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Collaborative Mapping with IoE-based Heterogeneous Vehicles for Enhanced Situational Awareness
Univ Turku, Dept Future Technol, Turku, Finland..
KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Integrated devices and circuits.
Univ Turku, Dept Future Technol, Turku, Finland..
2019 (English)In: 2019 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

The development of autonomous vehicles or advanced driving assistance platforms has had a great leap forward to get closer to human daily life over the last decade. Nevertheless, it is still challenging to achieve an efficient and fully autonomous vehicle or driving assistance platform due to many strict requirements and complex situations or unknown environments. One of the main remaining challenges is a robust situation awareness in autonomous vehicles when the environment is unknoen. An autonomous system with a poor situation awareness due to low quantity or quality of data may directly or indirectly cause serious consequences. For instance, a person's life might be at risk due to a delay caused by a long or incorrect path planning of an autonomous ambulance. Internet of Everything (IoE) is currently becoming a prominent technology for many applications such as automation. In this paper, we propose an IoE-based architecture consisting of a heterogeneous team of cars and drones for enhancing situational awareness in autonomous cars, especially when dealing with critical cases of natural disasters. In particular, we show how an autonomous car can plan in advance the possible paths to a given destination, and send orders to other vehicles. These, in turn, perform terrain reconnaissance for avoiding obstacles and dealing with difficult situations. Together with a map merging algorithm deployed into the team autonomous vehicles, the proposed architecture can help to save traveling distance and time significantly in case of complex scenarios.

Place, publisher, year, edition, pages
IEEE , 2019.
Keywords [en]
swarm robotics, heterogeneous swarms, cooperative mapping, Internet-of-Everything (IoE), situational awareness
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:kth:diva-255513DOI: 10.1109/SAS.2019.8706110ISI: 000474727000095Scopus ID: 2-s2.0-85065919982OAI: oai:DiVA.org:kth-255513DiVA, id: diva2:1361701
Conference
14th IEEE Sensors Applications Symposium, SAS 2019; Sophia Antipolis; France; 11 March 2019 through 13 March 2019
Note

QC 20191016

Available from: 2019-10-16 Created: 2019-10-16 Last updated: 2019-10-16Bibliographically approved

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Tenhunen, Hannu

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