2019
DOI: 10.1371/journal.pone.0215159
|View full text |Cite
|
Sign up to set email alerts
|

A real-time road detection method based on reorganized lidar data

Abstract: Road Detection is a basic task in automated driving field, in which 3D lidar data is commonly used recently. In this paper, we propose to rearrange 3D lidar data into a new organized form to construct direct spatial relationship among point cloud, and put forward new features for real-time road detection tasks. Our model works based on two prerequisites: (1) Road regions are always flatter than non-road regions. (2) Light travels in straight lines in a uniform medium. Based on prerequisite 1, we put forward di… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
9
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
8
1
1

Relationship

0
10

Authors

Journals

citations
Cited by 28 publications
(9 citation statements)
references
References 31 publications
0
9
0
Order By: Relevance
“…This helps to differentiate between road segments, curbs, dividers, vegetation, etc. using the technique presented in [ 21 ]. Points with high reflectivity are also selected as they correspond to the bright surfaces such as lane markings and railings.…”
Section: Methodsmentioning
confidence: 99%
“…This helps to differentiate between road segments, curbs, dividers, vegetation, etc. using the technique presented in [ 21 ]. Points with high reflectivity are also selected as they correspond to the bright surfaces such as lane markings and railings.…”
Section: Methodsmentioning
confidence: 99%
“…Moreover, challenging weather conditions can cause poor visibility, directly affecting the accuracy of the vehicle's perception, which is one of the three main functions of an autonomous system. When it comes to perception, many sensors, such as cameras, LiDAR (light detection and ranging), and thermal imaging, have been used to detect the environment [7], [8], [9]. The research on road perception and recognition has gained significant importance in recent years, and many methods have been developed to support drivers' perception and recognition [10], [11].…”
Section: Multi-modal Sensor Fusion-based Semantic Segmentation For Sn...mentioning
confidence: 99%
“…An integral parts of robotics [17][18][19][20], object recognition with LiDAR sensor commonly depends on feature extraction for classification of objects. Accurate object detection and classification allows object tracking, road signs detection [21], scene understanding [22] and behaviour recognition [23]. 3D LiDAR traits based on local surface and key-points are amongst the main features for extraction within object recognition [24].…”
Section: Related Workmentioning
confidence: 99%