3D Vehicle Display for Drivable Surface and Obstacle Detection
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Solution Overview
Problem
Current vehicle data display systems struggle to effectively detect and display drivable areas and non-drivable obstacles in various environmental conditions, such as darkness and inclement weather, due to limitations in radar and camera technologies, which lack distance information and rely on specific object recognition that is not universally applicable.
Innovation Solution
A vehicle data display system equipped with a 3D sensor, such as LIDAR, and an electronic controller that processes cloud data to generate a 3D model of physical features around the vehicle, including ground surfaces and non-drivable obstacles, providing real-time data points on distance, direction, and vertical location, independent of lighting and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera-based systems are used to detect physical features, then object identification is possible, but detection is not consistent in darkness or inclement weather and lacks distance information
Solution Approach 1:
The system merges LIDAR technology with camera-based systems to combine the distance measurement capabilities of LIDAR with the object identification capabilities of cameras, creating a unified sensing system that operates reliably in all environmental conditions
Solution Approach 2:
The LIDAR system provides universal detection capability that works independently of lighting conditions and weather, detecting both distance and physical features through laser ranging technology that penetrates darkness, rain, snow, and fog
2Reliability
If radar is used to detect physical features, then detection range is achieved, but radar cannot detect features like curbs, speed bumps, and potholes
Solution Approach 1:
The system replaces radar's electromagnetic wave detection with LIDAR's laser-based optical detection, which provides superior precision for detecting surface features like curbs, speed bumps, and potholes through time-of-flight measurements that capture vertical dimension information
3Loss of information
If camera images are interpreted into 3D scene understanding, then spatial understanding is achieved, but this requires non-repeating features and object identification training that is location-dependent
Solution Approach 1:
The system extracts direct 3D geometric information from LIDAR point cloud data, eliminating the need for complex object identification algorithms and training data, as the depth and spatial information are directly measured rather than inferred from 2D images
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 system effectively displays drivable areas and non-drivable features in real-time, enhancing driver safety by providing accurate and universal detection of obstacles regardless of environmental conditions, without the need for object recognition training, and reducing the operator's monitoring burden.
Implementation Method 1
A 3D sensor, such as LIDAR, and an electronic controller that processes cloud data to generate a 3D model of physical features around the vehicle
Data Source
AI summary
A vehicle data display system includes an electronic display installed within a vehicle, a 3-D sensor and an electronic controller. The 3-D sensor configured to scan areas forward of and along lateral sides of the vehicle producing point cloud. Each data point of the cloud data corresponding to a surface portion of a physical feature. Each data point includes distance, direction and vertical location of each surface point. The electronic controller is connected to the electronic display and the 3-D sensor. The electronic controller receives and evaluates the point cloud from the 3-D sensor generating a 3-D model of detected ones of the physical features around the vehicle including ground surfaces, non-drivable features and driving limiting features relative to the vehicle. The non-drivable features are features that have predetermined geometric relationships with adjacent ground surfaces such that caution is to be taken when driving over or on driving limiting features.