Construction Marker Connectivity for Autonomous Work Zone Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating through construction zones where temporary lanes are created using construction markers, as existing lane markings become less relevant, necessitating real-time identification and connectivity determination of these markers to update the reference path.
Innovation Solution
A perception system using sensors like image, LiDAR, and RADAR identifies construction markers, determines their connectivity, and updates the drivable surface and reference path in real-time, forming a connectivity graph to guide the vehicle through the construction zone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle uses existing lane markings for navigation, then navigation is simple and straightforward, but navigation fails in construction zones where temporary lanes are created using construction markers
Solution Approach 1:
The system dynamically switches between using existing lane markings and construction markers based on the detected environment. When construction markers are detected, the system transitions from relying on static lane markings to dynamically tracking construction marker positions and connectivity, allowing the navigation system to adapt to changing road conditions in construction zones
Solution Approach 2:
The patent introduces construction markers as intermediary objects that mediate between the vehicle's navigation system and the temporary lanes in construction zones. These markers serve as temporary reference points that replace traditional lane markings, enabling the vehicle to follow constructed paths through real-time marker detection and connectivity determination
2Measurement precision
If the system updates the reference path in real-time based on construction markers, then navigation accuracy through construction zones improves, but computational load and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing the connectivity graph structure and preparing the reference path update mechanism before entering construction zones. By anticipating the need for real-time updates and having the computational framework ready, the system reduces the actual processing time required when markers are detected and connectivity must be determined
Solution Approach 2:
The system implements continuous feedback loops where detected construction markers are immediately processed to update the reference path, which then guides subsequent marker searches. This closed-loop approach ensures high path identification accuracy while optimizing processing efficiency by focusing computational resources on relevant areas based on the current reference path
3Reliability
If the system determines connectivity between all construction markers, then accurate temporary lane identification is achieved, but system complexity and computational requirements increase
Solution Approach 1:
The system segments the construction zone into discrete construction markers and determines connectivity between adjacent markers rather than analyzing all markers simultaneously. This segmentation approach divides the complex connectivity determination problem into smaller, manageable pairs of adjacent markers, reducing overall system complexity while maintaining reliable temporary lane identification
Solution Approach 2:
The patent applies local quality by focusing connectivity determination on local adjacent marker pairs along the reference path rather than globally analyzing all marker relationships. Each marker's connectivity is determined based on its local spatial relationship with neighboring markers, ensuring reliable lane identification while minimizing computational complexity through localized analysis
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and safe navigation through construction zones by updating the reference path based on construction marker connectivity, enhancing vehicle safety and regulatory compliance.
Implementation Method 1
Perception technologies use sensors like a camera, a radio detection and ranging (RADAR) sensor, a light detection and ranging (LiDAR) sensor for detecting the surrounding environment of the autonomous vehicle
Implementation Method 2
Perception technologies use sensors like a camera, a radio detection and ranging (RADAR) sensor, a light detection and ranging (LiDAR) sensor for detecting the surrounding environment of the autonomous vehicle
Data Source
AI summary
A perception system including at least one processor configured to perform operations including (i) identifying at least two construction markers on a road surface based upon analysis of sensor data from a plurality of sensors; (ii) based upon the identification of at least two construction markers, determining a starting point of a construction zone; (iii) for each construction marker identified past the starting point in the construction zone, (a) connecting each construction marker with a corresponding leading construction marker; (b) inserting each construction marker and a respective connection with the corresponding leading construction marker into a graph or a map; and (c) based upon each construction marker and the respective connection inserted into the graph or map, updating a drivable surface and a reference path; and (iv) upon not detecting a new construction marker past the starting point in the construction zone, determining the construction zone has ended is disclosed.