Android应用获取用户每日乘车行驶距离：方案可行性及替代方案咨询

Hey there! Let's break down how to solve your Android app problem—getting daily travel distance for users on moving vehicles, while working around those tricky background location limits.

一、Better Alternatives to Timed Location Requests #

Your original approach hits a wall with Android's background location quotas, so here are more efficient workarounds:

1. Trigger Location Updates with Activity Recognition API #

Google's Activity Recognition API is a game-changer here—it can accurately detect what the user is doing: IN_VEHICLE, ON_BICYCLE, WALKING, STILL, etc. Here's how to use it:

• Register to listen for changes in the user's activity state
• When you get an IN_VEHICLE status, fire up frequent location updates using the Fused Location Provider
• As soon as the user switches to a non-moving state (like STILL or WALKING), stop the location requests immediately

This cuts down on unnecessary location calls drastically, stays under the quota, and saves battery life too.

2. Use the Passive Location Provider #

Instead of requesting locations yourself, let your app passively receive location data that other apps or the system are already requesting. You can set up a broadcast receiver or use the Fused Location Provider's passive callback to grab these updates. This way, you don't burn through your own location request quota, and you still get the data you need—perfect for background scenarios.

3. Combine WorkManager with Triggered Location Requests #

For Android 8.0+, use WorkManager to create background tasks that only run when specific conditions are met:

• For example, use the accelerometer to detect significant device movement (to rule out tiny shakes)
• Or tie it to Activity Recognition state changes
• When the task runs, grab a batch of location points, calculate the total distance, then shut down right away to avoid lingering in the background

二、Best Way to Detect If a User Is in a Moving Vehicle #

Top Pick: Activity Recognition API #

This is the most reliable method by far. Google's trained model does all the heavy lifting to distinguish between being in a car, walking, biking, etc. To implement it:

• Add the Google Play Services dependency to your project
• Request the ACTIVITY_RECOGNITION permission (required for Android 10+)
• Use ActivityRecognitionClient to listen for state updates—when you get IN_VEHICLE, you know the user's riding in a vehicle

Backup Plan: Sensors + Location Speed (No Google Play Services) #

If you need to support devices without Google Play Services, you can roll your own detection:

• Use the accelerometer to pick up on movement patterns (vehicles have different acceleration spikes than walking)
• Calculate speed between consecutive location points: use location.distanceTo(previousLocation) divided by the time difference. If the speed stays above 10-15 km/h (tweak this threshold as needed) and matches the accelerometer data, it's likely the user is in a vehicle
• Make sure to filter out GPS drift that might cause weird speed spikes

三、Is Your Original Approach Feasible? #

Your core logic—tracking location changes to detect movement and calculate distance—works in theory, but the timed request part is a dealbreaker for Android 8.0+ background usage. The quota limits will leave you with too few location points to calculate accurate distance.

If you want to keep parts of your original idea, you'll need to rework it:

• Ditch the timed requests and instead trigger location updates only when you detect the user is moving (using Activity Recognition or sensors)
• Stop requesting locations as soon as the user stops moving

This tweak will help you stay under the quota, improve accuracy, and save battery.

内容的提问来源于stack exchange，提问作者RJBo