mlsanityData to 14 Oct 2026

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

arXiv 2508.21411 ↗First posted 29 Aug 2025cs.AIcited by 0

Not on the map. Why?

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.

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

12 of 20 references.

References · 12

  1. 2017CARLA: An Open Urban Driving Simulatorcited by 2,449
  2. 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclescited by 493
  3. 2017Behavior Trees in Robotics and AI: An Introductioncited by 107
  4. 2024DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Drivingcited by 98
  5. 2023The Waymo Open Sim Agents Challengecited by 86
  6. 2018Scenic: A Language for Scenario Specification and Scene Generationcited by 83
  7. 2021Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehiclescited by 21
  8. 2021Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centerscited by 16
  9. 2020Behavior Trees in Action: A Study of Robotics Applicationscited by 9
  10. 20233D Environment Modeling for Falsification and Beyond with Scenic 3.0cited by 6
  11. 2024Risk Scenario Generation for Autonomous Driving Systems based on Causal Bayesian Networkscited by 2
  12. 2025On-Demand Scenario Generation for Testing Automated Driving Systemscited by 1

Built on by

Not cited yet.