DMVC

Crime and motor vehicle collisions are
distinct yet interrelated social phenomena, deeply
influenced by demographic distributions, economic
disparities, and systemic urban dynamics. This study
investigates the spatial and temporal patterns of crime
and motor vehicle collisions (MVCs) across New York
City (NYC), integrating quantitative machine learning
techniques and qualitative socio-economic analysis.
This research constructs a unified, structured feature
set at both borough and ZIP code levels by leveraging
multiple open-source datasets, including crime,

This data set contains all relevant data content required in the experiment, and all data are stored in.mat format. This format is a commonly used data file format in MATLAB software, which facilitates efficient data processing and analysis. Users can import these.mat files directly without additional data conversion or processing, saving time and improving productivity. In addition, the content in the dataset has been carefully curated to ensure the integrity and accuracy of the data, which is suitable for use in various experiments and research work.