ITSC 2025 Paper Abstract

Paper TH-EA-T17.2

Dehler, Robin (Ulm University), Schumann, Oliver (Ulm University), Ruof, Jona (Ulm University), Buchholz, Michael (Universität Ulm)

Multi-Staged Framework for Safety Analysis of Offloaded Services in Distributed Intelligent Transportation Systems

Scheduled for presentation during the Invited Session "S17b-Synthetic-Data-Aided Safety-Critical Scenario Understanding in ITS" (TH-EA-T17), Thursday, November 20, 2025, 13:50−14:10, Southport 2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Integration of Autonomous Vehicles with Public and Private Transport Networks, Safety Verification and Validation Methods for Autonomous Vehicle Technologies, Autonomous Vehicle Safety and Performance Testing

Abstract

The integration of service-oriented architectures (SOA) with function offloading for distributed, intelligent transportation systems (ITS) offers the opportunity for connected autonomous vehicles (CAVs) to extend their locally available services. One major goal of offloading a subset of functions in the processing chain of a CAV to remote devices is to reduce the overall computational complexity on the CAV. The extension of using remote services, however, requires careful safety analysis, since the remotely created data are corrupted more easily, e.g., through an attacker on the remote device or by intercepting the wireless transmission. To tackle this problem, we first analyze the concept of SOA for distributed environments. From this, we derive a safety framework that validates the reliability of remote services and the data received locally. Since it is possible for the autonomous driving task to offload multiple different services, we propose a specific multi-staged framework for safety analysis dependent on the service composition of local and remote services. For efficiency reasons, we directly include the multi-staged framework for safety analysis in our service-oriented function offloading framework (SOFOF) that we have proposed in earlier work. The evaluation compares the performance of the extended framework considering computational complexity, with energy savings being a major motivation for function offloading, and its capability to detect data from corrupted remote services.