English

LimSim: A Long-term Interactive Multi-scenario Traffic Simulator

Systems and Control 2023-07-27 v2 Robotics Systems and Control

Abstract

With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios is increasing. Existing simulation systems suffer from a lack of support for different types of scenarios, and the vehicle models used in these systems are too simplistic. Thus, such systems fail to represent driving styles and multi-vehicle interactions, and struggle to handle corner cases in the dataset. In this paper, we propose LimSim, the Long-term Interactive Multi-scenario traffic Simulator, which aims to provide a long-term continuous simulation capability under the urban road network. LimSim can simulate fine-grained dynamic scenarios and focus on the diverse interactions between multiple vehicles in the traffic flow. This paper provides a detailed introduction to the framework and features of the LimSim, and demonstrates its performance through case studies and experiments. LimSim is now open source on GitHub: https://www.github.com/PJLab-ADG/LimSim .

Keywords

Cite

@article{arxiv.2307.06648,
  title  = {LimSim: A Long-term Interactive Multi-scenario Traffic Simulator},
  author = {Licheng Wen and Daocheng Fu and Song Mao and Pinlong Cai and Min Dou and Yikang Li and Yu Qiao},
  journal= {arXiv preprint arXiv:2307.06648},
  year   = {2023}
}

Comments

Accepted by 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023)

R2 v1 2026-06-28T11:29:14.733Z