Supporting autonomous vehicles by creating HD maps

• Autorzy: Barsi A. , Poto V. , Somogyi A. , Lovas T. , Tihanyi V. , Szalay Z.
• Języki publikacji: EN

Abstrakty

EN

Maps are constantly developing, also, the newly defined High Definition (HD) maps increase the map content remarkably. They are based on three-dimensional survey, like laser scanning, and then stored in a fully new structured way to be able to support modern-day vehicles. Beyond the traditional lane based map content, they contain information about the roads’ neighbourhood. The goal of these maps is twofold. Primarily, they store the connections where the vehicles can travel with the description of the road-environment. Secondly, they efficiently support the exact vehicle positioning. The paper demonstrates the first results of a pilot study in the creation of HD map of an urban and a rural environment. The applied data collection technology was the terrestrial laser scanning, where the obtained point cloud was evaluated. The data storage has been solved by an in-house developed information storage model with the ability to help in vehicle control processes.

Słowa kluczowe

EN

High Definition map; vehicle navigation; laser scanning; point cloud

PL

nawigacja pojazdów; skanowanie laserowe; chmura punktów; mapy HD

• Wydawca: Oficyna Wydawnicza Stowarzyszenia Menedżerów Jakości i Produkcji
• Czasopismo: Production Engineering Archives
• Rocznik: 2017
• Tom: Vol. 16
• Strony: 43--46
• Opis fizyczny: Bibliogr. 5 poz., rys., tab.

Twórcy

autor

Barsi A.

• Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Muegyetem rakpart 3, Budapest, Hungary

autor

Poto V.

• Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Muegyetem rakpart 3, Budapest, Hungary

autor

Somogyi A.

• Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Muegyetem rakpart 3, Budapest, Hungary

autor

Lovas T.

• Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Muegyetem rakpart 3, Budapest, Hungary

autor

Tihanyi V.

• Department of Automotive Technologies, Budapest University of Technology and Economics, Stoczek utca 6, Budapest, Hungary

autor

Szalay Z.

• Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Muegyetem rakpart 3, Budapest, Hungary

Bibliografia

• 1. CLOUDCOMPARE, http://www.cloudcompare.org/ (Last access: 04/15/2017).
• 2. DETREKŐI Á. 1991. Adjustment calculation [in Hungarian]. Tankönyvkiadó, Budapest.
• 3. FARO SCENE SOFTWARE, http://www.faro.com/en-us/products/faro-software/scene/overview (Last access: 04/15/2017). NDS OPEN LANE MODEL, http://www.openlanemodel.org/ (Last access: 04/15/2017).
• 4. MATTHAEI R., MAURER M. 2016. Autonomous driving – a top-down-approach, at – Automatisierungstechnik. Vol. 63, No. 3, 155-167.
• 5. LI Q., CHEN L., LI M., SHAW S., NÜCHTER A. 2014. A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios. IEEE Transactions on Vehicular Technology, Vol. 63, No. 2, 540-555.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).