View source for 17983771. VEHICLE LIDAR SYSTEM AND OBJECT DETECTION METHOD THEREOF simplified abstract (HYUNDAI MOTOR COMPANY)

=VEHICLE LIDAR SYSTEM AND OBJECT DETECTION METHOD THEREOF=


==Organization Name==

[[:Category:HYUNDAI MOTOR COMPANY|HYUNDAI MOTOR COMPANY]]


[[Category:HYUNDAI MOTOR COMPANY]]

==Inventor(s)==

[[:Category:Ju Hyeok Ra of Guri-si (KR)|Ju Hyeok Ra of Guri-si (KR)]][[Category:Ju Hyeok Ra of Guri-si (KR)]]

[[:Category:Hyun Ju Kim of Yongin-si (KR)|Hyun Ju Kim of Yongin-si (KR)]][[Category:Hyun Ju Kim of Yongin-si (KR)]]

==VEHICLE LIDAR SYSTEM AND OBJECT DETECTION METHOD THEREOF - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17983771 titled 'VEHICLE LIDAR SYSTEM AND OBJECT DETECTION METHOD THEREOF

==Simplified Explanation==

The abstract describes a method for detecting objects using a LiDAR system in a vehicle. Here is a simplified explanation of the abstract:

* The method involves creating a grid map based on freespace point data and object information.
* The grid map includes grids that represent the host vehicle lane, with the size of the grids determined by the lane width.
* The method calculates a road boundary candidate by analyzing the occupation percentages of objects in each lane and the distribution of the freespace point data.
* The calculated road boundary candidate is then adjusted based on information from a previous time point to improve accuracy.
* The method outputs road boundary information, which can be used for various purposes such as navigation or autonomous driving.

Potential applications of this technology:

* Autonomous driving systems can use the road boundary information to navigate and stay within the designated lanes.
* Advanced driver-assistance systems (ADAS) can utilize the road boundary information to provide warnings or assistance to the driver.
* Traffic management systems can benefit from the accurate road boundary information for monitoring and controlling traffic flow.

Problems solved by this technology:

* Accurate detection of road boundaries is crucial for safe and efficient navigation.
* Traditional methods may struggle with detecting road boundaries accurately in complex or dynamic environments.
* This technology addresses these challenges by combining freespace point data, object information, and historical data to calculate and adjust the road boundary candidate.

Benefits of this technology:

* Improved accuracy in detecting road boundaries, leading to safer navigation and reduced risk of accidents.
* The method can adapt to changing road conditions by incorporating historical data, ensuring reliable performance in various environments.
* The grid-based approach allows for efficient processing and analysis of the LiDAR data, making it suitable for real-time applications.


==Original Abstract Submitted==

An object detection method of a vehicle LiDAR system includes setting grids including a host vehicle lane according to a lane width on a grid map which is generated based on freespace point data and object information, and calculating a road boundary candidate based on occupation percentages of objects by lane calculated based on the object information and distributions of the freespace point data; and outputting road boundary information by correcting the calculated road boundary candidate based on information on a road boundary candidate determined at a previous time point.



[[Category:G06V20/56]]
[[Category:G01S17/89]]