Smart Work Zone Management

Construction zones are one of the leading contributors to Toronto’s ever-growing congestion. The aim of this study is to develop an integrated construction zone traffic management framework to minimize disruption of the traffic and reduce the effect in terms of congestion. This study leverages historical and real data collected from on-board construction trucks provided by the partner organization to find an insight as to how far upstream and downstream of the work zone congestion propagates. Using such information, it is then possible to develop novel prediction models determining the impact zone for future construction zones and selecting optimal work zone size and staging of vehicles and equipment. In addition to the prediction model as part of this collaboration, an innovative anticipatory vehicle routing algorithm will be developed that not only help motorist to avoid construction zones but also guides them to their destination while minimizing travel time and utilizing road network more efficiently.

Faculty Supervisor:

Bilal Farooq

Student:

Melvin Wong

Partner:

Lazaret Capital

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Ryerson University