How Does Swiftly Generate Arrival Predictions?


Building trust with passengers is key to increasing ridership. With reliable and accurate updates, more people will catch their ride, keeping cities moving happily and efficiently.

We are big believers in data accuracy. To help improve the passenger experience, we have created state of the art algorithms which leverage large volumes of historical and real-time data to more accurately predict future arrival times. 

Here's a high level overview of how Swiftly Transitime generates an arrival estimate for passengers:

  1. We use historical vehicle position data to understand how fast vehicles move at certain times of day, on certain road segments, etc. We often analyze tens or hundreds of millions of historical data points to really understand how the transit network performs under different circumstances.
  2. We then combine this historical data with real-time information we observe on the road.
  3. Lastly, we generate an arrival prediction based on all of the real-time and historical data points we observe. We generate a new prediction for every time we receive a vehicle position update, ensuring that passengers always have the most up to date information.

Once a prediction is made, it can be sent anywhere through data feeds and APIs. Swiftly Transitime can send data to mobile apps, web pages, automated SMS systems, automated voice response systems, electronic stop displays, and more. 

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