Road Work Extension Identification Using Speed Funnel Analysis
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Solution Overview
Problem
Current methods for indicating roadwork zones to motorists and autonomous vehicles are inadequate, particularly at higher speeds, leading to potential collisions and delays, as pictorial and iconic signs may not be clearly identifiable.
Innovation Solution
A system, method, and computer program that determine road work extension data by processing speed funnel data, validating speed signs, and searching downstream links to identify candidate speed signs, allowing for the identification of road work zones and providing advance notification to drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If roadwork zones are indicated using traditional road signs and lane markings, then motorists can be notified of roadwork zones, but at higher speeds the signs cannot be clearly identified leading to potential collisions and delays
Solution Approach 1:
The system performs preliminary identification of roadwork zones by analyzing speed funnel patterns before the vehicle reaches the zone. By detecting speed limit changes and identifying roadwork extensions in advance, the system provides early warning to drivers, allowing them to slow down and prepare for the roadwork zone before arrival, thus resolving the identification accuracy problem at high speeds
2Extent of automation
If autonomous vehicles operate in autonomous mode approaching roadwork zones, then navigation is automated, but decision time for switching to manual mode is insufficient without advance identification
Solution Approach 1:
The system performs preliminary identification of roadwork zones and calculates optimal switching points before the autonomous vehicle reaches the zone. By detecting speed funnel patterns and identifying roadwork extensions in advance, the system provides early warning to the autonomous driving system, allowing sufficient time to transition from autonomous to manual mode safely before entering the roadwork zone
3Measurement precision
If roadwork zones are identified using only traditional signs, then the identification method is simple, but the identification accuracy and advance notice distance are insufficient
Solution Approach 1:
The system introduces speed funnel analysis as an intermediary method between traditional sign identification and direct roadwork zone detection. By analyzing speed limit changes and vehicle speed patterns, the system indirectly identifies roadwork zones and their extensions, achieving higher accuracy and advance notice distance without requiring complex direct detection equipment
Solution Approach 2:
The system replaces reliance on mechanical visual identification of road signs with data-driven speed pattern analysis. By processing speed funnel data and detecting speed limit changes, the system substitutes traditional optical recognition methods with computational analysis, achieving more accurate and earlier identification of roadwork zones
Data Source
AI summary
A solution including a method, a system, and a computer program product are provided herein in accordance with at least one example embodiment for identification of at least one road work extension in a geographical location. The solution includes the process of building and accessing of a map for the geographic location curated with the marking of one or more road work zones corresponding to the at least one road work extensions. The method includes the steps of obtaining multiple speed funnels of a route and validating at least one speed funnel based on the sign value of a last learned speed sign of the speed funnel. The method further generates the road work extension data associated with the road work extension based on the last learned speed sign and a result.