PROVIDENT: Predictable Software Development in Connected Vehicles Utilising Blended TSN-5G Networks

Status:

active

Start date:

2020-09-01

End date:

2024-08-31

Modern vehicles in many segments of the vehicular domain need to communicate and collaborate to achieve a joint functionality in, e.g., an autonomous quarry, mine or a recycling site. To provide such functionality, these vehicles need to be equipped with high data-rate sensors (e.g., cameras and lidars). The large amount of data acquired from these sensors needs to be communicated within as well as among the vehicles with predictable low latencies. The traditional intra-vehicle communication (based on field buses) and inter-vehicle communication (based on WiFi and 4G) are becoming a bottleneck in meeting the high-bandwidth and low-latency communication requirements. The recently introduced IEEE Time-Sensitive Networking (TSN) standards and 5G communication offer promising solutions to address these requirements within and among the vehicles respectively. Alas, there is a lack of a holistic software development framework and execution environment for predictable vehicular systems that utilise blended TSN-5G communication. This lack hinders the vehicle industry from taking full advantage of these ground- breaking technologies. The aim of PROVIDENT is to develop novel techniques to provide a full- fledged holistic software development environment for vehicular systems that utilise blended TSN- 5G communication. The benefits for the vehicle industry include cost-efficient system development, better quality of developed functions to lower costs, and better use of expensive and scarce computing and communication resources. A major trait of the project consortium is that it offers a clear value chain initiating from academia (MDH); through a tools developer (Arcticus Systems); and finally to an end user of the technology (HIAB).

[Show all publications]

A Comprehensive Systematic Review of Integration of Time Sensitive Networking and 5G Communication (Jun 2023)
Zenepe Satka, Mohammad Ashjaei, Hossein Fotouhi, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen
Journal of Systems Architecture, 2023 (JSA)

Timing Predictability and Performance Standoff in Component-based Vehicle Software on Multi-core (Mar 2023)
Saad Mubeen
IEEE International Conference on Software Architecture Companion Proceedings (MDE4SA@ICSA 2023)

Communication Patterns for Evaluating Vehicular E/E Architectures (Nov 2022)
Elena Lisova, Ruben Broux, Joachim Denil , Alessio Bucaioni, Saad Mubeen
The 2nd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2022)

Schedulability Analysis of WSAN Applications: Outperformance of a Model Checking Approach (Sep 2022)
Ehsan Khamespanah , Morteza Mohaqeqi , Mohammad Ashjaei, Marjan Sirjani
International Conference on Emerging Technologies and Factory (ETFA'2022)

Concurrent OPC UA information model access, enabling real-time OPC UA PubSub (Sep 2022)
Patrick Denzler, Mohammad Ashjaei, Thomas Frühwirth , Victor Nicholas Ebirim , Wolfgang Kastner
International Conference on Emerging Technologies and Factory (ETFA'2022)

Cognitive and Time Predictable Task Scheduling in Edge-cloud Federation (Sep 2022)
Somayeh Abdi, Mohammad Ashjaei, Saad Mubeen
International Conference on Emerging Technologies and Factory (ETFA'2022)

PartnerType
Arcticus Systems AB Industrial
HIAB AB Industrial

Saad Mubeen, Professor

Email: saad.mubeen@mdu.se
Room: U1-142
Phone: +4621103191