Traffic Congestion Estimation Using Signal Phase and Timing Data
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Solution Overview
Problem
Existing methods for determining traffic conditions on roadways often misinterpret vehicle probe data, leading to erroneous information due to the volume and complexity of data, particularly in distinguishing between traffic congestion and queueing caused by traffic signals.
Innovation Solution
A system that integrates vehicle probe data and traffic signal phase and timing (SPaT) data to differentiate between traffic congestion and queueing at intersections, using a traffic processing engine to synchronize and analyze data from mobile devices and traffic controllers, establishing thresholds to accurately assess congestion levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If vehicle probe data is used to determine traffic conditions, then the volume of available data increases, but the accuracy of traffic condition estimation deteriorates due to misinterpretation and erroneous information
Solution Approach 1:
The patent segments the analysis by distinguishing between different types of traffic conditions (congestion vs. queueing) and different locations (approach roads vs. intersections). It separates the evaluation of traffic signals from the evaluation of actual congestion, allowing for more precise interpretation of probe data by analyzing different segments of the traffic system independently.
Solution Approach 2:
The patent introduces traffic signal phase and timing (SPaT) data as an intermediary to mediate between raw probe data and traffic condition estimation. This intermediary data source provides context that helps correctly interpret probe data, distinguishing whether vehicles are stopped due to congestion or due to normal traffic signal cycles.
2Measurement precision
If traffic signal data is integrated with probe data, then the ability to distinguish between congestion and queueing improves, but the complexity of the data processing system increases
Solution Approach 1:
The patent merges probe data with traffic signal phase and timing (SPaT) data in a unified analysis framework. By combining these two data sources, the system achieves more accurate traffic condition estimation while managing complexity through integrated processing that leverages the complementary nature of the data sources.
Solution Approach 2:
The patent creates a multi-functional data processing system that simultaneously performs multiple tasks: estimating congestion levels, identifying queueing conditions, analyzing traffic signal effectiveness, and providing route guidance. This universal approach handles diverse analysis requirements within a single framework, managing complexity through consolidation rather than separate specialized systems.
3Reliability
If thresholds are established to assess congestion levels, then the reliability of traffic information improves, but the difficulty of detecting and measuring actual congestion increases
Solution Approach 1:
The patent changes the parameters used for congestion detection by establishing specific thresholds based on traffic signal cycle timing and vehicle probe data patterns. Instead of using absolute speed or density thresholds, the system uses relative thresholds that account for signal-induced queueing, making the detection more reliable while managing the complexity of measurement through standardized parameter transformations.
Data Source
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AI summary
A method for improved traffic congestion estimation is provided using signal phase and timing data from traffic signals at intersections and probe data from vehicles traversing said intersections. An example method may include: identifying each of a plurality of paths through an intersection; identifying signal phase and timing data for each traffic light associated with each path through the intersection; receiving probe data for vehicles approaching or traversing the intersection; estimating a number of vehicles failing to traverse the intersection along a path through the intersection; estimating a congestion status of the path through the intersection based on the number of vehicles failing to traverse the intersection; and causing the congestion status to be provided to permit updating of a map to reflect the congestion status.