Online maps find routes by turning a real road network into a graph that a computer can search. Intersections become nodes, and road segments become edges with numbers such as distance, travel time, or traffic cost. This matters because the fastest route is not always the shortest route, especially when speed limits, congestion, and one-way streets are included.
A map app must compare many possible paths quickly and choose one that best matches the user's goal.
Understanding How Online Maps Find Routes
A route planner needs more detail than road length and speed. Roads have direction, so a street that allows travel east may not allow travel west. Some connections are blocked by gates, construction, private access, or rules for certain vehicle types.
Turning can have a cost too. A left turn across busy traffic often takes longer than continuing straight. At a roundabout, each exit creates a different choice.
Good route data stores these rules so the app does not suggest an illegal or impractical path. This is why a road network is not simply a picture of lines on a screen.
One common search method begins at the starting location and keeps a list of places that can be reached. It first considers the cheapest nearby option, then updates the best known cost of reaching later places through that option. If it finds a quicker way to reach an intersection, it replaces the older, slower estimate.
This process continues until the destination has its best cost. It works reliably when every added cost is zero or greater.
A route cannot have negative travel time, so this condition fits most navigation tasks. The important idea is that the computer does not need to list every complete route before making progress.
For large maps, searching outward equally in all directions would waste time. A star search uses an estimate of the remaining journey to focus toward the destination. Straight line distance is a useful estimate because a real road trip cannot normally be shorter than a direct line through the air.
The estimate must be chosen carefully. If it claims the remaining trip is cheaper than it really can be, the search may miss the best route.
Map services use further shortcuts too. They prepare road data in advance, grouping local streets and major roads so that long journeys can be planned without inspecting every side street in a country.
Your phone location adds another challenge. GPS readings can drift, especially near tall buildings, tunnels, or dense trees. The app must decide which nearby road you are actually using.
This step is called map matching. It compares several recent positions with road directions and likely movement, rather than trusting one inaccurate point. Traffic predictions are uncertain as well.
A crash may clear quickly, or a busy school pickup road may slow down every weekday. When a route changes, the app compares the new expected cost with the cost of staying on the current path. Students learning this topic should separate the map model from the search algorithm.
The model decides which moves are allowed and what they cost. The algorithm decides how to search those choices efficiently.
Key Facts
- A road map can be modeled as a graph: G = (V, E), where V is the set of nodes and E is the set of edges.
- An edge weight can represent distance, time, toll cost, or a combined cost.
- Travel time can be estimated by t = d / v, where d is distance and v is average speed.
- Dijkstra's algorithm finds the lowest-cost path when all edge weights are nonnegative.
- A* search uses f(n) = g(n) + h(n), where g(n) is the cost so far and h(n) is an estimate of remaining cost.
- Live traffic changes edge weights, so a route can be recalculated when conditions change.
Vocabulary
- Graph
- A graph is a structure made of nodes connected by edges, used to model networks such as roads.
- Node
- A node is a point in a graph, such as an intersection, address, or road junction.
- Edge
- An edge is a connection between two nodes, such as a road segment between intersections.
- Weight
- A weight is a number assigned to an edge that measures cost, such as distance or travel time.
- Heuristic
- A heuristic is an estimate that helps an algorithm search toward a goal more efficiently.
Common Mistakes to Avoid
- Treating the shortest distance as always the fastest route is wrong because speed limits, traffic, turns, and stops can make a longer route quicker.
- Ignoring one-way streets is wrong because graph edges may have direction, so a road can be usable from A to B but not from B to A.
- Using straight-line distance as the actual road distance is wrong because roads curve, detour, and may not connect directly.
- Assuming route calculations never change is wrong because edge weights can update when traffic, construction, crashes, or closures appear.
Practice Questions
- 1 A road segment is 6 km long and the average speed is 40 km/h. What is the estimated travel time in minutes?
- 2 A route has edge travel times of 4 min, 7 min, 3 min, and 6 min. A second route has edge travel times of 5 min, 5 min, 5 min, and 4 min. Which route is faster and by how many minutes?
- 3 Explain why an online map might recommend a route that is longer in kilometers than another available route.