Traffic Volume Estimation Using Probe Data Algorithms
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Solution Overview
Problem
Existing methods for determining traffic volume rely heavily on expensive sensors, which are not universally available, and the low penetration rate of probe data from personal devices disrupts accurate traffic volume estimation, especially in congested conditions.
Innovation Solution
A system that uses probe data from personal devices to estimate traffic volume by selecting between free flow and congestion algorithms, combining real-time and historical data to calculate traffic density and volume, leveraging the relationship between probe points, traffic density, and road characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based methods are used to measure traffic volume, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses probe data from mobile devices as a copy or proxy representation of actual traffic conditions. Instead of directly measuring all traffic with sensors, the system collects data from a sample of vehicles (probe vehicles) and uses this copied information to estimate overall traffic volume, thereby avoiding the need for extensive sensor deployment while maintaining measurement capability
Solution Approach 2:
The patent replaces expensive, permanent sensor installations with inexpensive, temporary probe data collection from mobile devices. The probe data serves as a disposable, low-cost alternative to traditional sensor infrastructure, eliminating the need for costly sensor installation and maintenance while providing sufficient traffic volume estimation
2Device complexity
If probe data is used to estimate traffic volume, then device complexity is reduced, but measurement precision deteriorates due to low penetration rate
Solution Approach 1:
The patent changes the parameters used for traffic volume estimation by incorporating multiple factors beyond simple probe count, including probe density, vehicle speed, travel time, and route information. This parameter transformation allows the system to compensate for low probe penetration rates and achieve accurate traffic volume estimates without requiring high probe data coverage
Solution Approach 2:
The system uses feedback mechanisms to continuously refine traffic volume estimates by comparing probe data with historical traffic patterns and adjusting calculations based on observed discrepancies. This feedback loop enables the system to maintain measurement precision even with limited probe data by learning from and adapting to actual traffic conditions
3Reliability
If historical data is combined with real-time probe data, then reliability is improved, but loss of time increases due to data processing
Solution Approach 1:
The patent performs preliminary processing and organization of historical traffic data in advance, structuring it for efficient comparison with real-time probe data. By pre-processing historical information and establishing baseline traffic patterns beforehand, the system minimizes the time required for real-time data integration and acceleration while maintaining reliable traffic volume estimation
Data Source
AI summary
Method, systems, and devices are described for determining traffic volume of one or more path segments. A computing device may receive probe data associated with a road segment from one or more sources. The computing device selects either a free flow algorithm or a congestion algorithm for the probe data, and calculates an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm. A traffic volume may be estimated from the estimate probe quantity.