CBLab Datasets

该数据集包含了6个真实世界城市数据集和9个合成数据集，旨在为交通系统优化算法的性能评估提供基准。这些数据集支持典型的交通系统优化场景，并包含了使用生成式人工智能方法生成的真实起点-终点矩阵。数据集规模宏大，支持多达2,464,950辆车的数据。其任务是对交通系统优化算法进行基准测试。This dataset comprises 6 real-world urban datasets and 9 synthetic datasets, serving as a benchmark for performance evaluation of traffic system optimization algorithms. These datasets support typical traffic system optimization scenarios and contain real origin-destination (OD) matrices generated via generative artificial intelligence methods. Boasting a substantial scale, the dataset accommodates data for up to 2,464,950 vehicles, and its core task is to benchmark traffic system optimization algorithms.