雄安窄路密网环境下面向多路口信号协同及公交优先控制数据集

本数据集面向雄安新区窄路密网环境，基于数字道路多粒度交通仿真系统构建，支持多路口信号协同及公交优先控制算法优化研究。数据集包含4个.xlsx格式文件，分别记录信号协同控制算法优化前后与公交优先控制算法优化前后的仿真输出数据，在2025年9月仿真输出仿真区域涵盖雄安新区容东片区100个交叉口和5条公交线路，数据字段包括路口标识、交通流参数及公交运行指标等核心字段。本文首先对多粒度交通仿真系统进行算法部署，将信号协同控制算法和公交优先控制算法部署到系统上，保证系统能够在原有路网模型的基础上实现算法优化；其次在不采用算法的前提下运行仿真，得到优化前的路口通行数据和公交运行数据；随后将算法应用到仿真系统，对路网模型的信号配时方案进行优化，得到优化后的路口通行数据和公交运行数据；最后将优化前与优化后的数据进行对比，分析算法的优化效果。数据可靠性符合行业标准，该数据集填补了窄路密网场景下交通控制算法验证的数据空白，可为学术研究提供算法效果对比基础，同时保障长期可用性，助力智能交通与数字城市融合发展。Targeting the narrow-road dense-grid traffic environment of Xiong'an New Area, this dataset is constructed based on the multi-granularity traffic simulation system for digital roads, and supports research on the optimization of multi-intersection signal coordination and bus priority control algorithms. The dataset contains 4 files in .xlsx format, which respectively record the simulation output data before and after the optimization of the signal coordination control algorithm, as well as that before and after the optimization of the bus priority control algorithm. The simulation carried out in September 2025 covers the Rongdong District of Xiong'an New Area, involving 100 intersections and 5 bus routes. The core data fields include intersection identification, traffic flow parameters, bus operation indicators, and other relevant items. The development of this dataset follows the workflow below: Firstly, deploy the signal coordination control algorithm and bus priority control algorithm onto the multi-granularity traffic simulation system for digital roads, enabling the system to perform algorithm optimization based on the original road network model; Secondly, run the simulation without enabling any algorithms to collect the pre-optimization intersection traffic data and bus operation data; Thirdly, apply the aforementioned algorithms to the simulation system to optimize the signal timing plan of the road network model, and obtain the post-optimization intersection traffic data and bus operation data; Finally, compare the pre-optimization and post-optimization data to analyze the optimization effect of the algorithms. The data reliability complies with industry standards. This dataset fills the data gap for the verification of traffic control algorithms in narrow-road dense-grid scenarios, provides a fundamental basis for comparing algorithm effects in academic research, ensures long-term availability, and facilitates the integrated development of intelligent transportation and digital cities.

搜集汇总

背景与挑战

背景概述

该数据集针对雄安新区窄路密网环境，基于数字道路多粒度交通仿真系统构建，包含信号协同控制与公交优先控制算法优化前后的仿真输出数据，覆盖100个交叉口和5条公交线路。数据集以xlsx格式提供，支持多路口信号协同及公交优先控制算法的效果对比研究，为智能交通与数字城市融合发展提供数据基础。