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  • Summary & Details

Crowdsourced Generation of Parking Maps Using Mass-Production Vehicle Data for Parking-to-Parking Automated Driving

Parking-to-Parking自動運転に向けた市販車データに基づくクラウドソーシングの駐車場地図生成手法の検討

Detailed Information

Author(J)1) 加藤 雄大, 2) 早川 和孝, 3) 岡部 寛, 4) 前川 敬介, 5) 長瀬 伊織, 6) 福田 直季
Author(E)1) Yudai Kato, 2) Kazutaka Hayakawa, 3) Hiroshi Okabe, 4) Keisuke Maekawa, 5) Iori Nagase, 6) Naoki Fukuda
Affiliation(J)1) アイシン, 2) アイシン, 3) アイシン, 4) パナソニックアドバンストテクノロジー, 5) パナソニックアドバンストテクノロジー, 6) アイシン
Affiliation(E)1) Aisin, 2) Aisin, 3) Aisin, 4) Panasonic Advanced Technology Development, 5) Panasonic Advanced Technology Development, 6) Aisin
Abstract(J)出発地の駐車区画から目的地の駐車区画まで公道および駐車場内を含めて自動走行する機能(Parking to Parking)を実現するため,本研究では市販車から収集されるセンサデータを活用した駐車場地図のクラウドソーシング生成技術を検討する.GNSSが利用困難な屋内・地下環境においても,複数車両の観測を統合することで幾何情報と意味情報を付与した地図を生成し,継続的な更新を可能とする.専用計測車両に依存しない低コストかつスケーラブルな地図構築方式の実現を目指し,提案手法の構成および有効性を検討する.

Translation

Abstract(E)Parking to Parking (P2P), which enables automated driving from an origin parking space to a destination parking space including both public roads and parking environments, is an important capability for next-generation mobility systems. To realize P2P, this study proposes a crowdsourced mapping technique for parking environments using sensor data collected from mass-production vehicles. Even under GNSS-denied conditions such as indoor and underground environments, the proposed method integrates observations from multiple vehicles to generate maps enriched with both geometric and semantic information. Furthermore, the approach enables continuous map updates without relying on dedicated mapping vehicles. The proposed framework aims to achieve a low-cost and scalable mapping solution, and its system architecture and effectiveness are investigated.

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