Travel Prompting Using Historical Duration and Real-Time Arrival Data
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Solution Overview
Problem
Existing terminal devices inaccurately remind users of departure times, leading to early or late departures.
Innovation Solution
A trip prompting method that acquires trip information, calculates arrival and departure times, and displays prompts based on historical and real-time data to ensure accurate departure timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the terminal device uses a fixed departure reminder time, then the reminder is simple to implement, but the accuracy of the departure time is poor leading to early or late departures
Solution Approach 1:
The system performs preliminary actions by acquiring historical duration data from multiple terminals in advance, clustering this data to determine a statistical first duration before the actual trip occurs. This pre-computed duration is then used to adjust the departure reminder time, improving accuracy without adding complexity during the actual reminder moment.
Solution Approach 2:
The system incorporates feedback mechanisms by using historical duration data from multiple terminals to continuously refine and update the first duration. This feedback loop allows the system to learn from actual travel patterns and improve departure time accuracy over time, balancing precision with manageable system complexity.
2Measurement precision
If the terminal device calculates departure time using only trip start time, then the calculation is simple, but the result does not account for travel duration leading to inaccurate reminders
Solution Approach 1:
The system performs preliminary clustering of historical duration data from multiple terminals to determine the first duration before it is needed for the actual departure calculation. This pre-computed statistical duration is stored and reused, avoiding repeated processing and reducing time loss during actual trip planning while maintaining high accuracy.
3Measurement precision
If the terminal device uses clustering analysis on historical data, then the departure time accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The complex clustering analysis is performed in advance on historical duration data from multiple terminals to determine a statistical first duration. This pre-computed value is then used directly in the departure time calculation, transferring the computational complexity to an offline preprocessing stage while keeping the online reminder system simple and efficient.
Data Source
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AI summary
Embodiments of this application provide a trip prompting method and apparatus, applied to a first terminal. The first terminal may obtain trip information. The first terminal may acquire a first duration associated with a trip start position. The trip information includes a trip start time and a trip start position. The first terminal may acquire a second duration required to arrive at the trip start position from a position of the first terminal at a first time. The first terminal calculates a first difference between the trip start time and a second time. The second time is a time after the first time passes the second duration. Therefore, when the first difference is less than or equal to the first duration, the first terminal may display, through a first interface, information for prompting departure. The first difference is less than or equal to the first duration, and the first duration is learned in advance. Therefore, when the first user departs from the first time, a first user may not depart too early or too late.