Public Transit Control Using Transfer Demand and Arrival Prediction
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Solution Overview
Problem
Existing public transportation systems fail to consider the impacts of delays and congestion on passengers and vehicles, particularly in transfer scenarios, and lack real-time passenger data for automated decision-making on dwell times and cruising speeds.
Innovation Solution
A control apparatus using historical and real-time passenger data to automate decisions on dwell times and cruising speeds, incorporating a transfer demand prediction unit, arrival time prediction unit, and dwell time analysis unit to optimize vehicle operations and passenger transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated control decisions are implemented for dwell times and cruising speeds, then system reliability and automation level improve, but device complexity increases
Solution Approach 1:
The patent introduces a control apparatus as an intermediary system that includes a transfer demand prediction unit, arrival time prediction unit, and dwell time analysis unit. This intermediary processes real-time passenger data and generates automated control decisions, resolving the contradiction by providing reliable automated control while managing complexity through modular functional units rather than monolithic control logic
Solution Approach 2:
The system implements feedback mechanisms by continuously receiving real-time passenger data, processing it through prediction units, and using the results to dynamically adjust dwell times and cruising speeds. This feedback loop enables the system to adapt to changing conditions, improving reliability while the automated nature of the feedback reduces the need for complex human decision-making processes
2Measurement precision
If real-time passenger data is collected and processed, then measurement precision and decision-making quality improve, but loss of time and processing overhead increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and storing historical passenger data in databases before real-time analysis is needed. The transfer demand prediction unit and arrival time prediction unit use this pre-prepared data to quickly generate predictions when real-time data arrives, thereby improving measurement precision without incurring excessive processing delays
Solution Approach 2:
The data processing system is segmented into distinct functional units: data collection, historical data storage, transfer demand prediction, arrival time prediction, and control decision generation. This segmentation allows parallel processing of different data streams and predictions, reducing overall processing time while maintaining high measurement precision through specialized processing for each function
3Ease of operation
If dwell times are extended to accommodate transfer passengers, then passenger service quality improves, but productivity and system efficiency decrease
Solution Approach 1:
The patent applies dynamics by making dwell times variable rather than fixed. The dwell time analysis unit dynamically adjusts dwell times based on real-time transfer demand predictions and arrival time predictions. This allows the system to extend dwell times only when and where needed for transfer passengers, improving service quality while minimizing the impact on overall system productivity through localized, time-dependent adjustments
Solution Approach 2:
The system implements local quality by applying different dwell time adjustments to different stations and vehicles based on their specific transfer demand characteristics. Rather than uniformly extending dwell times across the entire system, the control apparatus identifies specific locations and time periods where transfer assistance is needed, thereby improving passenger service quality at critical points while maintaining high productivity elsewhere in the system
Data Source
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AI summary
The present disclosure relates to a control apparatus for a public transportation system, comprising a database 1105 configured to store historical travel data of passengers using the transportation services; a transfer demand prediction unit 1101 configured to receive a travel plan 1201 from each of a plurality of mobile devices 1200 of passengers using a transportation service, and to determine, as a transfer demand value; an arrival time prediction unit 1102 configured to predict an arrival time of a transportation vehicle of a first transportation service at a station for transferring between the first transportation service and a second transportation service, a dwell time analysis unit 1103 configured to determine a cruising speed of the transportation vehicle and/or one or more dwell times of the second transportation service in a station based on the predicted arrival times.