CoLD Fusion: A Real-time Capable Spline-based Fusion Algorithm for Collective Lane Detection

Fuente: arXiv
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Main Authors: Gamerdinger, Jörg, Teufel, Sven, Volk, Georg, Bringmann, Oliver
Format: Preprint
Published: 2025
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author Gamerdinger, Jörg
Teufel, Sven
Volk, Georg
Bringmann, Oliver
author_facet Gamerdinger, Jörg
Teufel, Sven
Volk, Georg
Bringmann, Oliver
contents Comprehensive environment perception is essential for autonomous vehicles to operate safely. It is crucial to detect both dynamic road users and static objects like traffic signs or lanes as these are required for safe motion planning. However, in many circumstances a complete perception of other objects or lanes is not achievable due to limited sensor ranges, occlusions, and curves. In scenarios where an accurate localization is not possible or for roads where no HD maps are available, an autonomous vehicle must rely solely on its perceived road information. Thus, extending local sensing capabilities through collective perception using vehicle-to-vehicle communication is a promising strategy that has not yet been explored for lane detection. Therefore, we propose a real-time capable approach for collective perception of lanes using a spline-based estimation of undetected road sections. We evaluate our proposed fusion algorithm in various situations and road types. We were able to achieve real-time capability and extend the perception range by up to 200%.
format Preprint
id arxiv_https___arxiv_org_abs_2512_14355
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CoLD Fusion: A Real-time Capable Spline-based Fusion Algorithm for Collective Lane Detection
Gamerdinger, Jörg
Teufel, Sven
Volk, Georg
Bringmann, Oliver
Robotics
Comprehensive environment perception is essential for autonomous vehicles to operate safely. It is crucial to detect both dynamic road users and static objects like traffic signs or lanes as these are required for safe motion planning. However, in many circumstances a complete perception of other objects or lanes is not achievable due to limited sensor ranges, occlusions, and curves. In scenarios where an accurate localization is not possible or for roads where no HD maps are available, an autonomous vehicle must rely solely on its perceived road information. Thus, extending local sensing capabilities through collective perception using vehicle-to-vehicle communication is a promising strategy that has not yet been explored for lane detection. Therefore, we propose a real-time capable approach for collective perception of lanes using a spline-based estimation of undetected road sections. We evaluate our proposed fusion algorithm in various situations and road types. We were able to achieve real-time capability and extend the perception range by up to 200%.
title CoLD Fusion: A Real-time Capable Spline-based Fusion Algorithm for Collective Lane Detection
topic Robotics
url https://arxiv.org/abs/2512.14355