AR Driving State Display Using Lane Detection Instead of HD Maps
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Solution Overview
Problem
Existing automated driving technologies rely on high-precision map data, which consumes significant storage, computing, and network resources, and fail to effectively integrate real-world environment correlations into navigation displays.
Innovation Solution
Discard high-precision map data and utilize vehicle driving state and environment sensing information to generate an augmented reality map through lane line detection, fusing scene images with driving state prompt elements for multi-dimensional display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-precision map data is used for navigation, then navigation accuracy is improved, but storage resource consumption, computing resource consumption, and network resource consumption increase
Solution Approach 1:
The patent extracts only the essential lane line information from the complex high-precision map data by performing lane line detection on real-time scene images. This extraction approach obtains the necessary navigation accuracy while eliminating the need to store and process the entire high-precision map dataset, thereby reducing storage resource consumption.
Solution Approach 2:
Instead of using pre-stored high-precision map data, the patent creates a real-time copy of lane line information by detecting and rendering lane lines directly from current scene images captured by the vehicle's sensors. This copying approach provides up-to-date navigation accuracy without the overhead of storing large map datasets.
2Measurement precision
If high-precision map data is used for navigation, then navigation accuracy is improved, but computing resource consumption increases
Solution Approach 1:
The patent extracts only the essential lane line information from the complex high-precision map data by performing lane line detection on real-time scene images. This extraction approach obtains the necessary navigation accuracy while eliminating the need to store and process the entire high-precision map dataset, thereby reducing storage resource consumption.
Solution Approach 2:
Instead of using pre-stored high-precision map data, the patent creates a real-time copy of lane line information by detecting and rendering lane lines directly from current scene images captured by the vehicle's sensors. This copying approach provides up-to-date navigation accuracy without the overhead of storing large map datasets.
3Measurement precision
If high-precision map data is used for navigation, then navigation accuracy is improved, but network resource consumption increases
Solution Approach 1:
The patent extracts only the essential lane line information from the complex high-precision map data by performing lane line detection on real-time scene images. This extraction approach obtains the necessary navigation accuracy while eliminating the need to store and process the entire high-precision map dataset, thereby reducing storage resource consumption.
Solution Approach 2:
Instead of using pre-stored high-precision map data, the patent creates a real-time copy of lane line information by detecting and rendering lane lines directly from current scene images captured by the vehicle's sensors. This copying approach provides up-to-date navigation accuracy without the overhead of storing large map datasets.
4Loss of information
If environment sensing information is fused with driving state prompt elements, then the correlation between real environment and driving state is improved, but device complexity increases
Solution Approach 1:
The patent merges the environment sensing information (scene images) with the driving state prompt elements (detected lane lines and vehicle state) into a unified augmented reality navigation display. This merging presents the correlated real-world driving state in an integrated visual interface, showing both the actual environment and the detected driving state information together.
Solution Approach 2:
The patent uses an augmented reality rendering system as an intermediary to fuse the environment sensing information with the driving state prompt elements. This intermediary process integrates the scene images with the detected lane lines and vehicle state information, presenting a unified correlated view without requiring direct complex interactions between all system components.
Data Source
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AI summary
This application relates to the field of computer technologies, and in particular, to a vehicle driving state display method and apparatus, an electronic device, and a storage medium, so as to effectively display a vehicle driving state, and may be applied to a map, transportation, automated driving, and the like. The method includes: obtaining a vehicle driving state of a current vehicle, and obtaining environment sensing information that is related to a current driving scene of the current vehicle and includes a scene image of the current driving scene; performing lane line detection on the scene image to obtain lane information in the current driving scene; and generating a driving state prompt element corresponding to the vehicle driving state based on the lane information, and performing superposed fusion on the driving state prompt element and the environment sensing information to render, generate, and display an augmented reality map. In this application, only a vehicle driving state and related environment sensing information are required, to render and generate an augmented reality map, thereby effectively displaying the vehicle driving state.