Crowd-Sourced Navigation for Delivery Lockers
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Solution Overview
Problem
The navigation accuracy of map navigation in the 'last mile' for delivery lockers is relatively low, leading to longer distances and increased en-route time for couriers, resulting in low delivery time efficiency.
Innovation Solution
A method that determines the most accurate navigation path to a delivery locker by using user track data, allowing users to select the most convenient navigation mode, and guiding them to the locker based on this data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map navigation based on satellite positioning is used to find delivery lockers, then the navigation system is simple and widely available, but the navigation accuracy in the last mile is low and the en-route time is long
Solution Approach 1:
The navigation system is segmented into two parts: macro-navigation using satellite positioning for long-distance guidance, and micro-navigation using crowd-sourced track data for precise last-mile guidance within communities. This segmentation allows each system to operate in its optimal range, improving overall navigation accuracy while reducing time loss in the critical last mile
Solution Approach 2:
The system performs preliminary action by collecting and storing crowd-sourced track data from multiple users before navigation is needed. This pre-collected data creates a database of optimal paths that can be quickly retrieved and applied during actual navigation, eliminating the need for real-time path calculation and reducing en-route time
2Productivity
If crowd-sourced track data is collected and processed to determine optimal navigation paths, then navigation accuracy and delivery time efficiency are improved, but the system complexity increases
Solution Approach 1:
The navigation system performs multiple functions: it collects crowd-sourced data, processes track information, determines optimal paths, and provides real-time navigation guidance. By making the system universal and multi-functional, the increased complexity is justified by the significant improvement in delivery time efficiency and navigation accuracy, as a single integrated system replaces multiple separate processes
Solution Approach 2:
The system uses self-service by automatically collecting track data from users during their normal movements, processing this data through algorithms, and generating navigation paths without requiring manual intervention. This automated self-service approach manages system complexity through algorithmic processing rather than human operation, improving productivity while keeping operational complexity manageable
Data Source
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AI summary
Provided are a method and apparatus for seeking a delivery locker, a device, and a storage medium. The method includes determining a target starting position where a user sending a delivery locker seeking request is located and determining at least one delivery locker to be sought corresponding to the delivery locker seeking request based on a navigation path from the target starting position to a delivery locker corresponding to the delivery locker seeking request; where the navigation path is a path in minimum time among a plurality of paths determined according to acquired user track data, and the plurality of paths include paths from the target starting position to each delivery locker; acquiring a target delivery locker selected from the at least one delivery locker to be sought and a target navigation mode corresponding to the target delivery locker; determining a target navigation path corresponding to both the target starting position and the target navigation mode; and guiding the user to find the target delivery locker according to the target navigation path.