# One Stack, Diverse Vehicles: Checking Safe Portability of Automated Driving Software

arXiv: https://arxiv.org/abs/2501.18769 · HTML: https://mlsanity.com/paper/2501.18769/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2025.

## Built on by (most cited first, 1 of 1)

- [Defining Operational Conditions for Safety-Critical AI-Based Systems from Data](https://mlsanity.com/paper/2601.22118/) (2026)

## Abstract (arXiv)

Integrating an automated driving software stack into vehicles with variable configuration is challenging, especially due to different hardware characteristics. Further, to provide software updates to a vehicle fleet in the field, the functional safety of every affected configuration has to be ensured. These additional demands for dependability and the increasing hardware diversity in automated driving make rigorous automatic analysis essential. This paper addresses this challenge by using formal portability checking of adaptive cruise controller code for different vehicle configurations. Given a formal specification of the safe behavior, models of target configurations are derived, which capture relevant effects of sensors, actuators and computing platforms. A corresponding safe set is obtained and used to check if the desired behavior is achievable on all targets. In a case study, portability checking of a traditional and a neural network controller are performed automatically within minutes for each vehicle hardware configuration. The check provides feedback for necessary adaptations of the controllers, thus, allowing rapid integration and testing of software or parameter changes.