  The emergence of Multimodal Large Language Models ((M)LLMs) has ushered in
new avenues in artificial intelligence, particularly for autonomous driving by
offering enhanced understanding and reasoning capabilities. This paper
introduces LimSim++, an extended version of LimSim designed for the application
of (M)LLMs in autonomous driving. Acknowledging the limitations of existing
simulation platforms, LimSim++ addresses the need for a long-term closed-loop
infrastructure supporting continuous learning and improved generalization in
autonomous driving. The platform offers extended-duration, multi-scenario
simulations, providing crucial information for (M)LLM-driven vehicles. Users
can engage in prompt engineering, model evaluation, and framework enhancement,
making LimSim++ a versatile tool for research and practice. This paper
additionally introduces a baseline (M)LLM-driven framework, systematically
validated through quantitative experiments across diverse scenarios. The
open-source resources of LimSim++ are available at:
https://pjlab-adg.github.io/limsim-plus/.
