Grant: Alliance Grants
University of Waterloo
$81,079.00
Advancing Vision Zero Road Safety with Operational AI and Smart City Data
FY 2021-22
Summary
Vision Zero is a road safety strategy aimed at achieving no road user fatalities or serious injuries with a specific focus on vulnerable road users (VRUs) such as pedestrians and cyclists. Each year in Canada, about 2,000 people are killed and 165,000 are injured (10,000 seriously), while using our road transportation system. The annual social costs of the motor vehicle collisions in terms of loss of life, medical treatment, rehabilitation, lost productivity, and property damage are measured in tens of billions of dollars - estimated at 40.7 billion (or 2.1% of GDP) for Canada in 2017.The goal of the proposed research is to advance the planning, designing and evaluation of various road safety strategies and safety countermeasures by leveraging emerging data sources and recent advances in artificial intelligence. For example, the emergence of video- and laser-based smart city sensors provides an opportunity to monitor traffic "conflicts" - situations where there is an increased risk of collision. Then, artificial intelligence can use these data to predict collisions in the future. Similarly, these data can be used to develop simulation models to test road safety projects and policies that do not yet exist in reality. Hence, the proposed research will develop state-of-the-art tools and techniques for quantitatively assessing the road safety effects of decisions made in the planning, design, operations, and maintenance of transportation systems.The proposed research is anticipated to directly enhance the Vision Zero plans developed concurrently by the partnering cities of Kitchener and Waterloo. Similarly, Miovision, a leading and partnering smart city sensor provider, is anticipated to commercialize promising developments for applications in other Canadian cities.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
561017-2020
Name nom
Bachmann, Christian
Department département
Civil & Environmental Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2020
Award amount
81079
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
1003
Research subject group en
Civil engineering
Research subject group fr
Génie civil
Research subject en
Transportation engineering
Research subject fr
Génie du transport
Installment
inst:1; 2
Partie
2
Nb partie
3
Application title
Advancing Vision Zero Road Safety with Operational AI and Smart City Data
Keyword
NSERC
Application summary
Vision Zero is a road safety strategy aimed at achieving no road user fatalities or serious injuries with a specific focus on vulnerable road users (VRUs) such as pedestrians and cyclists. Each year in Canada, about 2,000 people are killed and 165,000 are injured (10,000 seriously), while using our road transportation system. The annual social costs of the motor vehicle collisions in terms of loss of life, medical treatment, rehabilitation, lost productivity, and property damage are measured in tens of billions of dollars - estimated at 40.7 billion (or 2.1% of GDP) for Canada in 2017.The goal of the proposed research is to advance the planning, designing and evaluation of various road safety strategies and safety countermeasures by leveraging emerging data sources and recent advances in artificial intelligence. For example, the emergence of video- and laser-based smart city sensors provides an opportunity to monitor traffic "conflicts" - situations where there is an increased risk of collision. Then, artificial intelligence can use these data to predict collisions in the future. Similarly, these data can be used to develop simulation models to test road safety projects and policies that do not yet exist in reality. Hence, the proposed research will develop state-of-the-art tools and techniques for quantitatively assessing the road safety effects of decisions made in the planning, design, operations, and maintenance of transportation systems.The proposed research is anticipated to directly enhance the Vision Zero plans developed concurrently by the partnering cities of Kitchener and Waterloo. Similarly, Miovision, a leading and partnering smart city sensor provider, is anticipated to commercialize promising developments for applications in other Canadian cities.