Course 3, lesson 23 of 100, Ages 7+
Maps and traffic
How apps find the fastest way
Like I’m 5
A map app is like a friend who can see every road at once and remembers how busy each one usually gets. It picks the quickest way for you.
The big idea
A map app knows the roads, but the clever part is predicting traffic. It learns from years of trips and from phones on the road right now to estimate how long each street will take.
Then it searches through possible routes to find the quickest one, and keeps updating as things change. If there's a jam ahead, it may suggest a new route mid-journey.
Examples
- Rush hour: The app knows school mornings are slow and plans around it.
- Live jams: Lots of phones moving slowly on a road means a jam right now.
- Arrival time: 'You'll arrive at 9:42' is a prediction, and it updates as you drive.
How it works
- Map apps know the roads, and they collect anonymous speed data from lots of phones to see where traffic is slow.
- AI learns patterns, like busy school mornings, to predict what traffic will be like by the time you get there.
- Then a route-finding method compares possible paths and picks the fastest one.
Check your understanding
- How does a map app know a road is busy right now?
- Options: From the speed of lots of phones on that road; It asks every driver; It only checks the weather.
Answer: From the speed of lots of phones on that road. Anonymous speed data from many phones shows where traffic is moving slowly. - How does a map app know there's a traffic jam right now?
- Options: Lots of phones on that road are moving slowly; It guesses randomly; Someone phones the app company.
Answer: Lots of phones on that road are moving slowly. Live, anonymous speed data from many phones reveals jams.
Remember
Map apps predict traffic from patterns and live data.
Talk about it
How would you find the quickest way to school?
Go deeper
Navigation combines graph-search algorithms (variants of Dijkstra’s and A*) with machine-learned travel-time predictions from historical and live data. Privacy protections such as aggregation and anonymisation matter, because location data is sensitive.