Hierarchically and Cooperatively Learning Traffic Signal Control
Authors: Bingyu Xu, Yaowei Wang, Zhaozhi Wang, Huizhu Jia, Zongqing Lu669-677
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirically, we demonstrate that Hi Light outperforms state-of-the-art RL methods for traffic signal control in real road networks with real traffic. |
| Researcher Affiliation | Collaboration | Bingyu Xu1, Yaowei Wang1, Zhaozhi Wang2, Huizhu Jia2, Zongqing Lu2 1Peng Cheng Laboratory 2Peking University |
| Pseudocode | Yes | Algorithm 1 Hi Light training |
| Open Source Code | No | The paper mentions using 'City Flow (Zhang et al. 2019), an open-source simulator' and using 'open-source implementations' for baselines, but does not provide a link or state that the authors are releasing the source code for their own method, Hi Light. |
| Open Datasets | Yes | The road networks and traffic flows of Jinan, Hangzhou, and New York City are the public datasets1. 1https://traffic-signal-control.github.io/ |
| Dataset Splits | No | The paper mentions training and evaluating performance, but does not explicitly provide specific train/validation/test dataset splits, percentages, or sample counts needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running experiments, such as GPU models, CPU types, or cloud computing instance specifications. |
| Software Dependencies | No | The paper mentions using City Flow simulator, and algorithms like DQN and PPO, but does not provide specific version numbers for any software dependencies needed to replicate the experiment. |
| Experiment Setup | Yes | Hyperparameters Table 1 summarizes the hyperparameters of Hi Light, Co Light, and Press Light. For Co Light and Press Light, we use their open-source implementations. For fair comparison, we also use their default parameter settings which perform better than other settings as verified by experiments. |