Dynamic ROI Lidar Vehicle Detection on Curved Lanes
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Solution Overview
Problem
Conventional vehicle detection systems, such as Vision-Lidar Fusion, face errors when detecting vehicles on curved lanes, compromising traffic safety.
Innovation Solution
A vehicle detection assisting method and system that utilizes a dynamic region of interest (ROI) created based on the lane width and trace, using a lidar unit, width analyzing unit, and processing unit to accurately determine if a vehicle is on or leaves the lane, even on curved paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the whole front range is detected even if the lane is curved, then the detection coverage is improved, but the vehicle detection accuracy deteriorates due to curved lane causing detection errors
Solution Approach 1:
The patent applies local quality by creating a dynamic region of interest (ROI) that adapts to the local lane geometry. Instead of uniformly detecting the entire front range, the system adjusts the detection region's shape and position according to the curved lane trace, concentrating detection resources where vehicles are actually likely to be located relative to the current lane path.
Solution Approach 2:
The patent implements dynamics by making the detection region dynamic rather than static. The dynamic ROI continuously adjusts its parameters (position, size, orientation) based on real-time lane trace information and vehicle state, allowing the detection coverage to adapt to changing lane conditions while maintaining accurate vehicle detection.
2Measurement precision
If a dynamic region of interest is created according to lane width and trace, then the vehicle detection accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating the dynamic ROI parameters based on the detected lane trace and width before performing vehicle detection. The system prepares the detection region in advance according to the lane geometry, so that when vehicle detection is performed, the accurate region is already established, improving detection accuracy without adding complex real-time adjustment mechanisms.
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
This approach ensures accurate detection of vehicles on the lane and their departure from the lane, enhancing driving safety by reducing errors associated with curved lanes and optimizing processing load.
Implementation Method 1
a lidar unit, a width analyzing unit, a trace analyzing unit and a processing unit. The lidar unit is used for emitting a plurality of scanning lines.
Data Source
AI summary
A vehicle detecting detection assisting method and a vehicle detection assisting system are provided. The vehicle detection assisting method includes the following steps. A scanning range of a lidar unit is obtained. A width of a lane is obtained. A trace of the lane is obtained. A dynamic region of interest in the scanning range is created according to the width and the trace.