Design and development of a big data analytics system to accommodate dynamic risk modeling of emergency responder delays at active rail crossings

In this project, we design and develop a big data analytics system, which is expected to support the advancement in the state-of-the-art in modeling the dynamic risks associated to emergency responders being delayed at active rail crossings. The model will be used to show risk within cities and support prescribed solutions to mitigate the impacts. Specifically, we design and develop a model to evaluate the risk of emergency responders being exposed to active crossings in terms of lost travel time. We also design and develop a state-of-the-art big data management system for efficient computation on generating and regenerating the models at a city level based on thousands of rail crossing blockage events, thousands of emergency response calls, with numerous potential origins and destinations is essential to evaluate the risk factors in varying scenarios.

Faculty Supervisor:

Carson Leung

Student:

Bryan Wodi;Maryam Ghaffari-Dolama

Partner:

TRAINFO

Discipline:

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program: