CARJAN: Agent-Based Generation and Simulation of Traffic Scenarios with AJAN
This addresses the need for accessible traffic scenario simulation tools for researchers and developers working with autonomous vehicles and urban planning, though it appears incremental as an integrated approach building on existing frameworks.
The researchers tackled the challenge of user-friendly modeling and simulation of urban traffic scenarios with diverse interacting agents by developing CARJAN, a tool that integrates AJAN and CARLA for semi-automated generation and simulation, providing a visual interface and SPARQL Behavior Tree-based decision-making.
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.