Lane-Accurate Occupancy Grid Map Creation
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Solution Overview
Problem
Current navigation systems for motorized transportation vehicles lack accurate representation of lane occupancy and traffic density, which is crucial for proactive traffic planning and route optimization.
Innovation Solution
A method and system that capture image sequences using cameras, identify and classify objects, and create a lane-accurate occupancy grid map by determining object positions and lane information, which is then transmitted to a map creation device for merging and updating a digital map, allowing for real-time traffic density calculation and route planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current navigation systems are used, then basic navigation functionality is provided, but accurate representation of lane occupancy and traffic density is lacking
Solution Approach 1:
The environment is divided into multiple sections along the direction of travel, with each section having a predetermined size and boundaries. This segmentation allows for detailed lane occupancy analysis in each section while maintaining overall traffic density representation, resolving the contradiction between measurement precision and information completeness.
Solution Approach 2:
The system transitions from traditional 2D map representation to a 3D occupancy grid map that includes lane-level detail. By adding the lane dimension to the occupancy representation, the system achieves both accurate lane occupancy measurement and comprehensive traffic density information simultaneously.
2Measurement precision
If detailed lane-level occupancy data is collected and processed, then accurate traffic density representation is achieved, but system complexity increases
Solution Approach 1:
The map creation device divides the environment into manageable sections with predetermined boundaries. This segmentation reduces the complexity of processing entire environments at once while maintaining detailed lane-level occupancy measurements in each section, making the system more tractable without sacrificing measurement precision.
Solution Approach 2:
The system creates simplified occupancy grid representations that capture essential lane occupancy information without requiring complete detailed models of all environmental features. This copying approach maintains accurate traffic density measurement while reducing overall system complexity.
Data Source
AI summary
A method for creating a lane-accurate occupancy grid map for lanes. In at least one mobile device, an environment is sensed by a camera and evaluated by an evaluating unit. The evaluating unit defines a section in the environment and determines a lane in the section. Objects in the environment or in the section are also detected and classified by the evaluating unit. The object information, section information, time information, and the lane information are transmitted to a map-creating device, which creates a lane-accurate occupancy grid map for the lane therefrom. The lane-accurate occupancy grid map can be transmitted back to the mobile device. Also disclosed is an associated system.