Weather Classification Using an Automotive LIDAR Sensor Based on Detections on Asphalt and Atmosphere
A semi-/autonomous driving car requires local weather information to identify if it is working inside its operational design domain and adapt itself accordingly. This information can be extracted from changes in the detections of a light detection and ranging (LIDAR) sensor. These changes are caused...
Main Authors: | Jose Roberto Vargas Rivero, Thiemo Gerbich, Valentina Teiluf, Boris Buschardt, Jia Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-08-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/15/4306 |
Similar Items
-
Data Augmentation of Automotive LIDAR Point Clouds under Adverse Weather Situations
by: Jose Roberto Vargas Rivero, et al.
Published: (2021-06-01) -
Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions
by: Maria Jokela, et al.
Published: (2019-06-01) -
A Quantitative Analysis of Point Clouds from Automotive Lidars Exposed to Artificial Rain and Fog
by: Karl Montalban, et al.
Published: (2021-06-01) -
LiDAR Point Cloud Generation for SLAM Algorithm Evaluation
by: Łukasz Sobczak, et al.
Published: (2021-05-01) -
An Overview of Autonomous Vehicles Sensors and Their Vulnerability to Weather Conditions
by: Jorge Vargas, et al.
Published: (2021-08-01)