Validating multi-sensor object tracking in Heavy-Duty Trucks with extended trailer dynamics for road traffic situations - UTU Tutkimustietojärjestelmä

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Validating multi-sensor object tracking in Heavy-Duty Trucks with extended trailer dynamics for road traffic situations

Tekijät: Adu-Kyere, Akwasi; Nigussie, Ethiopia; Isoaho, Jouni; Ronkainen, Jukka; Kyytinen, Arto

Toimittaja: Shakshuki, Elhadi

Konferenssin vakiintunut nimi: International Conference on Ambient Systems, Networks and Technologies Networks

Julkaisuvuosi: 2024

Journal: Procedia Computer Science

Kokoomateoksen nimi: The 15th International Conference on Ambient Systems, Networks and Technologies Networks (ANT) / The 7th International Conference on Emerging Data and Industry 4.0 (EDI40), April 23-25, 2024, Hasselt University, Belgium

Tietokannassa oleva lehden nimi: Procedia Computer Science

Vuosikerta: 238

Aloitussivu: 167

Lopetussivu: 174

eISSN: 1877-0509

DOI: https://doi.org/10.1016/j.procs.2024.06.012

Verkko-osoite: https://doi.org/10.1016/j.procs.2024.06.012

Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/457187506

Tiivistelmä

Multi-sensing technologies in vehicles have the potential to improve road and pedestrian safety. Freighting trucks with extended trailer face challenges in urban maneuvering due to limited visibility. In this paper, we evaluate and validate extended trailer dynamics for Heavy-Duty Trucks in road traffic situations with multi-sensor object tracking emphasizing trailer dynamics, back-end parameters, and characteristics that influence decision-making strategies. A custom in-vehicle compute unit, in combination with the onboard truck’s computer, facilitated this research.

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Julkaisussa olevat rahoitustiedot:
This research was performed within the “Programmable Systems for Intelligence in Auto- mobiles” (PRYSTINE) project. PRYSTINE has received funding within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union’s H2020 Framework Programme and National Authorities, under Grant No. 783190.