Enhancing Automotive User Experience With Dynamic Service Orchestration for Software Defined Vehicles
Year: 2024
Type: article
Abstract: With the increasing demand for dynamic behaviors in automotive use cases, Software Defined Vehicles (SDVs) have emerged as a promising solution by bringing dynamic onboard service management capabilities. While users may request a wide range of services during vehicle operation, background tasks such as cooperative Vehicle-to-Everything (V2X) services can activate on-the-fly in response to real-time road conditions. In this dynamic environment, the efficient allocation of onboard resources becomes a complex challenge, in order to meet mixed-criticality onboard Quality-of-Service (QoS) network requirements while ensuring an optimal user experience (UX). Additionally, the ever-evolving real-time network connectivity and computational availability conditions further complicate the process. In this context, first we introduce the concept of Automotive eXperience Integrity Level (AXIL) which expresses a runtime priority for non-safety-critical applications to enable dynamic orchestration. Second, we present a dynamic resource-based onboard service orchestration algorithm that considers real-time in-vehicle and V2X network health, along with onboard resource constraints, to select degraded modes for onboard applications and maximize user experience. Third, we show by simulation that our algorithm produces near-optimal solutions while significantly reducing execution time: it satisfies approximately 90% of the onboard UX compared to the optimal while reducing the execution time of one to two orders of magnitude compared to an exact solver. With this approach, we aim to enable efficient onboard execution for a UX-focused service orchestration.
Authors: Pierre Laclau, Stéphane Bonnet, Bertrand Ducourthial, Xiaoting Li, Trista Lin
Language: English
Topic: Real-Time Systems Scheduling
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404056795
