# Towards a Skill- And Ability-Based Development Process for Self-Aware Automated Road Vehicles

arXiv: https://arxiv.org/abs/1708.02532 · HTML: https://mlsanity.com/paper/1708.02532/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2017.

## Built on by (most cited first, 6 of 6)

- [The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior](https://mlsanity.com/paper/2107.13507/) (2021)
- [Safety of the Intended Driving Behavior Using Rulebooks](https://mlsanity.com/paper/2105.04472/) (2021)
- [A Knowledge-based Approach for the Automatic Construction of Skill Graphs for Online Monitoring](https://mlsanity.com/paper/2102.08827/) (2021)
- [Towards Establishing Systematic Classification Requirements for Automated Driving](https://mlsanity.com/paper/2307.14058/) (2023)
- [Towards Scenario- and Capability-Driven Dataset Development and Evaluation: An Approach in the Context of Mapless Automated Driving](https://mlsanity.com/paper/2404.19656/) (2024)
- [An Ontology-based Approach Towards Traceable Behavior Specifications in Automated Driving](https://mlsanity.com/paper/2409.06607/) (2024)

## Abstract (arXiv)

The development of fully automated vehicles imposes new challenges in the development process and during the operation of such vehicles. As traditional design methods are not sufficient to account for the huge variety of scenarios which will be encountered by (fully) automated vehicles, approaches for designing safe systems must be extended in order to allow for an ISO~26262 compliant development process. During operation of vehicles implementing SAE Levels 3+ safe behavior must always be guaranteed, as the human driver is not or not immediately available as a fall-back. Thus, the vehicle must be aware of its current performance and remaining abilities at all times. In this paper we combine insights from two research projects for showing how a skill- and ability-based approach can provide a basis for the development phase and operation of self-aware automated road vehicles.