Automated Vehicle Road Edge Substrate Color Detection
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Solution Overview
Problem
Existing technologies lack a method to safely determine the color of a substrate adjacent to a non-elevated road surface for automated vehicles, particularly in situations without elevated barriers, which poses a risk of accidents when the vehicle deviates from the road.
Innovation Solution
A method that involves determining a trajectory parallel to the road lane trajectory with a predetermined distance to the road end, and then determining the color of the substrate at specific points along this trajectory using multiple perception sensors, such as LiDAR, cameras, and radar, to ensure safety and predict the road edge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple perception sensors are used to determine substrate color for safety, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The patent combines multiple perception sensors (cameras, LiDAR, radar) into an integrated sensor system that simultaneously captures data about substrate color, distance, and position. This merging approach achieves high measurement precision for substrate identification while managing device complexity through unified sensor fusion architecture.
Solution Approach 2:
The sensor system is designed to perform multiple functions: detecting substrate color for hazard identification, measuring distance to road edge, and tracking substrate position along the trajectory. This multi-functionality reduces the need for separate specialized sensors, balancing measurement precision with device complexity.
2Adaptability or versatility
If a trajectory parallel to the road lane is determined with predetermined distance, then the predictive capability improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system pre-calculates a trajectory parallel to the detected road lane at a predetermined distance before the vehicle reaches the road edge. This preliminary action enables predictive detection of potential hazards (grass, snow, loose soil) ahead of time, allowing the vehicle to prepare appropriate responses. The trajectory calculation uses geometric relationships based on the detected lane, reducing measurement difficulty.
3Reliability
If the color of substrate is determined for automated driving safety, then reliability improves, but the loss of time for processing increases
Solution Approach 1:
The system determines substrate color along a pre-calculated trajectory in advance, before the vehicle reaches the potential hazard zone. This preliminary color determination allows processing to occur during normal driving phases rather than during critical decision moments, reducing time loss while maintaining reliability.
Solution Approach 2:
Instead of analyzing every pixel in the entire field of view, the system focuses color determination efforts specifically along the predetermined parallel trajectory where hazards are most likely to occur. This partial action approach concentrates processing resources on critical areas, reducing overall processing time while maintaining safety reliability.
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
The method provides a safe and predictive way to determine the color of substrates next to roads without elevated barriers, enhancing the safety integrity of automated driving by accurately identifying the road edge and potential hazards like grass, snow, or loose soil.
Implementation Method 1
determining a trajectory being parallel to a given trajectory of a lane of the road and having a predetermined distance to a given lateral end of the road
Implementation Method 2
determining the color of the substrate for at least one point being located on or having a predetermined distance to the determined trajectory
Data Source
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AI summary
Provided is a method for determining a color of a substrate being laterally adjacent to a non-elevated surface of a road for an automated vehicle. The method comprises a step of determining a trajectory being parallel to a given trajectory of a lane of the road and having a predetermined distance to a given lateral end of the road. The method further comprises a step of determining the color of the substrate for at least one point being located on or having a predetermined distance to the determined trajectory.