# Engineering Automotive Digital Twins on Standardized Architectures: A Case Study

arXiv: https://arxiv.org/abs/2508.18662 · HTML: https://mlsanity.com/paper/2508.18662/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2025.

## Built on by (most cited first, 3 of 3)

- [Developing AI Agents with Simulated Data: Why, what, and how?](https://mlsanity.com/paper/2602.15816/) (2026)
- [Artificial Intelligence for Modeling & Simulation in Digital Twins](https://mlsanity.com/paper/2602.19390/) (2026)
- [DTScribe: Generating Models for Digital Twin Reporting using Local Large Language Models](https://mlsanity.com/paper/2610.18635/) (2026)

## Abstract (arXiv)

Digital twin (DT) technology has become of interest in the automotive industry. There is a growing need for smarter services that utilize the unique capabilities of DTs, ranging from computer-aided remote control to cloud-based fleet coordination. Developing such services starts with the software architecture. However, the scarcity of DT architectural guidelines poses a challenge for engineering automotive DTs. Currently, the only DT architectural standard is the one defined in ISO 23247. Though not developed for automotive systems, it is one of the few feasible starting points for automotive DTs. In this work, we investigate the suitability of the ISO 23247 reference architecture for developing automotive DTs. Through the case study of developing an Adaptive Cruise Control DT for a 1/10th-scale autonomous vehicle, we identify some strengths and limitations of the reference architecture and begin distilling future directions for researchers, practitioners, and standard developers.