The driver app is technically the most complex of the three system clients (driver, passenger, dispatcher). It must work in the background for hours, accept orders even with unstable internet, track the route accurately, and not drain the phone battery during a shift. On Android 13+, the system kills background services after 3 minutes if requirements are not met. This happened with one client: drivers complained they didn't see new orders. We had to rework the location module to use a ForegroundService and add a persistent notification. After that, order loss dropped by 25%. Our team has over 5 years of experience and 50+ completed projects in mobile development. Proper architecture saves up to 40% of time on post-launch refinements. We develop such apps turnkey. Typical development cost starts from $30,000.
How to organize background geolocation in a taxi driver app?
The driver doesn't hold the phone constantly. The app must receive orders via push, track the route, and update the server every 3–5 seconds. On iOS we use CLLocationManager with allowsBackgroundLocationUpdates. We disable pausesLocationUpdatesAutomatically. In standby mode, we switch to significant-change for battery saving. On Android — ForegroundService with a notification. Without it, MIUI 14, EMUI 12, and Samsung OneUI 6 kill the process within 5–10 minutes. We use FusedLocationProviderClient with PRIORITY_HIGH_ACCURACY during trips and PRIORITY_BALANCED_POWER_ACCURACY while waiting. Switching based on order status. According to Android documentation, ForegroundService is the only way. ForegroundService is 2–3 times more reliable than background services for Android location tracking.
| Platform | API | Features | Battery saving |
|---|---|---|---|
| iOS | CLLocationManager, allowsBackgroundLocationUpdates, background mode location | System automatically pauses updates when idle; can switch to significant-change | Automatic via pausesLocationUpdatesAutomatically |
| Android | ForegroundService + FusedLocationProviderClient | Requires persistent notification; for long background only ForegroundService | Switching between high accuracy and balanced power by order status |
How to ensure reliable order reception with poor internet?
New orders arrive as FCM/APNs data pushes. The driver accepts or declines — this must work even with a poor connection (tunnels, parking garages). Correct scheme: local queue of accepted/declined decisions with retry logic on WorkManager (Android) or BackgroundTasks (iOS). If the response doesn't reach within 10 seconds, retry, otherwise the dispatcher considers the order not accepted. Using MQTT with QoS 1 guarantees faster message delivery than standard REST. Order acceptance timeout is a classic pitfall. The server gives the driver 15–20 seconds. If the push is delayed (FCM can delay up to several minutes in Doze mode) — the driver sees the order, taps 'accept', gets an error 'order already assigned'. Solution: include the order creation timestamp in the push payload, the client checks the order age before displaying the dialog. A local queue with WorkManager reduces data loss by 90%.
Why is the order state machine important?
The driver app is strictly a finite state machine. States:
| Status | Description | Action |
|---|---|---|
| idle | Waiting for order | Listening for push |
| offer_received | New order received | Acceptance dialog |
| accepted | Order accepted | Lock other orders |
| en_route_to_pickup | Driving to passenger | Display route |
| arrived_at_pickup | At pickup location | Notify passenger |
| in_trip | Trip in progress | Taximeter, tracking |
| completed | Trip finished | Calculation, history |
Each transition is a request to the server with confirmation. The UI blocks buttons until the response is received to prevent double taps. 'Arrived' button pressed twice is a real problem: the driver pressed the button, no response (network lag), pressed again, both commands reached. The server must be idempotent for transitions, the client must show a spinner and block repeated taps until the response.
How to choose a navigation SDK for taxi?
Map integration is key. For the driver app, turn-by-turn with voice instructions is compared to offline maps, Mapbox is 30% faster in rerouting. Mapbox Navigation SDK for iOS and Android provides a ready-made NavigationViewController/NavigationView with customizable UI. Google Maps does not provide a ready turn-by-turn UI — you'd have to build it yourself using Directions API + TTS. Mapbox requires less integration time than Google Maps with custom implementation. Also available are 2GIS (good CIS coverage) and HERE Navigation SDK (real-time traffic). The choice depends on operating regions and budget. Rerouting on deviation — should trigger automatically when the driver deviates from the route by more than 50–100 meters. Mapbox has this built into the SDK, Google requires custom implementation.
What architecture suits a taxi app?
Clean Architecture with layers: presentation (ViewModel/BLoC), domain (use cases), data (repositories). For cross-platform — Flutter with native modules for location and push; for native — Swift + UIKit/SwiftUI on iOS, Kotlin + Jetpack Compose on Android. Real-time data exchange — WebSocket or MQTT for coordinates and statuses. MQTT is preferable for unstable connections: QoS 1 guarantees delivery, low overhead, built-in reconnect. ProGuard/R8 configuration requires rules to preserve models and Location API.
What's included in the work
- Design of order FSM and architecture
- Implementation of location module with background mode
- Integration of navigation and push notifications
- Configuration of code signing and provisioning profiles (iOS), ProGuard/R8 (Android)
- Publication to App Store and Google Play, including TestFlight and Firebase App Distribution
- API and code documentation
- Training drivers on app usage
- Post-release support for one month
What are the stages and timeline?
- Analysis of driver work scenarios — 1–2 weeks
- Design of FSM and architecture — 1–2 weeks
- Development of location module — 2–3 weeks
- Integration of navigation and push — 2–3 weeks
- Integration with backend — 2–3 weeks
- Testing on real devices — 1–2 weeks
- Publication — 1 week
Total timeline: from 8 to 16 weeks. Cost is calculated individually, based on integration complexity and platform requirements.
With over 5 years in the market and 50+ completed projects, we have the expertise to deliver. Get a consultation on app architecture and development timeline. Contact us to discuss your project.