Traffic Delay Detection via Ticket Validation Transfer Times
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Solution Overview
Problem
Current transportation systems lack an effective method to detect traffic delays without relying on comprehensive AVL systems, as many public transportation vehicles are not equipped with them, leading to incomplete data coverage and inefficient incident response.
Innovation Solution
The method utilizes ticket validation data to analyze transfer times between bus stops, identifying structural outliers and employing a greedy algorithm for stop pair selection to detect traffic delays, which can serve as an alternative or complementary source to AVL systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AVL systems are deployed for traffic delay detection, then detection accuracy is improved, but system cost and complexity increase significantly
Solution Approach 1:
The patent uses ticket validation data as a copy/alternative source to replace the need for direct AVL system deployment. By analyzing transfer times from ticket validations, the system replicates traffic delay detection functionality without requiring expensive GPS hardware in every vehicle, thus reducing system complexity while maintaining detection capability
Solution Approach 2:
The patent introduces ticket validation data as an intermediary medium between the vehicle location system and the traffic delay detection function. Instead of directly using AVL/GPS data, the system uses ticket validation timestamps as an intermediate source that indirectly reveals traffic conditions through transfer time analysis, thereby avoiding direct deployment of complex AVL infrastructure
2Reliability
If comprehensive AVL coverage is achieved, then traffic monitoring completeness is improved, but deployment cost increases
Solution Approach 1:
The patent makes the existing ticket validation system perform multiple functions: its primary fare collection function plus an additional traffic delay detection function. By analyzing transfer times from ticket validations, the system extracts traffic monitoring capabilities from an already-deployed infrastructure, achieving comprehensive coverage without additional deployment costs
Solution Approach 2:
The patent enables the ticket validation system to self-serve dual purposes. The same hardware and data collection infrastructure that captures fare information automatically generates traffic delay detection data through transfer time analysis, eliminating the need for separate AVL system deployment and reducing overall system cost
3Quantity of substance
If ticket validation data is used for traffic delay detection, then system cost is reduced, but data coverage completeness may decrease
Solution Approach 1:
The patent applies partial action by using only the necessary subset of ticket validation data (transfer times between stops) for traffic delay detection, rather than requiring complete AVL tracking. This selective use of data maintains cost advantages while achieving sufficient coverage for delay detection purposes
Solution Approach 2:
The patent performs preliminary analysis of ticket validation patterns to identify optimal stop pairs and establish baseline transfer times before actual delay detection. This preliminary processing enhances the reliability of subsequent delay detection from the same data source, compensating for any coverage limitations
Data Source
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AI summary
A method, system and processor-readable medium for detecting traffic delays A transfer time sample can be analyzed (704) from ticketing data (e.g., ticket validation timestamps) that includes data indicative of a plurality of stops. An optimal set of stop pairs can be selected (706) from among the pluraility of stops based on a plurality of factors including a coverage, a volume and a distance between at least two stops among the plurlaity of stops. A structural outlier associated with the transfer time sample can be then detected (708) in order to detect traffic delays determined from the optimal set of stop pairs selected from among the plurality of stops. Note that such a structural outlier can comprise an outlier in a spatio-temporal series collected from the transfer time sample.