Traffic Flow Rate Calculation Using Mobile and Stationary Sensor Data
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Solution Overview
Problem
Existing methods for calculating traffic flow rates are imprecise, particularly when the ratio of observable edges by stationary sensors is low, and fail to accurately determine the observation rate for each edge, leading to errors in traffic flow rate estimation.
Innovation Solution
A traffic flow rate calculation method using a road network represented by nodes and edges, where mobile sensor data and stationary sensor data are combined to estimate observation rates for each path, allowing for precise calculation of traffic flow rates by using the reciprocal of the observation rate as a variable and incorporating the number of observations by stationary sensors as a constraint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a constant observation rate is assumed across all edges to simplify calculation, then calculation complexity is reduced, but measurement precision of traffic flow rate deteriorates
Solution Approach 1:
The patent divides the road network into multiple edges and calculates a separate observation rate for each edge based on stationary sensor observations. This segmentation allows the system to account for varying observation conditions across different road sections, thereby improving measurement precision while maintaining manageable calculation complexity through localized computations.
Solution Approach 2:
The patent changes the observation rate parameter from a constant value to a variable that differs for each edge. By calculating and applying edge-specific observation rates derived from stationary sensor data, the system adapts to local traffic conditions and sensor coverage variations, significantly improving traffic flow rate measurement precision without requiring overly complex global optimization.
2Quantity of substance
If the ratio of observable edges by stationary sensors is low, then sensor deployment cost is reduced, but measurement precision of traffic flow rate deteriorates
Solution Approach 1:
The patent introduces mobile sensors as an intermediary component to bridge the gap when stationary sensor coverage is insufficient. Mobile sensors collect trajectory data that complements stationary sensor observations, enabling the system to calculate observation rates and traffic flow rates even when the ratio of observable edges by stationary sensors is low, thereby maintaining measurement precision with reduced stationary sensor deployment.
3Device complexity
If mobile sensor trajectory data is used without combining with stationary sensor data, then device complexity is reduced, but measurement precision of observation rate deteriorates
Solution Approach 1:
The patent merges mobile sensor trajectory data with stationary sensor observation data to calculate accurate observation rates. By combining these two data sources, the system leverages the comprehensive coverage of mobile sensors and the ground-truth measurements of stationary sensors, achieving high-precision observation rate estimation. The merging is implemented through a calculation framework that integrates both data types without requiring overly complex integration mechanisms.
Data Source
AI summary
A traffic flow rate calculation method includes, by using a road network produced by representing a road system with a plurality of nodes and a plurality of edges including a stationary sensor edge in which a stationary sensor measures the number of moving bodies; obtaining the first number of observations corresponding to the number of trajectories measured by mobile sensors for each path, the each path including the at least one edge, the each of trajectories corresponding to a movement trajectory of the moving body, and the second number of observations corresponding to the number of moving bodies measured by the stationary sensor; estimating an observation rate by using the first number of observations and the second number of observations; calculating a traffic flow rate for the each path by using the estimated observation rate and the first number of observations for each path.