Restricted Travel Lane Benefit from Probe Speed Binning
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Solution Overview
Problem
Conventional traffic monitoring systems fail to accurately and efficiently determine the benefit of traveling in restricted travel lanes compared to unrestricted lanes, leading to uncertain cost-benefit decisions for drivers and autonomous vehicles.
Innovation Solution
A method and apparatus that analyze probe data points from multiple lanes to identify speed differences by dividing distances into spatial bins, determining average speeds, and evaluating the benefit of restricted travel lanes relative to unrestricted lanes, providing guidance to drivers and autonomous systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional crowd-sourced traffic data is used, then traffic information is available for navigation, but the accuracy and latency of traffic speed identification deteriorates
Solution Approach 1:
The patent segments the road segment into multiple spatial bins along the longitudinal direction and divides probe data points into different groups based on their lateral distance from the road centerline. This segmentation allows separate speed analysis for restricted lanes versus unrestricted lanes, enabling accurate identification of lane-specific traffic conditions while maintaining overall traffic information availability.
Solution Approach 2:
The patent applies local quality by analyzing traffic speeds in different spatial locations separately. Probe data points are categorized into first group (restricted lane side) and second group (unrestricted lane side), with each group analyzed independently to determine local speed characteristics. This local analysis approach improves measurement precision for specific lane conditions while preserving comprehensive traffic information.
2Measurement precision
If traffic speeds are computed with high accuracy, then reliable navigation decisions are possible, but the computational latency increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining spatial bins and grouping criteria for probe data points before actual speed computation. The road segment is pre-segmented into lateral groups corresponding to restricted and unrestricted lanes, and probe data points are pre-filtered and assigned to appropriate groups based on their geographic coordinates. This preliminary organization reduces computational complexity during real-time speed calculation, achieving high accuracy without excessive latency.
3Measurement precision
If probe data points are analyzed in detail to determine lane-specific speeds, then accurate restricted travel lane benefit is determined, but the data processing complexity increases
Solution Approach 1:
The patent simplifies data processing complexity through segmentation by dividing the analysis into distinct spatial bins and probe data point groups. Each segment (restricted lane group, unrestricted lane group) is processed independently using the same speed calculation logic, which standardizes the processing approach and reduces overall system complexity while maintaining detailed lane-specific accuracy.
Data Source
AI summary
A method, apparatus, and computer program product are provided for evaluating traffic conditions across a plurality of lanes to determine whether it is advantageous to travel in the restricted travel lane. Methods may include: receiving a plurality of probe data points, each probe data point received from a probe apparatus of a plurality of probe apparatuses; map-matching the probe data points of the plurality of probe apparatuses to a road segment of a road network; determining a distance of each probe data point from a centerline of the road segment; determining a range of distances for the probe data points from the centerline of the road segment; dividing the range of distances into a predefined number of spatial bins; identifying a speed associated with each spatial bin; and determining a restricted travel lane benefit based on an analysis of the speeds of each spatial bin.