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Efficient Graph-Based V2V Free Space Fusion

Luthardt, Stefan ; Han, Chao ; Willert, Volker ; Schreier, Matthias (2019)
Efficient Graph-Based V2V Free Space Fusion.
2017 IEEE Intelligent Vehicles Symposium (IV). Redondo Beach, CA, USA (11.06. -14.06.2017)
Conference or Workshop Item, Secondary publication, Postprint

Luthardt_IV_2017_PFS_Fusion.pdf - Accepted Version
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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Efficient Graph-Based V2V Free Space Fusion
Language: English
Date: 16 January 2019
Place of Publication: Darmstadt
Year of primary publication: 2017
Publisher: IEEE
Book Title: IEEE Symposium on Intelligent Vehicle
Event Title: 2017 IEEE Intelligent Vehicles Symposium (IV)
Event Location: Redondo Beach, CA, USA
Event Dates: 11.06. -14.06.2017
Corresponding Links:

A necessary prerequisite for future driver assistance systems as well as automated driving is a suitable and accurate representation of the environment around the vehicle with a sufficient range. To extend the range of the environment representation, sharing the environment detections of multiple vehicles via vehicle-to-vehicle (V2V) communication is a promising approach. In this paper, we present a method to fuse shared free space detections from multiple vehicles. The detections are represented as Parametric Free Space (PFS) maps, which are especially suitable for real-time radio V2V-transmission due to their compactness.

A graph-based algorithm to fuse PFS maps is proposed that solves possible contradictions between the maps and incorporates the maps' uncertainty attributes. By solely operating on the contour, the fusion can be carried out by a simple path search in a fusion graph that is constructed from the maps. This results in an efficient method that finds the fusion result within few iterations.

To account for possible errors in the relative poses between the PFS maps, we furthermore present an adapted Iterative Closest Point (ICP) matching to align the maps before the fusion. Therein we employ a modified soft-assign scheme for robust outlier rejection, and incorporate the PFS maps' boundary orientation to improve the matching process. We show the capabilities of our method by presenting results on real test drive data.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-83584
Classification DDC: 600 Technology, medicine, applied sciences > 600 Technology
600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics (from 01.08.2022 renamed Control Methods and Intelligent Systems)
Date Deposited: 16 Jan 2019 12:16
Last Modified: 08 Dec 2023 08:03
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/8358
PPN: 442892624
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