Vehicle Lane Tracking Using LiDAR Virtual Boxes and Histograms
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Solution Overview
Problem
Existing vehicle control systems struggle to accurately identify the driving direction and type of external objects using LiDAR sensors, particularly in determining the lane and heading direction of vehicles, which is crucial for safe navigation and autonomous driving.
Innovation Solution
A vehicle control apparatus and method utilizing a processor to determine virtual boxes corresponding to road edges and external vehicles, merging or changing the heading direction of these boxes based on lateral and longitudinal distances, vehicle speed, and yaw rates, to enhance lane identification and object tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If LiDAR sensor is used to identify external objects, then object detection capability is improved, but measurement precision of driving direction and lane identification deteriorates
Solution Approach 1:
The patent divides the detection space into multiple virtual boxes corresponding to different lanes and road regions. Each virtual box independently tracks external vehicles, allowing the system to segment the complex task of lane identification into manageable regions, thereby improving measurement precision while maintaining comprehensive object detection coverage
Solution Approach 2:
The patent introduces histogram analysis as an additional dimension for processing LiDAR data. By generating histograms from tracked virtual boxes and using them to determine lane information, the system transforms raw spatial data into statistical patterns that enhance driving direction and lane identification accuracy without compromising object detection capability
2Reliability
If virtual boxes are used to track external vehicles, then object tracking capability is improved, but device complexity increases
Solution Approach 1:
The virtual box mechanism serves multiple functions simultaneously: it tracks external vehicles, determines lane identification, generates histograms for statistical analysis, and identifies driving directions. This multi-functionality reduces the need for separate tracking systems, thereby improving reliability without proportionally increasing device complexity
Solution Approach 2:
The patent merges the tracking of multiple external vehicles within adjacent lanes into a unified virtual box system. By combining tracking resources and using shared histogram analysis, the system achieves reliable multi-object tracking while reducing computational overhead and system complexity compared to independent tracking of each vehicle
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
Improves the accuracy of lane detection and object tracking, stabilizing vehicle control systems by effectively identifying and managing the position and direction of external vehicles, enhancing safety and autonomy in driving assistance and autonomous modes.
Implementation Method 1
identify an external object by using a sensor (e.g., light detection and ranging (LiDAR) sensor)
Data Source
AI summary
The present disclosure may relate to a vehicle control apparatus and a method. The vehicle control apparatus may determine virtual boxes for external vehicles between the first and second virtual boxes, determine a vehicle's lane from divided lanes using a virtual box location or tracking histograms, adjust virtual boxes or heading directions of a virtual box based on the vehicle's lane or adjacent vehicles, and signal the adjustments.