UrbanLogiq launches AI-powered traffic metrics

Users can easily access these AI-powered traffic metrics through the UrbanLogiq platform. Once historical traffic volume data is ingested, a model automatically evaluates the usability of a customer’s current data, processes it through a series of transformations, and employs machine learning to understand a city’s unique traffic flow relationships, and relate movements to metrics on road segments with missing data.

UrbanLogiq reports its AI-powered traffic metrics, developed in collaboration with the City of Nanaimo in British Columbia, Canada, have greatly benefited from the city’s forward-thinking and data-driven transportation leadership. The city was instrumental in testing, and validating these metrics to ensure their practical application and have used them to support the calculation of crash rates.

“Through our partnership with UrbanLogiq, we now have a more complete view of our system which can be updated more frequently with less effort”

Crash rates are metrics that measure the frequency of traffic crashes within a specific area, calculated by the number of crashes per unit of traffic volume or distance travelled. These rates help identify high-risk areas and guide road safety improvement programmes.

“Traffic volumes are a key element of transportation engineering. Traditional methods for acquiring this information are costly and typically mean that network wide data sets can take years to produce and renew,” said Jamie Rose, transportation manager at the City of Nanaimo.

“Through our partnership with UrbanLogiq, we now have a more complete view of our system which can be updated more frequently with less effort. All of this enables us to make more informed decisions when investing in road improvement projects across our community.”