Public Transport Timetable Generation Using Route Interval Timing
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Solution Overview
Problem
Conventional methods for generating public transport vehicle timetables are manual and rely on personal experience, leading to inefficiencies, inaccuracies, and failure to consider external environment interferences, resulting in unsatisfactory user experiences due to unpredictable waiting times and inconsistent vehicle arrivals.
Innovation Solution
A method and apparatus that generate a complete driving timetable by acquiring a preset route, extracting driving intervals, determining durations based on interval attributes, and calculating arrival times at each station, considering factors like intersections and speed limits, to create a precise and user-friendly schedule.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual compilation method is used, then the process is simple and requires no complex system, but the timetable cannot be complete and scientific, and relies on personal experience
Solution Approach 1:
The patent replaces manual mechanical compilation with an automated computer-based system that uses algorithms to generate timetables. The system processes historical operating data, external environment factors, and route attributes through computational algorithms to produce scientific and complete timetable results, eliminating the limitations of manual personal experience-based compilation.
Solution Approach 2:
The system transforms the compilation process from qualitative manual adjustment to quantitative parameter-based calculation. By changing from manual experience-based parameters to data-driven parameters including historical operating data, external environment factors, and route attributes, the system achieves complete and scientific timetable generation.
2Productivity
If statistical analysis of historical operating data is used, then the timetable can be generated automatically, but external environment interferences are not considered, resulting in non-ideal timetable
Solution Approach 1:
The system integrates multiple data sources and consideration factors into a unified timetable generation framework. It not only processes historical operating data but also incorporates external environment factors such as weather, traffic conditions, and route attributes, making the system universally applicable to various real-world scenarios and producing reliable timetables under different conditions.
Solution Approach 2:
The patent introduces external environment factors as intermediary elements between the historical operating data and the final timetable. These factors act as mediators that adjust and refine the timetable generation process, ensuring that external conditions are properly accounted for while maintaining automated generation efficiency.
3Device complexity
If conventional timetable methods are used, then the system is simple, but waiting time is unpredictable and vehicles arrive inconsistently
Solution Approach 1:
The system incorporates feedback mechanisms by continuously analyzing historical operating data and external environment factors to generate and optimize timetables. This feedback loop enables the system to learn from past performance and adjust schedules to improve vehicle arrival consistency and waiting time predictability, transforming the simple static scheduling into a dynamic optimized process.
Data Source
AI summary
Driving timetable generation methods and electronic devices are disclosed. The methods and electronic devices can comprise or be configured for: acquiring a preset driving route of a public transport vehicle, the driving route comprising multiple stations; sequentially extracting driving intervals of two adjacent stations in the driving route in the direction from a starting station to a terminal station among the plurality of stations; for each driving interval, determining, according to an interval attribute of the driving interval, a driving duration of the public transport vehicle passing through the driving interval; on the basis of a preset departure moment of the public transport vehicle and the driving duration of each driving interval corresponding to the departure moment, calculating time information that the public transport vehicle corresponding to the departure moment arrives at each station in the driving route; and generating, according to the time information, a driving timetable corresponding to the departure moment of the public transport vehicle on the current driving route.