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Yandex Maps service has introduced an innovative pedestrian and cycling router that offers users the most popular and comfortable routes, taking into account traffic lights, elevation changes, and other route characteristics.

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Yandex Maps service has introduced a revolutionary routing technology that will fundamentally change the approach to planning pedestrian and cycling routes. The new algorithm doesn't simply build the shortest path, but suggests the most comfortable and popular routes among users.

Smart Route Assessment

When building a route, the new technology analyzes multiple factors: the presence of bike lanes and sidewalks, the popularity of each route section among users. The algorithm studies a large volume of anonymized data about how people usually move in a specific area.

If the system detects a short but inconvenient passage that users often bypass, it automatically replaces it with a less fast but more comfortable alternative. As a result, Yandex Maps will suggest a direct path along a wide comfortable street instead of a winding route through courtyards.

ML Model for Accurate Time Calculation

The updated travel time assessment algorithm uses machine learning and considers not only average movement speed, but also additional factors:

  • Traffic lights on the route
  • Number of turns
  • Time of day
  • Terrain relief and elevation changes

The system understands that going uphill takes pedestrians more time than going downhill. Thanks to these improvements, the error in determining travel time has decreased by an impressive 45%.

Benefits for Users

The new routing technology helps pedestrians and cyclists:

  • Better plan walks and trips
  • Choose more comfortable and safer routes
  • More accurately calculate travel time
  • Avoid inconvenient and confusing sections

This innovation makes Yandex Maps an even more useful tool for urban mobility, especially for those who prefer eco-friendly modes of transportation.

More details about the new technology can be found on the official Yandex website.

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