交通数盘场景交通拥堵数据

依托路段速度相关数据，进行加工、分析、构建模型，生成路段拥堵指数数据；丰富交通监测指标、精准判断道路实时交通运行情况，助力对区域交通规划和管理，有利于反映交通拥堵状况及指导交通管理。在自研的交通态势数盘平台上，通过对路段速度相关数据（路段速度、自有流速度），进行加工、分析、挖掘构建拥堵指数算法模型，最终生成路段拥堵指数数据；
一、数据来源
数据清理：从数据库中抽取路段速度相关数据，对数据进行清洗；
数据处理：对数据进行过滤、去除异常和缺失数据；对数据进行计算和分析，如特征分析、数据验证等；
二、算法建模
模型评估：使用历史车速范围或道路限速等数据对模型进行测试和评估，根据评估结果对模型进行优化；
算法描述：根据历史数据对模型进行训练，生成路段的自由流速度；依托路段的实时速度和自由流速度，通过拥堵算法计算生成路段拥堵指数数据。

Relying on road segment speed-related data, this work conducts processing, analysis and model construction to generate road segment congestion index data. It enriches traffic monitoring indicators, accurately judges real-time road traffic operation conditions, supports regional traffic planning and management, and helps reflect traffic congestion status and guide traffic management. On the self-developed traffic situation platform, by processing, analyzing and mining road segment speed-related data (including road segment speed and free-flow speed), we build a congestion index algorithm model and finally generate road segment congestion index data.

1. Data Sources
- Data Cleaning: Extract road segment speed-related data from the database and clean the data;
- Data Processing: Filter the data, remove abnormal and missing values; perform calculations and analysis on the data, such as feature analysis, data validation, etc.

2. Algorithm Modeling
- Model Evaluation: Test and evaluate the model using data such as historical vehicle speed ranges or road speed limits, and optimize the model based on the evaluation results;
- Algorithm Description: Train the model based on historical data to generate the free-flow speed of road segments; generate road segment congestion index data through the congestion algorithm based on the real-time speed and free-flow speed of the road segments.

搜集汇总

数据集介绍

特点

该数据集为交通数盘场景交通拥堵数据，包含501条记录，每日更新，数据结构包括路段id、城市id、拥堵指数等字段。数据通过自研算法模型生成，用于交通拥堵监测和管理，助力区域交通规划和管理。