Road marking detection using LIDAR reflective intensity data and its application to vehicle localization

145 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, methodology): “A road marking detection method using lidar and Monte Carlo Localization (MCL) was used in [94].”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, methodology): “The lidar reflection intensity can be analyzed using a modified Otsu method to recognize the road marking, which is robust to the lighting conditions [95], [96].”
Robust localization using 3D NDT scan matching with experimentally determined uncertainty and road marker matching (2017, methodology): “Localization methods using these objects have been previously proposed [2], [3], [4], [5], [6].”
A Hybrid Vision-Map Method for Urban Road Detection (2017, background): “That property makes them detectable with a LIDAR sensor since they detect surface reflectivity intensity [11].”
Computer vision in automated parking systems: Design, implementation and challenges (2017, unknown): “the road markings, as exemplified in [13].”
Computing Systems for Autonomous Driving: State of the Art and Challenges (2020, background): “Landmarks, such as poles, curbs, signs, and road markers, can be detected with LiDAR [108] or camera [109].”