time Estimation with Different Traffic Detection Technologies

To support research and practices that aim to analyze and improve traffic systems, accurate traffic state estimation is required, which is usually based on ground truth data obtained from monitoring infrastructures. The most common way to monitor traffic nowadays is by using inductive loop detectors, the costs of which are too high to be used for the entire road network. Alternative traffic detection methods include radar sensors, global positioning system (GPS), and GPS-enabled smartphones. The objective of this project is to evaluate the accuracy of data obtained from these three traffic detection systems, develop mathematical models to describe the differences among them, and provide suggestions for future traffic detection technology development. The City of Edmonton and the CT Protein Biotech Inc. will provide data and technical support to help develop this project.

Faculty Supervisor:

Tony Z Qiu

Student:

Partner:

City of Edmonton;CT Protein BioTech Inc

Discipline:

Engineering

Sector:

Administrative and support, waste management and remediation services; Public administration

University:

University of Alberta

Program: