Automated Vehicle Crash Rate Comparison Using Naturalistic Data
The fundamental objectives of the research described in this report are to improve the quality of the available data involving self-driving cars and to analyze existing data to better understand the relative crash rate of self-driving cars. Five research questions guided this analysis: (1) How many crashes go unreported to police or insurance? (2) Do unreported crash rates vary by location? (3) How is the comparison between crash rates for the Self-Driving Car and national crash rates affected by the percentage of unreported crashes and severity level? (4) How do crash rates vary based on street type and speed limit? (5) What are the factors contributing to unreported crashes?
- Record URL:
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Corporate Authors:
Virginia Tech Transportation Institute
Blacksburg, VA United StatesGoogle Incorporated
1600 Amphitheatre Parkway
Mountain View, CA United States 94043 -
Authors:
- Blanco, Myra
- Atwood, Jon
- Russell, Sheldon
- Trimble, Tammy
- McClafferty, Julie
- Perez, Miguel
- Publication Date: 2016-1
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Appendices; Figures; References; Tables;
- Pagination: 88p
Subject/Index Terms
- TRT Terms: Alternatives analysis; Automatic data collection systems; Crash rates; Crash reports; Crash severity; Data quality; Highway safety; Intelligent vehicles; Speed limits
- Geographic Terms: United States
- Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01593724
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 16 2016 9:35AM