ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi

Marek Drewniak; Krzysztof Tokarz; Michał Rędziński

doi:10.1007/978-3-319-67077-5_22

ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi

Marek Drewniak
, Krzysztof Tokarz
, Michał Rędziński

Katedra Grafiki, Wizji Komputerowej i Systemów Cyfrowych (RAU/RAU6)

AIUT
Silesian University of Technology

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

2 Cytowania z bazy Scopus

Abstrakt

In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.

Język oryginału	angielski
Tytuł publikacji goszczącej	Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings
Redaktorzy	Piotr Jedrzejowicz, Gottfried Vossen, George A. Papadopoulos, Ngoc Thanh Nguyen, Bogdan Trawinski
Wydawca	Springer Verlag
Strony	227-237
Liczba stron	11
ISBN (drukowany)	9783319670768
Identyfikatory DOI	https://doi.org/10.1007/978-3-319-67077-5_22
Status publikacji	Opublikowano - 2017
Wydarzenie	9th International Conference on Computational Collective Intelligence, ICCCI 2017 - Nicosia, Cypr Czas trwania: 27 wrz 2017 → 29 wrz 2017

Seria publikacji

Nazwa	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Tom	10449 LNAI
ISSN (drukowany)	0302-9743
ISSN (elektroniczny)	1611-3349

Konferencja

Konferencja	9th International Conference on Computational Collective Intelligence, ICCCI 2017
Kraj/Terytorium	Cypr
Miejscowość	Nicosia
Okres	27/09/17 → 29/09/17

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 9 Przemysł, innowacje i infrastruktura

Obszary tematyczne ASJC Scopus

Informatyka teoretyczna
Informatyka ogólna

Uzyskaj dostęp do dokumentu

10.1007/978-3-319-67077-5_22

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Drewniak, M., Tokarz, K., & Rędziński, M. (2017). ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. W P. Jedrzejowicz, G. Vossen, G. A. Papadopoulos, N. T. Nguyen, & B. Trawinski (Red.), Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings (str. 227-237). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 10449 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-67077-5_22

Drewniak, Marek ; Tokarz, Krzysztof ; Rędziński, Michał. / ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings. redaktor / Piotr Jedrzejowicz ; Gottfried Vossen ; George A. Papadopoulos ; Ngoc Thanh Nguyen ; Bogdan Trawinski. Springer Verlag, 2017. str. 227-237 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{642d90ac732e4ef08ec984ff22b3b9ee,

title = "ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi",

abstract = "In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.",

keywords = "ADAS, CAN bus, CANoe, Ethernet, LIDAR, Raspberry Pi",

author = "Marek Drewniak and Krzysztof Tokarz and Micha{\l} R{\c e}dzi{\'n}ski",

note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 9th International Conference on Computational Collective Intelligence, ICCCI 2017 ; Conference date: 27-09-2017 Through 29-09-2017",

year = "2017",

doi = "10.1007/978-3-319-67077-5\_22",

language = "English",

isbn = "9783319670768",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "227--237",

editor = "Piotr Jedrzejowicz and Gottfried Vossen and Papadopoulos, \{George A.\} and Nguyen, \{Ngoc Thanh\} and Bogdan Trawinski",

booktitle = "Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings",

address = "Germany",

}

Drewniak, M, Tokarz, K & Rędziński, M 2017, ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. w P Jedrzejowicz, G Vossen, GA Papadopoulos, NT Nguyen & B Trawinski (red), Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), tom 10449 LNAI, Springer Verlag, str. 227-237, 9th International Conference on Computational Collective Intelligence, ICCCI 2017, Nicosia, Cypr, 27/09/17. https://doi.org/10.1007/978-3-319-67077-5_22

ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. / Drewniak, Marek; Tokarz, Krzysztof; Rędziński, Michał.
Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings. red. / Piotr Jedrzejowicz; Gottfried Vossen; George A. Papadopoulos; Ngoc Thanh Nguyen; Bogdan Trawinski. Springer Verlag, 2017. str. 227-237 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 10449 LNAI).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi

AU - Drewniak, Marek

AU - Tokarz, Krzysztof

AU - Rędziński, Michał

PY - 2017

Y1 - 2017

N2 - In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.

AB - In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.

KW - ADAS

KW - CAN bus

KW - CANoe

KW - Ethernet

KW - LIDAR

KW - Raspberry Pi

UR - https://www.scopus.com/pages/publications/85030842008

U2 - 10.1007/978-3-319-67077-5_22

DO - 10.1007/978-3-319-67077-5_22

M3 - Conference contribution

AN - SCOPUS:85030842008

SN - 9783319670768

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 227

EP - 237

BT - Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings

A2 - Jedrzejowicz, Piotr

A2 - Vossen, Gottfried

A2 - Papadopoulos, George A.

A2 - Nguyen, Ngoc Thanh

A2 - Trawinski, Bogdan

PB - Springer Verlag

T2 - 9th International Conference on Computational Collective Intelligence, ICCCI 2017

Y2 - 27 September 2017 through 29 September 2017

ER -

Drewniak M, Tokarz K, Rędziński M. ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. W Jedrzejowicz P, Vossen G, Papadopoulos GA, Nguyen NT, Trawinski B, redaktorzy, Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings. Springer Verlag. 2017. str. 227-237. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-67077-5_22

ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi

Abstrakt

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Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

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