Assessing Risk for Hazardous Driving and Accident Propensity

Road safety affects everyone, and companies are looking for ways to identify the risk factors for their fleet drivers, and to reduce the chance of accidents. This project will build on Geotab’s existing methods for assessing driving risks, and develop new techniques to better identify risky drivers and risky behaviours. The project will focus on predicting a safety score that is more meaningful to fleet managers and more indicative of risky behaviours. The produced safety scores will help fleet managers decide which driver(s) are more at risk, and take appropriate actions accordingly.

Faculty Supervisor:

Andrei Badescu;Sheldon Lin

Student:

Partner:

Geotab Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

University:

University of Toronto

Program: