Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis (doi:10.7910/DVN/V71K5R)

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Document Description

Citation

Title:

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis

Identification Number:

doi:10.7910/DVN/V71K5R

Distributor:

Harvard Dataverse

Date of Distribution:

2023-10-26

Version:

2

Bibliographic Citation:

Abhinav Nippani; Dongyue Li, 2023, "Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis", https://doi.org/10.7910/DVN/V71K5R, Harvard Dataverse, V2

Study Description

Citation

Title:

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis

Subtitle:

Accompanying Datasets

Identification Number:

doi:10.7910/DVN/V71K5R

Authoring Entity:

Abhinav Nippani (Northeastern University)

Dongyue Li (Northeastern University)

Distributor:

Harvard Dataverse

Access Authority:

Ryan Zhang

Holdings Information:

https://doi.org/10.7910/DVN/V71K5R

Study Scope

Keywords:

Computer and Information Science, Graph Neural Networks, Traffic Accident Analysis, Road Networks

Abstract:

Here we deposit the datasets we have extracted for ten states in the US. In each zip file, we include each state's accident records, road networks, and network features. For further information about using the dataset and how we extracted the data, check out our GitHub repository for instructions.

Notes:

For each state, because there are multiple files in the dataset, we uploaded a zip file that includes all the files for that state. As a summary, once you download the zip file, unzip it, then there should be the following files in it: (1) adj_matrix.pt: The sparse adjacency matrix of the road network. (2) accidents_monthly.csv: All accidents spanning multiple years and aggregated by month. (3) Nodes/: The node features, including weather information, every month. (4) node_features_{year}_{month}.pt: The weather information of a particular month. (5) Edges/: The edge features, including road and traffic volume information, if available. (6) edge_features.pt: Edge features describing the road information. (7) edge_features_traffic_{year}.pt: Traffic volume records of a particular year.

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

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CA-1.zip

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CA-2.zip

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DE.zip

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IA.zip

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IL.zip

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MA.zip

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MD.zip

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MN.zip

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MT.zip

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NV.zip

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NY.zip

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application/zip