Adaptive service selection for enabling the mobility of autonomous vehicles

Elif Eryilmaz; Manzoor Ahmed Khan; Frank Trollmann; Sahin Albayrak

doi:10.1007/978-3-030-34255-5_14

Adaptive service selection for enabling the mobility of autonomous vehicles

Elif Eryilmaz, Manzoor Ahmed Khan, Frank Trollmann, Sahin Albayrak

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Recent advances in the Internet of Things (IoT) provides rich opportunities to future mobility services for the development of more flexible solutions. Instead of using a fixed set of data sources or services, applications can benefit from those flexible mechanisms by adapting to change in the sensing environment such as sensor disappearance/degradation or service unavailability. In this paper, we contribute with an approach that enables dynamic selection of the services for mobility to meet requirements of autonomous driving use-cases. Our approach is focused on different mobility services using available data sources and data processing methods with their related quality parameters. Those services are inspired by the standards and the dynamics of real-test road. We present a prototypical implementation of the mechanism for optimal service selection in an autonomous driving test environment and evaluated our testing results with respect to correctness and performance.

Original language	English
Title of host publication	Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings
Editors	Ioannis Chatzigiannakis, Boris De Ruyter, Irene Mavrommati
Publisher	Springer
Pages	203-218
Number of pages	16
ISBN (Print)	9783030342548
DOIs	https://doi.org/10.1007/978-3-030-34255-5_14
Publication status	Published - 2019
Externally published	Yes
Event	15th European Conference on Ambient Intelligence, AmI 2019 - Rome, Italy Duration: Nov 13 2019 → Nov 15 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11912 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th European Conference on Ambient Intelligence, AmI 2019
Country/Territory	Italy
City	Rome
Period	11/13/19 → 11/15/19

Keywords

Adaptive service selection
Autonomous driving
IoT
Mobility
Opportunistic sensing
Quality-optimal selection

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-34255-5_14

Cite this

Eryilmaz, E., Khan, M. A., Trollmann, F., & Albayrak, S. (2019). Adaptive service selection for enabling the mobility of autonomous vehicles. In I. Chatzigiannakis, B. De Ruyter, & I. Mavrommati (Eds.), Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings (pp. 203-218). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11912 LNCS). Springer. https://doi.org/10.1007/978-3-030-34255-5_14

Adaptive service selection for enabling the mobility of autonomous vehicles. / Eryilmaz, Elif; Khan, Manzoor Ahmed; Trollmann, Frank et al.
Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings. ed. / Ioannis Chatzigiannakis; Boris De Ruyter; Irene Mavrommati. Springer, 2019. p. 203-218 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11912 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Eryilmaz, E, Khan, MA, Trollmann, F & Albayrak, S 2019, Adaptive service selection for enabling the mobility of autonomous vehicles. in I Chatzigiannakis, B De Ruyter & I Mavrommati (eds), Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11912 LNCS, Springer, pp. 203-218, 15th European Conference on Ambient Intelligence, AmI 2019, Rome, Italy, 11/13/19. https://doi.org/10.1007/978-3-030-34255-5_14

Eryilmaz E, Khan MA, Trollmann F, Albayrak S. Adaptive service selection for enabling the mobility of autonomous vehicles. In Chatzigiannakis I, De Ruyter B, Mavrommati I, editors, Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings. Springer. 2019. p. 203-218. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-34255-5_14

Eryilmaz, Elif ; Khan, Manzoor Ahmed ; Trollmann, Frank et al. / Adaptive service selection for enabling the mobility of autonomous vehicles. Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings. editor / Ioannis Chatzigiannakis ; Boris De Ruyter ; Irene Mavrommati. Springer, 2019. pp. 203-218 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{0e7e0451357e4586897cf54b29d2dc6c,

title = "Adaptive service selection for enabling the mobility of autonomous vehicles",

abstract = "Recent advances in the Internet of Things (IoT) provides rich opportunities to future mobility services for the development of more flexible solutions. Instead of using a fixed set of data sources or services, applications can benefit from those flexible mechanisms by adapting to change in the sensing environment such as sensor disappearance/degradation or service unavailability. In this paper, we contribute with an approach that enables dynamic selection of the services for mobility to meet requirements of autonomous driving use-cases. Our approach is focused on different mobility services using available data sources and data processing methods with their related quality parameters. Those services are inspired by the standards and the dynamics of real-test road. We present a prototypical implementation of the mechanism for optimal service selection in an autonomous driving test environment and evaluated our testing results with respect to correctness and performance.",

keywords = "Adaptive service selection, Autonomous driving, IoT, Mobility, Opportunistic sensing, Quality-optimal selection",

author = "Elif Eryilmaz and Khan, {Manzoor Ahmed} and Frank Trollmann and Sahin Albayrak",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 15th European Conference on Ambient Intelligence, AmI 2019 ; Conference date: 13-11-2019 Through 15-11-2019",

year = "2019",

doi = "10.1007/978-3-030-34255-5_14",

language = "English",

isbn = "9783030342548",

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

publisher = "Springer",

pages = "203--218",

editor = "Ioannis Chatzigiannakis and {De Ruyter}, Boris and Irene Mavrommati",

booktitle = "Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings",

}

TY - GEN

T1 - Adaptive service selection for enabling the mobility of autonomous vehicles

AU - Eryilmaz, Elif

AU - Khan, Manzoor Ahmed

AU - Trollmann, Frank

AU - Albayrak, Sahin

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - Recent advances in the Internet of Things (IoT) provides rich opportunities to future mobility services for the development of more flexible solutions. Instead of using a fixed set of data sources or services, applications can benefit from those flexible mechanisms by adapting to change in the sensing environment such as sensor disappearance/degradation or service unavailability. In this paper, we contribute with an approach that enables dynamic selection of the services for mobility to meet requirements of autonomous driving use-cases. Our approach is focused on different mobility services using available data sources and data processing methods with their related quality parameters. Those services are inspired by the standards and the dynamics of real-test road. We present a prototypical implementation of the mechanism for optimal service selection in an autonomous driving test environment and evaluated our testing results with respect to correctness and performance.

AB - Recent advances in the Internet of Things (IoT) provides rich opportunities to future mobility services for the development of more flexible solutions. Instead of using a fixed set of data sources or services, applications can benefit from those flexible mechanisms by adapting to change in the sensing environment such as sensor disappearance/degradation or service unavailability. In this paper, we contribute with an approach that enables dynamic selection of the services for mobility to meet requirements of autonomous driving use-cases. Our approach is focused on different mobility services using available data sources and data processing methods with their related quality parameters. Those services are inspired by the standards and the dynamics of real-test road. We present a prototypical implementation of the mechanism for optimal service selection in an autonomous driving test environment and evaluated our testing results with respect to correctness and performance.

KW - Adaptive service selection

KW - Autonomous driving

KW - IoT

KW - Mobility

KW - Opportunistic sensing

KW - Quality-optimal selection

UR - http://www.scopus.com/inward/record.url?scp=85076301213&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85076301213&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-34255-5_14

DO - 10.1007/978-3-030-34255-5_14

M3 - Conference contribution

AN - SCOPUS:85076301213

SN - 9783030342548

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

SP - 203

EP - 218

BT - Ambient Intelligence - 15th European Conference, AmI 2019, Proceedings

A2 - Chatzigiannakis, Ioannis

A2 - De Ruyter, Boris

A2 - Mavrommati, Irene

PB - Springer

T2 - 15th European Conference on Ambient Intelligence, AmI 2019

Y2 - 13 November 2019 through 15 November 2019

ER -

Adaptive service selection for enabling the mobility of autonomous vehicles

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this