Big Data Visualization and Spatiotemporal Modeling of Risky Driving [supporting dataset]

Jahangiri, Arash; Machiani, Sahar Ghanipoor; Tsou, Ming-Hsiang; Nara, Atsushi; Harwood, Leslie; San Diego State University; Safety through Disruption (Safe-D) University Transportation Center (UTC); Virginia Tech Transportation Institute

doi:10.15787/VTT1/KOT55T

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Big Data Visualization and Spatiotemporal Modeling of Risky Driving [supporting dataset]

2019-11-19
See Associated Publication(s)
By Jahangiri, Arash ; Machiani, Sahar Ghanipoor ; Tsou, Ming-Hsiang ; ...

[PDF-144.43 KB]

English

Details Supporting Files Publications You May Also Like

Details:

Alternative Title:

Big Data Visualization and Spatiotemporal Modeling of Aggressive Driving (03-087) [Dataset title]
Creators:

Jahangiri, Arash ; Machiani, Sahar Ghanipoor ; Tsou, Ming-Hsiang ; Nara, Atsushi ; Harwood, Leslie

Jahangiri, Arash ; Machiani, Sahar Ghanipoor ; Tsou, Ming-Hsiang ; Nara, Atsushi ; Harwood, Leslie Less -
Corporate Creators:

San Diego State University ; Safety through Disruption (Safe-D) University Transportation Center (UTC) ; Virginia Tech Transportation Institute

San Diego State University ; Safety through Disruption (Safe-D) University Transportation Center (UTC) ; Virginia Tech Transportation Institute Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Aggression Behavior Big Data Analytics Cluster Analysis Data Analysis Data Mining Data Visualization Drivers Driving Risky Driving Behavior Simulation Spatial Analysis Time Visualization
Publication/ Report Number:

03-087
DOI:

https://doi.org/10.15787/VTT1/KOT55T
Resource Type:

Dataset
Geographical Coverage:

United States
Corporate Publisher:

Safety through Disruption (Safe-D) University Transportation Center (UTC)
Abstract:

Project Description: The study goal was to identify risky driving behavior using data mining methods within a large dataset. The data used in this study was obtained from the SPMD study conducted in Ann Arbor, Michigan. Data Scope: One week of SPMD data was processed to create a data table (each row representing a monitoring period) in csv format. Total number of observations for this table was 320 million with a total of 32 variables (i.e., columns). Data Specification: A detailed description of each variable in dataset can be found in Appendix A.
Format:

ZIP
Funding:

69A3551747115/Project 03-087
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:bf0551e31890516ed65bbc220fd7ca7bb8d0681f6f974f35695adcf105f3c539
Download URL:

https://rosap.ntl.bts.gov/view/dot/56819/dot_56819_DS1.pdf
File Type:

Big_Data_Visualization_and_Spatiotemporal_Modeling_of_Risky_Driving.json

json

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