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Vision-based positioning of electric buses for assisted docking to charging stations

Nowak Tomasz, Nowicki Michał R., Skrzypczyński Piotr

International Journal of Applied Mathematics and Computer Science

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2022

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Vol. 32, no. 4

583--599

EN

We present a novel approach to vision-based localization of electric city buses for assisted docking to a charging station. The method assumes that the charging station is a known object, and employs a monocular camera system for positioning upon carefully selected point features detected on the charging station. While the pose is estimated using a geometric method and taking advantage of the known structure of the feature points, the detection of keypoints themselves and the initial recognition of the charging station are accomplished using neural network models. We propose two novel neural network architectures for the estimation of keypoints. Extensive experiments presented in the paper made it possible to select the MRHKN architecture as the one that outperforms state-of-the-art keypoint detectors in the task considered, and offers the best performance with respect to the estimated translation and rotation of the bus with a low-cost hardware setup and minimal passive markers on the charging station.

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Budowa wirtualnego środowiska do symulacji układów bezpieczeństwa

Otrębska M., Skarka W., Zamorski P.

Mechanik

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2014

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R. 87, nr 2CD

PL

W artykule przedstawiono metodykę budowy wirtualnego środowiska do symulacji układów bezpieczeństwa oraz zaawansowanych systemów wspomagania kierowcy. Opracowanie wirtualnego środowiska do symulacji systemów bezpieczeństwa w elektrycznym bolidzie MuShellka, startującym na zawodach Shell Eco-marathon, przyspieszyło i ułatwiło zaprojektowanie tych systemów. Układy te bazują na rzeczywistych systemach, które są wykorzystywane obecnie w samochodach. Przy pomocy specjalnego oprogramowania PreScan firmy TASS zaprojektowano i przebadano systemy: BLIS (system informujący kierowcę o pojawieniu się obiektu w martwym polu lusterka wstecznego), ACC (system skanujący przestrzeń przed bolidem), ACS (system działający w przypadku kolizji).

EN

The paper presents a methodology to build a virtual environment for safety systems simulation and advanced driver assistance systems. Development of virtual environment for safety systems simulation for electric vehicle MuShellka, during its development for 2013 Shell Eco-marathon, is much simpler and quicker. The system is based on real systems, which are currently used in automobiles. With the aid of special software PreScan from TASS, which is a computer simulator for advanced driver assistance systems, there were possibilities to design and test safety systems such as BLIS (Blind Spot Information System), ACC (Adaptive Cruise Control) and ACS (Automatic Crash System).

3

Standardization of ADAS functionalities for fully electric vehicles

Matysiak A., Niezgoda M., Kamiński T., Kruszewski M.

Archives of Transport System Telematics

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2013

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Vol. 6, iss. 4

31--36

EN

EcoGem Project was conducted in scope of ICT Green Cars Initiative under the Seventh Framework Program, during 2010-2013 period. EcoGem Consortium’s aim was to provide ICT-based solutions increasing the mobility of Fully Electric Vehicles (FEV). A FEV-dedicated Advanced Driver Assistance System was developed in scope of the Project. It included suitable monitoring, analysis, reasoning and management capabilities, which increased the autonomy and energy efficiency of FEVs. One of the Project’s goals was to deliver a significant contribution into standardization activities concerning management of external information provided to ADAS systems. During the project development, a contact with various standardization organizations was established. We contributed to the standard development activities of OGC and TISA. The article presents the proposed solutions with regard to EcoGem functionalities. Described in the article standardization contribution includes new FEV oriented propositions of specifications for transmission of multi-modal traffic and travel information as well as the attributes defining charging stations.