Traffic Information Estimation for Mixed Road Networks
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Solution Overview
Problem
Current traffic information estimation methods fail to accurately estimate traffic information for arterial roads when mixed with expressways, as they rely on weighted means from neighboring links, leading to inadequate information and inaccurate link speeds, and do not consider road types, making it difficult for car navigation devices to calculate optimal routes during commute times.
Innovation Solution
A method and device that calculate the quantity of change in relative speed and damping parameters to estimate traffic information for links without observed data, using observed data from nearby links with similar road types, and apply these estimates to arterial roads, even when mixed with expressways, by employing a CPU-based system with storage sections for road network and traffic information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traffic information of arterial roads is estimated using weighted mean from neighboring links including expressways, then traffic information coverage is improved, but estimation accuracy deteriorates due to mixing different road types with different speed characteristics
Solution Approach 1:
The patent applies local quality by differentiating estimation methods based on road type. Expressways and arterial roads are estimated separately using their respective neighboring links, rather than mixing all road types. This ensures that the estimation for arterial roads (typically 40-60 km/hr) is not contaminated by expressway data (80+ km/hr), maintaining local characteristics and improving accuracy while still providing comprehensive coverage.
Solution Approach 2:
The patent segments the road network into different road types (expressways, arterial roads, etc.) and applies separate estimation processes for each segment. By dividing the estimation task by road type, the system avoids the error of mixing dissimilar traffic patterns and speed characteristics, thereby improving estimation accuracy for each specific road category while maintaining overall system coverage.
2Reliability
If traffic information is provided only for expressways and trunk roads, then data quality is maintained, but route calculation accuracy for arterial roads deteriorates
Solution Approach 1:
The patent enables arterial roads to self-generate their traffic information by estimating it from their own neighboring arterial road links, rather than relying on expressway data or external sources. This self-service approach maintains the reliability of observed data quality while providing the precision needed for accurate route calculation on arterial roads, resolving the contradiction between data quality and route accuracy.
Solution Approach 2:
The patent changes the estimation parameter source by selecting neighboring links of the same road type rather than using a universal weighted mean approach. This parameter change ensures that arterial road estimations use appropriate speed ranges and traffic patterns specific to arterial roads, thereby maintaining data reliability while improving route calculation accuracy for these roads.
3Device complexity
If weighted mean estimation is used for all links, then device complexity is reduced, but estimation accuracy for mixed road networks deteriorates
Solution Approach 1:
The patent applies local quality by implementing a simple classification rule (same road type) that guides the estimation process. Instead of a complex universal model, the system uses a straightforward principle: estimate arterial roads from arterial road neighbors and expressways from expressway neighbors. This maintains low device complexity while significantly improving accuracy for mixed road networks by respecting local road type characteristics.
Solution Approach 2:
The patent inverts the conventional approach by not estimating all roads from all available data, but rather estimating each road type from its own同类 (same-type) neighbors. This inversion of the weighted mean principle, while maintaining simplicity, resolves the accuracy issue in mixed road networks by preventing cross-contamination of speed characteristics between different road types.
Data Source
AI summary
There is provided a method and a device for accurately estimating traffic information of a link having no traffic information even if different types of roads are mixed. The device finds a parameter characterizing a damping curve of a quantity of change of relative speed based on stored traffic information for links on a city center side on a minimum-time cost route connecting the city center and suburbs, finds a quantity of change of relative speed of the link having no observed traffic information and estimates its traffic information based on the damping curve. The device also calculates a ratio of quantities of change of relative speed of two links whose road types change as a speed change similarity ratio and estimates traffic information of the link of a second road type from known traffic information of the link of a first road type by using that ratio.