Transit Vehicle Trip Assignment Using Probe Data Queues
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Solution Overview
Problem
In real-time transit tracking environments, transit vehicles like buses often do not report their current trip, making it difficult to determine if they are running late, on time, or ahead of schedule, which hinders the implementation of advanced features such as personalized real-time routing and alerting.
Innovation Solution
A method is developed to match transit vehicles with their corresponding trips using real-time location data and spatial and temporal properties of all trips, involving the placement of probe data into a queue based on the trip completion, calculation of arrival times at the next closest stop, and assignment to the closest scheduled trip, enabling real-time routing and service alerting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If probe data is placed into a queue based on trip completion for vehicle-trip matching, then the accuracy of determining whether a bus is running late, on time, or ahead of schedule is improved, but the system complexity increases due to the need for queue management and real-time data processing
Solution Approach 1:
The system performs preliminary actions by placing probe data into a queue based on trip completion status before actual trip assignment occurs. This preliminary organization of data allows for more accurate determination of bus trip status by ensuring data is processed in the correct sequence, resolving the contradiction between measurement precision and system complexity through advance data preparation
Solution Approach 2:
The queue serves as an intermediary structure between data collection and trip assignment. By introducing this intermediate storage mechanism, the system can accurately track trip completion status without requiring complex real-time processing at every stage, thus improving measurement precision while managing system complexity through a simple buffering mechanism
2Adaptability or versatility
If real-time location data is processed to match vehicles with trips, then the ability to provide personalized real-time routing and alerting is improved, but the loss of time for data processing and matching increases
Solution Approach 1:
The system performs preliminary matching of vehicles to trips using the queue-based approach before real-time routing requests are made. This preliminary action pre-establishes vehicle-trip associations, enabling personalized routing and alerting to be generated quickly without extensive real-time processing, thus reducing time loss while maintaining adaptability
Solution Approach 2:
The system dynamically adjusts the matching process by continuously updating the queue with new probe data and re-evaluating vehicle-trip assignments. This dynamic approach allows the system to maintain accurate real-time routing capabilities while optimizing processing time by only reprocessing data when necessary rather than continuously
3Reliability
If the system monitors transit vehicles for state changes and purges assignments when changes occur, then the reliability of trip assignment information is improved, but the productivity of the system decreases due to frequent purging operations
Solution Approach 1:
The system implements feedback mechanisms by monitoring vehicle state changes and using this information to determine when purging assignments is necessary. This feedback-driven approach ensures that assignments are only purged when actual state changes occur, maintaining reliability while minimizing unnecessary purging operations that would reduce productivity
Solution Approach 2:
The system applies partial purging by only removing assignments for vehicles that have actually changed state, rather than purging all assignments periodically. This selective approach maintains high reliability by ensuring accurate assignment information while preserving productivity by avoiding unnecessary system-wide purging operations
Data Source
AI summary
A method, apparatus and computer program products are provided for matching a transit vehicle to a trip. An example method may comprise receiving probe data, the probe data comprising at least one of identity information, location information, or time information corresponding to the transit vehicle, causing placement of the probe data into a queue, wherein a placement in the queue is dependent on how much of the trip the transit vehicle has completed as indicated by the probe data, and causing assignment of the transit vehicle to a single candidate trip from among a set of candidate trips comprising a scheduled arrival time at a next closest stop closest to a calculated arrival time.