交通数盘场景实时车速数据

依托回传的设备经纬度数据及对应的时间戳，进行加工、分析、构建模型，生成路段实时车速数据；利用实时车速数据分析道路的通行情况及车速分布情况，实现合理优化信号配时、优化交通流等目的。在自研的交通态势数盘平台上，SDK方式回传的设备位置数据，进行加工、分析、挖掘构建模型；通过聚合算法将车辆位置聚合到道路路网中，最终生成车辆的实时车速数据；
一、数据来源
数据清理：从数据库中抽取回传的经纬度数据，对数据进行清洗；
数据处理：对数据进行过滤、去除错误和缺失数据；对数据进行计算和分析，如数据聚合、特征分析、结果校准等；
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：根据设备位置数据，与道路路网中所有路段位置数据进行聚合关联；根据时间戳可计算出时间差，对数据进行分析、校准，最终生成实时车速数据。

Relying on the returned device longitude and latitude data and their corresponding timestamps, we conduct processing, analysis and model construction to generate real-time speed data for road segments. By analyzing road traffic conditions and speed distribution using the real-time speed data, objectives including rational signal timing optimization and traffic flow improvement can be achieved. On the self-developed traffic situation data platform, device location data transmitted back via SDK is processed, analyzed, mined and used to construct models; vehicle locations are aggregated into the road network through aggregation algorithms, and finally real-time vehicle speed data is generated.

1. Data Sources
1.1 Data Cleaning: Extract the returned longitude and latitude data from the database, and clean the dataset.
1.2 Data Processing: Filter the data to remove erroneous and missing values; perform calculations and analysis on the dataset, including data aggregation, feature analysis, result calibration, etc.

2. Algorithm Modeling
2.1 Model Evaluation: Test and evaluate the model using data such as historical speed ranges or road speed limits, and optimize the model based on the evaluation results.
2.2 Algorithm Description: Perform aggregation and association between device location data and the location data of all road segments in the road network; calculate the time difference based on timestamps, analyze and calibrate the data, and finally generate real-time speed data.

搜集汇总

数据集介绍

特点

交通数盘场景实时车速数据集由浙江云通数达科技有限公司提供，包含501条数据，每日更新。该数据集通过设备经纬度和时间戳数据生成实时车速，用于分析道路通行情况和优化交通流。