Data in Action: Bringing Clarity to Transit Congestion

Dec 05 / 2017

In Vancouver, one of North America’s most traffic-congested cities, TransLink’s largest operator, Coast Mountain Bus Company (CMBC), is enlisting the help of data scientists to improve the reliability of its service, today and into the future.

The goal of the project was to extract insights from timing point data that could help CMBC create more accurate schedules for its over 200 daily bus routes.

Working with students from the University of British Columbia’s Master of Data Science program, CMBC has been testing a forecasting model that maps congestion hotspots and records any trends between scheduled run times and actual run times.

Essentially, the tool tracks a resource (bus) as it moves around a network with predefined paths (bus route) through varying conditions over time, but the structure could be applied beyond CMBC to trucking and courier/delivery companies, commercial air travel, and many others.

In this particular case, the data collected has given CMBC an objective view of how long each route takes to complete. With this information, they’ll be able to schedule their buses more accurately, which in turn benefits the customer who can better plan their route and schedule their day.

In the future, with Vancouver becoming more densely populated every year, ridership will grow, road conditions will change, and the transit network will expand. To offer the best possible service and encourage more people to choose transit going forward, Coast Mountain Bus Company will need to continue to adapt. And, it is precisely these types of tools and the data they provide that will become increasingly more valuable as they endeavour to do so.

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