Transport Route Usage Sampling for Fair Revenue Allocation
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Solution Overview
Problem
Existing methods struggle to determine the spatially resolved distribution of the use of different means of transport by a large number of individuals with distance resolution, particularly in fare networks where multiple operators cooperate, and there is a need to distribute revenue fairly among them based on passenger usage.
Innovation Solution
A method involving sensor-based data collection from a subset of individuals, using mobile devices to track route usage, which is extrapolated to represent the entire population, ensuring minimal privacy intrusion and efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complete data collection from all individuals is performed, then measurement precision is improved, but device complexity and data management burden increase
Solution Approach 1:
The patent divides the population into a representative subset (sample) rather than collecting data from all individuals. This segmentation allows the system to achieve sufficient measurement precision through statistical representation while dramatically reducing the complexity of data collection and management operations.
Solution Approach 2:
The patent uses mobile devices equipped with sensors to create digital copies of route usage data from a subset of individuals. These copies are then processed and extrapolated to represent the entire population, avoiding the need for complete data collection while maintaining measurement accuracy through statistical validity.
2Measurement precision
If data collection from all individuals is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
By collecting data only from a representative subset of individuals rather than the entire population, the patent significantly reduces the time required for data collection while maintaining measurement precision through statistically valid sampling methods.
Solution Approach 2:
The patent applies partial action by collecting data from only the necessary subset of individuals to achieve reliable statistical representation, rather than attempting to collect data from everyone. This partial data collection approach reduces time loss while maintaining sufficient measurement accuracy.
3Measurement precision
If complete data collection is performed, then measurement precision is improved, but quantity of substance (data volume) increases
Solution Approach 1:
The patent segments the data collection process by focusing only on a representative subset of individuals, which dramatically reduces the total volume of data that needs to be processed while maintaining measurement precision through statistical representation of the entire population.
Solution Approach 2:
The patent creates and processes copies of route usage data from a subset of individuals, then uses these copies to infer characteristics of the entire population. This copying approach reduces the quantity of data that must be directly collected and processed while maintaining measurement accuracy.
4Device complexity
If subset sampling is used, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent changes the parameter of sample size to an optimally determined value that provides sufficient statistical representation. By carefully selecting the subset size and ensuring it meets statistical criteria for representativeness, the patent maintains measurement precision while reducing system complexity.
Solution Approach 2:
The patent replaces the mechanical approach of collecting data from every individual with a statistical sampling method. This substitution uses mathematical principles to ensure that a subset provides accurate representation, maintaining measurement precision while significantly reducing data collection complexity.
Data Source
Figure 1
AI summary
The invention relates to a method for determining the distribution of the spatially resolved use of means of transport by a group of people consisting of a large number of individuals during a survey period, comprising the following steps: - Repeatedly and distributed over the survey period, automated central querying of the sensor-based, means-of-transport route usage for a specific sub-survey period of individuals from a specific sub-group of people, wherein the sub-group of people is formed as a subset of randomly selected individuals from the group of people and which sub-survey period is a fraction of the survey period, - Storing the centrally queried, means-of-transport route usage, - Extrapolating the probable means-of-transport route usage of the group of people based on the stored means-of-transport route usage for the entire survey period;- Output of a transport-mode and route-specific unit according to the extrapolated passenger-related use of the transport vehicles.;