CAR-Bench is a benchmark for evaluating AI voice assistants in a realistic automotive (car) environment. It tests an agent's ability to correctly use vehicle control tools, handle disambiguation, and avoid hallucinations.

Dataset Structure

The dataset is organized into task configs and mock data configs:

Tasks

Each task defines a user persona, an instruction, the initial vehicle/environment context, and the ground-truth sequence of tool-call… See the full description on the dataset page: https://huggingface.co/datasets/johanneskirmayr/car-bench-dataset.