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Driving Model Overview

An overview of how the driving model calculates accurate drive times, including the data sources used.

Updated over a week ago

Overview

  • We have built our own proprietary model for predicting and calculating drive times.

  • The model does not use live traffic data, but instead are built to model congestion levels at the specific time of the day - e.g driving speeds will be slower at 9am than they will be at 1pm, or at 1am.

  • The model itself takes a range of data sets such as OpenStreetMap and country-specific data, and then constructs speed profiles based around road types, the surrounding area, and features of the road itself.

  • These speed profiles are then benchmarked on test maps, fine-tuned, and then set live.

  • Once live, the models are regularly re-tested and updated.

  • Where a driving route starts or ends away from a road, we apply a time penalty based on how long it would take to walk to the road (see more details here).

Process in detail

  1. The map is broken down into urban and rural areas at a detailed local level, using data such as municipality limit shapes and speed limits

  2. The final areas are: Rural, Village, Town, Urban, City, Extra Urban, Dense Urban

  3. All roads are tagged with a road type, e.g residential, tertiary, trunk, motorway, etc.

  4. A library of representative trip samples is built

  5. Statistical modelling techniques are applied to build speed profiles for all combinations of road types and area, including the density of different connecting road types

  6. A test map is built

  7. The speed profiles are applied to real-world routes, taking into account map features such as traffic lights and zebra crossings, and peak and off-peak times

  8. Where appropriate, driving routes are book-ended with walking to represent how people actually travel, rather than simply ‘snapping’ to or from the nearest road

  9. Drive time predictions are tested extensively against a number of real-world routes and actual journeys

  10. The results of these tests are used to fine-tune the algorithm and speed profiles

  11. The model goes live, and is then regularly tested and benchmarked, and updated where appropriate

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