How do I add route planning and ETAs to a delivery app?

To add route planning and ETAs to a delivery app, you typically need three pieces:

1. Geocoding: convert addresses to coordinates
2. Routing/optimization: determine the best delivery order and route
3. ETA prediction: estimate arrival times based on distance, traffic, and stop times

Here’s a practical approach.

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1) Collect the right data

For each delivery stop, store:

• Pickup location and drop-off location
• Latitude/longitude for each stop
• Delivery time window, if any
• Service duration at the stop
• Driver start location
• Vehicle constraints, if relevant

You’ll usually want a schema like:

• orders
• stops
• drivers
• routes
• route_stops

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2) Geocode addresses

Before routing, turn addresses into coordinates.

Use:

• Google Geocoding API
• Mapbox Geocoding
• HERE Geocoding
• OpenStreetMap/Nominatim

Store the resulting lat/lng so you don’t geocode the same address repeatedly.

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3) Plan routes

There are two common problems:

A. Single route navigation

If a driver already has a set of stops, you just need directions between them.

Use a directions API:

• Google Directions API
• Mapbox Directions
• HERE Routing
• OSRM / GraphHopper if self-hosting

This gives:

• turn-by-turn path
• distance
• duration
• traffic-aware duration, if supported

B. Multi-stop route optimization

If you need to determine the best order of stops, use a route optimization solver.

This is the Vehicle Routing Problem (VRP) or Traveling Salesman Problem (TSP), depending on complexity.

Options:

• Google Route Optimization API
• Mapbox Optimization API
• OR-Tools
• Routific, OptimoRoute, Onfleet integrations

You can optimize for:

• shortest total distance
• earliest completion time
• time windows
• vehicle capacity
• driver shifts
• pickup and delivery pairing

If you want full control, Google OR-Tools is a strong choice.

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4) Compute ETAs

For ETAs, combine:

• travel time from routing API
• expected service time at each stop
• traffic adjustments
• historical delay patterns

A simple ETA calculation:

ETA(stop N) =
current time
+ travel time to stop 1
+ service time stop 1
+ travel time to stop 2
+ service time stop 2
...
+ travel time to stop N

If using live traffic, recalculate every time the route changes or every few minutes.

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5) Update ETAs dynamically

Delivery ETAs should change as the driver progresses.

Update when:

• driver starts route
• driver completes a stop
• driver is delayed
• traffic conditions change
• a stop is added/removed

You can recalculate in the backend and push updates to the app via:

• WebSockets
• Server-sent events
• Push notifications
• periodic polling

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6) Show route and ETA in the app

Typical UI:

• map with current route
• ordered stop list
• ETA for each stop
• “next stop” indicator
• live driver location
• delay notifications

Useful details to display:

• estimated arrival time
• remaining stops
• remaining distance/time
• confidence range, e.g. “ETA 2:10–2:25 PM”

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7) Suggested architecture

Backend

• Ingest orders
• Geocode addresses
• Build/optimize routes
• Store route plans and ETAs
• Recompute on events

Mobile app

• Show map
• Show route summary and stop list
• Share driver location
• Refresh ETAs

External services

• Maps/geocoding provider
• Traffic-aware directions
• Optimization engine

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8) Example flow

1. Dispatcher assigns 12 orders to a driver
2. System geocodes all stops
3. Optimization service orders stops efficiently
4. Routing API computes distance/duration between each stop
5. Backend calculates ETAs
6. Driver app shows the route
7. As the driver progresses, the backend updates ETAs in real time

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9) If you want a fast MVP

Use managed APIs:

• Google Maps Platform for geocoding + directions
• Google Route Optimization API or OR-Tools for multi-stop routing
• WebSocket updates for live ETAs

This is the quickest path to production.

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10) If you want to self-host

Use:

• Nominatim for geocoding
• OSRM or GraphHopper for routing
• OR-Tools for optimization

This reduces vendor costs but takes more infrastructure work.

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11) Important edge cases

Handle:

• traffic spikes
• failed geocoding
• missed stops
• re-routing mid-shift
• pickups and deliveries with precedence constraints
• time windows
• driver breaks
• vehicle capacity
• road closures

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12) Recommended implementation plan

Phase 1

• geocode addresses
• show a map
• compute ETA from routing API

Phase 2

• add multi-stop optimization
• update ETAs dynamically
• support stop sequencing

Phase 3

• add traffic-aware predictions
• historical delay modeling
• automatic re-optimization
• dispatcher controls

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If you want, I can also give you:

1. a sample database schema,
2. a backend API design, or
3. a code example using Google Maps + OR-Tools.