暴雨打击下高速路网交通状态演化数据集

面向恶劣天气下的系统功能风险隐患影响分析项目需求，针对2023年8月20日美国圣迭戈市发生极端暴雨前后的高速公路路网交通状态演化进行分析，选择了该城市受极端暴雨核心影响区范围内的高速公路路网断面流量及相应的断面速度数据，以及蒙哥马利机场所采集得到的大气压、温度、相对湿度、风速、能见度、降水量以及天气特征总结共七类天气数据作为原始数据集。 为了保证数据质量，本课题在数据预处理阶段，针对原始数据集中存在的缺失和空值问题，通过基于时间序列的插值以及历史数据的均值估计，进行数据填补；针对数据中存在部分不合常理的异常数据，基于卡尔曼滤波方法对原始交通流量、速度以及各类天气特征数据进行平滑和去噪操作；针对交通流量、速度数据与天气特征数据时间粒度不一致的问题（原始交通流量、速度数据时间粒度为5分钟，天气数据集时间粒度为1分钟），以交通流量和速度数据的时间粒度为准，将天气特征数据进行集计，统一调整至5分钟。 数据预处理工作后，本数据集最终选择2023年7月15日至2023年8月25日圣迭戈市共44个周围片区高速公路路段的对应流量、速度数据和同一时间段下蒙哥马利机场采集的各类天气数据，并对同一时间点下的不同路段断面流量值和天气特征数据进行拼接操作，从而得到最终的模型标准化结构输入数据集，数据量大小为8.13MB。Targeting the project requirements for analyzing the impacts of potential system functional risks under severe weather, this study investigates the evolution of highway traffic network states before and after the extreme rainstorm that occurred in San Diego, USA on August 20, 2023. The original dataset is composed of two parts: 1) highway section flow and corresponding section speed data within the core affected area of the extreme rainstorm in San Diego; 2) seven types of weather data collected at Montgomery Airport, including atmospheric pressure, temperature, relative humidity, wind speed, visibility, precipitation, and weather condition summaries. To ensure data quality, during the preprocessing stage, we addressed missing and null values in the original dataset using time-series interpolation and mean estimation from historical data to fill the gaps. For the abnormal and unreasonable values in the data, we applied the Kalman filter method to smooth and denoise the original traffic flow, speed, and all weather feature data. To resolve the inconsistency in temporal granularity between traffic flow/speed data and weather feature data (the original traffic flow and speed data have a 5-minute granularity, while the weather dataset has a 1-minute granularity), we aggregated the weather feature data to align with the 5-minute granularity of the traffic data. After preprocessing, the final standardized model input dataset was constructed by selecting traffic flow and speed data from 44 highway sections across the surrounding areas of San Diego between July 15 and August 25, 2023, along with the corresponding weather data collected at Montgomery Airport during the same period. We then concatenated the section flow values of different road segments and weather feature data at the same timestamp. The total size of this dataset is 8.13 MB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于2023年8月20日美国圣迭戈市极端暴雨事件前后高速公路路网的交通状态演化，整合了2023年7月15日至8月25日期间44个高速公路路段的流量、速度数据以及蒙哥马利机场的天气数据。数据经过预处理和标准化，形成8.13MB的CSV和DOCX格式文件，用于支持暴雨天气下的交通预测与分析。