Road Feature Point Extraction for Precise Autonomous Vehicle Control
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Solution Overview
Problem
Current autonomous driving systems face challenges in accurately extracting and providing relevant road information, leading to imprecise vehicle control, as they often extract unnecessary data and fail to identify critical road features like acceleration lane start and end points, affecting operations such as acceleration, deceleration, and lane changing.
Innovation Solution
A road feature point extraction method that uses high-precision map information and navigation data to determine and extract specific road feature points relevant to vehicle control, such as acceleration lane, deceleration lane, and main road widening/narrowing points, reducing data analysis and enhancing accuracy by combining navigation and map information redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If general road information is extracted from map information, then the vehicle can obtain road data, but useless information is extracted and really necessary information is not extracted
Solution Approach 1:
The patent extracts only the necessary road feature points (acceleration lane start/end points, deceleration lane start/end points, main road widening/narrowing points) from the map information, rather than extracting all general road information. This selective extraction ensures that useful information is captured while minimizing unnecessary data processing.
Solution Approach 2:
The patent applies different extraction criteria to different road feature types based on their specific characteristics. For example, acceleration lanes require extraction of start and end points for longitudinal control, while main road widening requires identification of specific location points. This localized approach ensures each feature type is extracted with the appropriate level of detail.
2Reliability
If general road information is extracted, then road data is available, but the information is not targeted and cannot accurately control vehicle operations
Solution Approach 1:
The patent extracts only the specific road feature points necessary for accurate vehicle control operations. By identifying and extracting only acceleration lane start/end points, deceleration lane start/end points, and main road widening/narrowing points, the system provides targeted information that directly supports longitudinal and lateral control without unnecessary data complexity.
3Measurement precision
If navigation information and map information are combined, then the accuracy of extracting road feature points is improved, but the data processing complexity increases
Solution Approach 1:
The patent combines navigation information (current position, heading) with map information (road geometry, feature points) to accurately determine the vehicle's location and extract relevant road feature points. This integration allows the system to identify acceleration lanes, deceleration lanes, and main road widening/narrowing points with high precision by correlating real-time navigation data with pre-stored map data.
Data Source
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AI summary
Disclosed are a road feature point extraction method and system. The road feature point extraction method comprises: acquiring map information for the current position of a vehicle (S110), wherein the map information comprises the attributes of the current road and the attributes of the next road section; comparing the attributes of the current road with the attributes of the next road section to determine the road type of the next road section (S120); and extracting, in conjunction with the road type of the next road section and the map information corresponding to the next road section, a road feature point representing a road scene on the next road section, and outputting the name of the extracted road feature point and information of the relative distance between the road feature point and the vehicle (S130). By determining a road feature point capable of precisely representing a road scene and extracting the name and position information of an important road feature point relating to vehicle control, without the need for separately collecting overall road information in the vicinity of the current position of a vehicle, the vehicle can be precisely controlled.