Travel Time Estimation Accuracy via Correlated Road Segments
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Solution Overview
Problem
Existing road traffic management systems face inaccuracies in estimating travel times due to insufficient data samples, particularly with near-field communication devices experiencing lossy wireless connections and devices being in sleep mode, leading to incomplete vehicle detection.
Innovation Solution
A method and system that collect and correlate data from multiple road segments to enhance the accuracy of travel time estimates by identifying preferred road segments with correlated travel times, using a processor to determine and store historical data, and compute average travel times through these segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If near field communication sensors are deployed to detect vehicles and compute travel times, then travel time data can be collected, but the number of detected vehicles is insufficient due to lossy wireless medium and devices being in sleep mode
Solution Approach 1:
The patent combines travel time data from multiple road segments into a unified dataset. By merging samples from correlated segments, the system increases the total number of available samples for statistical computation, thereby improving the precision of travel time estimates for any individual segment.
Solution Approach 2:
The system establishes universal correlation relationships between multiple road segments. Data collected from any segment can be universally applied to improve estimates for other correlated segments, making the sampling system more efficient and reducing the need for dense sensor deployment on each individual segment.
2Ease of operation
If sensors detect only vehicles with near field communication devices, then vehicle detection is simplified, but detection completeness is reduced due to devices in sleep mode and wireless losses
Solution Approach 1:
The patent uses correlated road segments as intermediaries to compensate for missed detections. When a vehicle is not detected on the primary segment (due to sleep mode or wireless loss), the system uses travel time data from correlated segments as proxy information, maintaining detection reliability without complicating the sensor operation.
3Measurement precision
If data from multiple road segments is correlated and combined, then statistical accuracy of travel time estimates is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary correlation analysis between road segments and pre-computes correlation coefficients. This preliminary action establishes which segments are correlated beforehand, so that during normal operation, the system only needs to combine data from pre-identified correlated segments rather than performing complex real-time correlation analysis, thus reducing operational complexity.
4Measurement precision
If the number of vehicle samples is increased to compute statistically accurate estimates, then average travel time and standard deviation can be computed more accurately, but the probability of devices being in sleep mode remains high
Solution Approach 1:
The patent merges vehicle detection data across multiple correlated road segments to increase the effective sample size. By combining samples from segments that vehicles traverse sequentially or alternatively, the system achieves sufficient statistical power for computing standard deviation without requiring every device to be continuously awake on any single segment.
Data Source
AI summary
A method and system for increasing accuracy in estimating average time taken to travel through a chosen road segment is provided. The method includes determination of time taken by one or more vehicles to travel through the road segments. Further, correlated road segments for which time taken to travel through the correlated road segments is correlated with the time taken to travel through the chosen road segment, are identified. A data repository stores a list of the one or more correlated road segments. Among the correlated road segments, one or more preferred road segments that increases the accuracy in determining the average time taken to travel through the chosen road segment, is determined by at least one processor. Further, the processor estimates the average time taken to travel through the chosen road segment using, data corresponding to time taken to travel through, the preferred road segments and the chosen road segment.