# 1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey

arXiv: https://arxiv.org/abs/2304.10850 · HTML: https://mlsanity.com/paper/2304.10850/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Apr 2023.

## Built on by (most cited first, 8 of 8)

- [Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis](https://mlsanity.com/paper/2506.11526/) (2025)
- [Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling](https://mlsanity.com/paper/2411.17826/) (2024)
- [Controllable Collision Scenario Generation via Collision Pattern Prediction](https://mlsanity.com/paper/2510.12206/) (2025)
- [Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios](https://mlsanity.com/paper/2503.23708/) (2025)
- [Why Braking? Scenario Extraction and Reasoning Utilizing LLM](https://mlsanity.com/paper/2507.15874/) (2025)
- [Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving](https://mlsanity.com/paper/2607.14387/) (2026)
- [GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation](https://mlsanity.com/paper/2410.13514/) (2024)
- [Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems](https://mlsanity.com/paper/2507.22429/) (2025)

## Abstract (arXiv)

Scenario generation is one of the essential steps in scenario-based testing and, therefore, a significant part of the verification and validation of driver assistance functions and autonomous driving systems. However, the term scenario generation is used for many different methods, e.g., extraction of scenarios from naturalistic driving data or variation of scenario parameters. This survey aims to give a systematic overview of different approaches, establish different categories of scenario acquisition and generation, and show that each group of methods has typical input and output types. It shows that although the term is often used throughout literature, the evaluated methods use different inputs and the resulting scenarios differ in abstraction level and from a systematical point of view. Additionally, recent research and literature examples are given to underline this categorization.