Crowdsourcing Transit Predictions

Uncertainty about transit arrival is a significant challenge for attracting new transit users, but accurate real time systems, built into vehicles and stations, are costly for agencies working on tight budgets. In many cities, it’s a vicious cycle: poor service leads to fewer riders, which leads to reduced budgets, which leads to worse service. App developers may have found a low-cost solution however. By crowdsourcing travel data, along with reports of delays and other issues, apps like Moovit and Swyft offer a new, low-cost way to ensure accurate travel information. This approach, which has particular promise for cities in developing countries or cities experiencing economic hardship, has the opportunity to make transit more attractive to potential users, without increasing costs for transit agencies.

Mitchell Reardon

Mitchell Reardon is the TH!NK by IBI blog curator, a land use planner and urban experimenter. His interdisciplinary work centres on people and how they live, work and move through the city. Mitchell is enjoying life in Vancouver, after 6 years of living and working in Stockholm, Sweden. Catch up with him on Twitter: @MitchellReardon

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