Transport Modality Statistics via Mobile Network Correlation
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Solution Overview
Problem
Current methods for generating transport modality statistics in public transport systems are expensive, inaccurate, and unable to provide real-time or near-real-time data, lacking information on modes of transport other than public vehicles and offering only long-term average traffic characteristics.
Innovation Solution
A processing node correlates mobile network and public transport location data using stochastic mathematical methods to determine transport modality, generating real-time or near-real-time statistics by identifying paths traveled by vehicles and subscriber devices, and assigning modes of transportation such as walking, biking, or car based on probabilistic distribution functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional household surveys and manual passenger counting are used, then cost is high and work involvement is high, but measurement precision is low due to covering only a very small subset of citizens and time periods
Solution Approach 1:
The patent uses mobile network infrastructure (base stations, network operators) as an intermediary to collect location data. Instead of directly surveying citizens or counting passengers, the system leverages the existing mobile network that citizens already use, obtaining location information through cell tower triangulation and GPS data from mobile devices. This intermediary approach provides comprehensive coverage without requiring direct intervention in citizen lives or manual counting operations.
Solution Approach 2:
The system creates a virtual copy of the physical transport system by tracking the digital footprints of citizens through their mobile devices. Instead of physically counting passengers at transport stops, the system reconstructs transport usage patterns by analyzing mobile device location data, creating a digital representation of actual transport behavior that covers all citizens rather than survey samples.
2Loss of information
If electronic ticketing systems are deployed, then detailed passenger use data is provided, but cost is high and information about other modes of transport is not available
Solution Approach 1:
The mobile network infrastructure serves multiple functions simultaneously: it provides voice communication, data transmission, and now transport monitoring. The same cell towers and network infrastructure that citizens use for everyday communication also collect location data for transport modality analysis. This universal approach eliminates the need for separate dedicated monitoring systems while capturing information about all transport modes, not just public transport.
Solution Approach 2:
Citizens' mobile devices automatically generate location data as part of normal network operation. The system does not require citizens to actively participate, install special applications, or use dedicated monitoring equipment. Their existing mobile devices continuously provide location information through normal network connectivity, making the data collection self-service and eliminating the need for expensive dedicated ticketing or monitoring systems.
3Productivity
If circuit-switched call data records are used, then location information is obtained, but data frequency is low and only long-term average traffic characteristics are provided
Solution Approach 1:
The system transitions from using circuit-switched data (which provides location only during voice calls) to packet-switched data and GPS coordinates, which provide continuous location information. By changing the data type and collection frequency parameters, the system moves from intermittent location updates tied to call events to continuous location tracking that captures real-time mobility patterns and dynamic changes in transport behavior.
Solution Approach 2:
The system implements continuous location data collection through mobile network signaling and GPS updates, ensuring that transport monitoring occurs without interruption. Unlike circuit-switched records that only capture location during calls, the continuous data stream provides uninterrupted information about citizen movement, enabling real-time detection of dynamic changes in mobility patterns due to events, road works, or service disruptions.
4Productivity
If manual methods are used for data collection, then implementation is simple, but productivity is low and real-time statistics cannot be generated
Solution Approach 1:
The system replaces manual mechanical data collection methods with automated electronic processing. Instead of human operators manually counting passengers or surveying citizens, the system uses automated algorithms to process mobile network location data, GPS coordinates, and transport schedule information. This substitution of mechanical human labor with electronic automated processing dramatically increases productivity while the complexity is managed through standardized software algorithms.
Data Source
AI summary
Methods and apparatuses for generating real-time or near-real-time transport modality statistics by correlating mobile network and public transport location data are provided. In an example, a processing node may perform a method using one or more processing circuits, the method including identifying paths traveled by multiple vehicles and determining paths traveled by multiple subscriber telecommunications devices of one or more network or service providers. In addition, the method may include correlating the paths traveled by the multiple vehicles and the paths traveled by the multiple subscriber telecommunications devices to determine which one or more modes of transportation each subscriber telecommunications device used over the path traveled by the subscriber telecommunications device. Corresponding apparatus, computer programs, and signals are also described.