# CARJAN: Agent-Based Generation and Simulation of Traffic Scenarios with AJAN

arXiv: https://arxiv.org/abs/2508.21411 · HTML: https://mlsanity.com/paper/2508.21411/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 20 references that are in the map.
- First posted on arXiv 29 Aug 2025.

## Builds on (most cited first, 12 of 12)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles](https://mlsanity.com/paper/2106.11810/) (2021)
- [Behavior Trees in Robotics and AI: An Introduction](https://mlsanity.com/paper/1709.00084/) (2017)
- [DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving](https://mlsanity.com/paper/2408.00415/) (2024)
- [The Waymo Open Sim Agents Challenge](https://mlsanity.com/paper/2305.12032/) (2023)
- [Scenic: A Language for Scenario Specification and Scene Generation](https://mlsanity.com/paper/1809.09310/) (2018)
- [Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles](https://mlsanity.com/paper/2103.07403/) (2021)
- [Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers](https://mlsanity.com/paper/2106.12442/) (2021)
- [Behavior Trees in Action: A Study of Robotics Applications](https://mlsanity.com/paper/2010.06256/) (2020)
- [3D Environment Modeling for Falsification and Beyond with Scenic 3.0](https://mlsanity.com/paper/2307.03325/) (2023)
- [Risk Scenario Generation for Autonomous Driving Systems based on Causal Bayesian Networks](https://mlsanity.com/paper/2405.16063/) (2024)
- [On-Demand Scenario Generation for Testing Automated Driving Systems](https://mlsanity.com/paper/2505.14053/) (2025)

## Abstract (arXiv)

User-friendly modeling and virtual simulation of urban traffic scenarios with different types of interacting agents such as pedestrians, cyclists and autonomous vehicles remains a challenge. We present CARJAN, a novel tool for semi-automated generation and simulation of such scenarios based on the multi-agent engineering framework AJAN and the driving simulator CARLA. CARJAN provides a visual user interface for the modeling, storage and maintenance of traffic scenario layouts, and leverages SPARQL Behavior Tree-based decision-making and interactions for agents in dynamic scenario simulations in CARLA. CARJAN provides a first integrated approach for interactive, intelligent agent-based generation and simulation of virtual traffic scenarios in CARLA.