Behavioural Route Choice

Summary

Route Choice models have long been based on the assumption that travelers choose the shortest travel time path between their origin and destination, despite increasing evidence that is not the case. Robust models based on empirical data of how travellers do select routes remains an open question. This research will use empirical data on actual route choices from GPS and econometric methods to better predict actual routes selected. 

Supervisor(s)

Professor David Levinson

Research Location

Civil Engineering

Program Type

Masters/PHD

Synopsis

This research will analyse existing GPS data sets of traveler routes between homes, workplaces, and other destinations and use statistical (econometric) and machine learning methods to develop empirical models of route choice. The models will be applied to large networks and compared with traditional equilibrium models and observed data. Datasets on highway and bicycle routes are available.

Additional Information

  • Use of research technique / methodology / technology
  • Potential topics of interest for the research opportunity
  • Current PHD and/or Masters topics
  • Eligibility criteria / candidate profile
  • Scholarship(s)  /  funding available

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Keywords

transport, Transportation, networks, GIS, Statistics, Geography, Econometrics, economics, spatial analysis, Bicycling, Route Choice

Opportunity ID

The opportunity ID for this research opportunity is: 2226

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