Traffic Flow Reconstruction Using Two-Stage Optimization Based on Microscopic and Macroscopic Features
Loading...
Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
This paper presents a two-stage optimization method for traffic reconstruction that considers both microscopic and macroscopic features. The method employs a microscopic driving model and uses the average speeds in the lanes as a macroscopic metric to reconstruct traffic that balances the characteristics of traffic flow and vehicle behaviors. Our results on the NGSIM dataset, conducted primarily on straight road segments, demonstrate that the proposed method effectively balances the preservation of microscopic-level details with the simulation of macroscopic traffic flows. Both stages of our method outperform previous work in their respective domains. Furthermore, animated results rendered in the CARLA simulator highlight the realism of the generated driving behaviors, underscoring the model's ability to accurately reproduce various scenarios observed in real-world traffic. By recovering physical simulation parameters from real data, our framework can be utilized to generate diverse, realistic traffic flows, supporting applications such as traffic animation, data augmentation, system testing, and traffic behavior analysis.
Description
CCS Concepts: Computing methodologies → Procedural animation; Interactive simulation
@inproceedings{10.2312:pg.20251262,
booktitle = {Pacific Graphics Conference Papers, Posters, and Demos},
editor = {Christie, Marc and Han, Ping-Hsuan and Lin, Shih-Syun and Pietroni, Nico and Schneider, Teseo and Tsai, Hsin-Ruey and Wang, Yu-Shuen and Zhang, Eugene},
title = {{Traffic Flow Reconstruction Using Two-Stage Optimization Based on Microscopic and Macroscopic Features}},
author = {Huang, Jung-Hao and Lai, Bo-Yun and Wong, Sai-Keung and Lin, Wen-Chieh},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-295-0},
DOI = {10.2312/pg.20251262}
}