activity
20232026
most citedChoose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Driving

73 citations · 94 across the 12 of their papers we have counts for

collaborators

12 papers

cs.AI2026

Choose Your Game Wisely: Measuring Game-Theoretic Structures in Real-World Vehicle Interactions

Yueyuan Li, Rongcheng Nie, Weijie Xi +4

Game-theoretic models provide principled frameworks for modeling vehicle interactions, but their underlying temporal assumptions have not been systematically examined against real-…

cs.RO2026

RoadWeaver: Large-Scale Lane-Level HD Map Generation from Scratch for Autonomous Driving Simulation

Yueyuan Li, Zexi Chen, Weijie Xi +4

Autonomous driving simulation requires diverse and scalable lane-level HD maps to support long-horizon evaluation across complex road networks. Existing approaches either rely on h…

cs.RO2026

DSIP: A Dynamic Coordination Planner for Signal-Free Intersections using Diffusion-Model-Based Multi-Agent Motion Planning

Qian Hu, Haoyang Peng, Songan Zhang +2

Traffic signal control at urban intersections inherently introduces stop-and-go behavior, resulting in increased delays and reduced traffic efficiency, especially under high traffi…

cs.RO2026

A Stitch in Time Saves Nine: Preserving Policy Compatibility Under Perception Updates in End-to-End Autonomous Driving

Yueyuan Li, Yifei Xiao, Mingyang Jiang +3

End-to-end autonomous driving systems tightly couple perception and decision-making through latent representations. Consequently, updates to perception models can alter these repre…

cs.CV2026

A Pedestrian-Vehicle Interaction Benchmark and Annotation Framework for Unstructured Scenes via Uncalibrated Cameras

Haoyang Peng, Qian Hu, Songan Zhang +1

Predicting the interaction between pedestrian and vehicle is essential for autonomous driving safety in unstructured and semi-structured scenarios; however, this task is severely h…

cs.RO2026

REAP: Reinforcement-Learning End-to-End Autonomous Parking with Gaussian Splatting Simulator for Real2Sim2Real Transfer

Changze Li, Zhe Chen, Shaoyu Chen +7

In recent years, autonomous parking has made significant advances, yet parking tasks still face challenges in extreme scenarios such as mechanical and dead-end parking slots, often…

cs.CV2025

Learning-based 3D Reconstruction in Autonomous Driving: A Comprehensive Survey

Liewen Liao, Weihao Yan, Wang Xu +3

Learning-based 3D reconstruction has emerged as a transformative technique in autonomous driving, enabling precise modeling of environments through advanced neural representations.…

cs.AI2024

From Imitation to Exploration: End-to-end Autonomous Driving based on World Model

Yueyuan Li, Mingyang Jiang, Songan Zhang +3

In recent years, end-to-end autonomous driving architectures have gained increasing attention due to their advantage in avoiding error accumulation. Most existing end-to-end autono…

cs.CV2024

SS-ADA: A Semi-Supervised Active Domain Adaptation Framework for Semantic Segmentation

Weihao Yan, Yeqiang Qian, Yueyuan Li +3

Semantic segmentation plays an important role in intelligent vehicles, providing pixel-level semantic information about the environment. However, the labeling budget is expensive a…

cs.RO2024★ 21 cited

HOPE: A Reinforcement Learning-based Hybrid Policy Path Planner for Diverse Parking Scenarios

Mingyang Jiang, Yueyuan Li, Songan Zhang +3

Automated parking stands as a highly anticipated application of autonomous driving technology. However, existing path planning methodologies fall short of addressing this need due…

cs.RO2023★ 73 cited

Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Driving

Yueyuan Li, Wei Yuan, Songan Zhang +4

Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor savings. Over the past few years, the number of simulators for autonomous driving h…

cs.LG2023

Tactics2D: A Highly Modular and Extensible Simulator for Driving Decision-making

Yueyuan Li, Songan Zhang, Mingyang Jiang +4

Simulation is a prospective method for generating diverse and realistic traffic scenarios to aid in the development of driving decision-making systems. However, existing simulators…