If you have been driving on unfamiliar or even familiar roads, you must surely have relied on some kind of navigation system. Gone are the days of memorizing road maps before traveling to a new area. In this age of technology-driven navigation software, Google Maps has exploded in popularity.
It is of great help in navigating new roads and also in predicting traffic density in an area and finding the best alternative route to your destination. The offline function even helps you in areas with poor or no connection.
Let us tell you more about the algorithm Google Map uses to help us on the road:
1. Google Maps uses machine learning to suggest streets with light traffic
Google Maps helps users find the route with the least traffic to reach their destination. In a post, Google explained,
“We also look at the size and directness of a road – driving on a freeway is often more efficient than driving on a smaller road with multiple stops.”
2. Google collects location data from all users in an area to provide live traffic details
Google Map collects data from users in an area to provide accurate traffic information. The data collected is also used to show possible routes to your destination and the traffic on each of them.
3. Google Maps uses past traffic patterns of roads to provide information about the traffic conditions at that specific point in time.
“A pattern may show that on the 280 Freeway in Northern California, vehicles typically travel at 65 miles per hour between 9 a.m. and 11 a.m., but only 15 to 20 miles per hour in the late afternoon. We then combine this database of historical traffic patterns with live traffic conditions and use machine learning to create predictions based on both sets of data.”
4. After partnering with sister company DeepMind, Google Maps intends to improve time accuracy
DeepMind is an AI research under Google parent company Alphabet. In partnership with DeepMind, Google Maps uses the machine learning architecture known as Graph Neural Networks to predict estimated time of arrival with greater accuracy.
5. Google Maps uses over 13 years of data and patterns to provide accurate traffic insights
Google Maps uses 13+ years of historical data and patterns to generate traffic forecasts and provide accurate, real-time data.
6. Road quality is taken into account to provide ETA and suggest better routes
One of the best features of Google Maps is that it tracks road conditions before suggesting them and estimates the ETA. Roads that are paved or unpaved or covered with gravel, dirt or mud are detailed in the app and the arrival time is calculated accordingly.
7. As users use the app, Google continuously uses machine learning to display traffic conditions
As you drive to a specific location with the app, Google Maps continuously uses machine learning to predict traffic conditions.
8. Google Maps basically uses graph algorithms, namely the Dijkstra algorithm and the A* algorithm, to find the shortest route
To calculate the shortest distance from the source (point A) to the destination (point B), Google Maps Graph uses algorithms namely the Dijkstra algorithm and the A* algorithm.
9. What are the Dijkstra algorithm and the A* algorithm?
Well they are diagram data structures which are a collection of nodes represented by edges and vertices.
You would probably have heard of Dijkstra’s algorithm if you had studied programming. It was written by Edsger.W. Dijkstra in 1956 and after three years it was published. Dijkstra’s algorithm is used to optimize and locate the shortest route between nodes in a diagram. It’s an effective algorithm.
Use of the Dijkstra algorithm in Google Maps
There are many variants to this particular algorithm.
- A single node is designated by the variant as the source and then effectively finds the shortest path to other nodes.
- With this concept, Google Maps calculates and shows the shortest and fastest route between two points.
- In Google Maps, the number of nodes is nearly infinite or uncountable, so this algorithm can fail with increasing temporal and spatial complexity. This is where the A* algorithm comes into play.
The A* graph algorithm, specially formulated for weighted graphs, is one of the most satisfactory graph traversal and path search algorithms.
Why is the A* algorithm better than Dijkstra’s algorithm?
- This algorithm is complete and optimal and efficient.
- A* algorithm helps to find a better and more efficient way by using a heuristic function.
- The A* algorithm only focuses on the target nodes and not on the other nodes, unlike Dijkstra’s, which makes it more powerful.
- It also takes into account parameters such as distance, time taken, etc. to optimize and select the more promising nodes.
Did you find it enlightening? Let us know in the comments section.