Smart Roadside Obstacle Filtering for Autonomous Vehicle Navigation
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Solution Overview
Problem
Smart roadside units face challenges in accurately detecting obstacles for autonomous vehicles due to the inclusion of the vehicle itself in obstacle sets, which affects navigation safety and reliability.
Innovation Solution
A method involving a smart roadside unit that uses a radar to detect obstacles, acquires status information from autonomous vehicles, filters out the vehicle object from the obstacle set based on this information, and sends the filtered set to the vehicle, enhancing navigation accuracy and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the radar detects all objects in the environment, then the obstacle detection coverage is improved, but the autonomous vehicle object is incorrectly included in the obstacle set, reducing navigation safety
Solution Approach 1:
The patent extracts and removes the autonomous vehicle object from the obstacle set by comparing detected objects with the vehicle's own status information (position, speed, acceleration). This extraction principle resolves the contradiction by maintaining comprehensive obstacle detection while eliminating the false inclusion of the vehicle itself, thereby preserving navigation safety.
2Loss of information
If the smart roadside unit sends all detected obstacle information to the autonomous vehicle, then the information completeness is improved, but the navigation accuracy is reduced due to inclusion of vehicle itself
Solution Approach 1:
The patent applies the extraction principle by removing the autonomous vehicle object from the obstacle set before transmitting information to the vehicle. This ensures that the transmitted obstacle information is both complete (including all actual obstacles) and accurate (excluding the vehicle itself), thereby resolving the contradiction between information completeness and navigation accuracy.
3Measurement precision
If the smart roadside unit uses multiple sensing detectors, then the sensing capability is improved, but the device complexity increases
Solution Approach 1:
The patent employs multiple sensing detectors (radar, camera) with each detector serving multiple functions: obstacle detection, vehicle identification, and status monitoring. This multi-functionality approach maintains high sensing capability while managing device complexity by making the detectors versatile rather than requiring specialized equipment for each function.
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
This approach improves the safety and reliability of autonomous vehicle navigation by ensuring that the vehicle itself is removed from the obstacle detection set, allowing for more precise automatic navigation.
Implementation Method 1
detecting the at least one obstacle via a radar to generate an obstacle set
Data Source
AI summary
Provided are a method for indicating at least one obstacle by a smart roadside unit, a system and a non-temporary computer-readable storage medium. The method includes: detecting the at least one obstacle via a radar to generate an obstacle set; acquiring status information reported by an autonomous vehicle; filtering the obstacle set according to the status information reported by the autonomous vehicle, to remove the autonomous vehicle object from the obstacle set; and sending a filtered obstacle set to the autonomous vehicle.