Data Mining to Improve Planning for Pedestrian and Bicyclist Safety
Between 2009 and 2016, the number of pedestrian and bicyclist fatalities saw a marked trend upward. Taken together, the overall percentage of pedestrian and bicycle crashes now accounts for 18% of total roadway fatalities, up from 13% only a decade ago. Technological advancements in transportation have created unique opportunities to explore and investigate new sources of data for the purpose of improving safety planning. This study investigated data from multiple sources, including automated pedestrian and bicycle counters, video cameras, crash databases, and GPS/mobile applications, to inform bicycle and pedestrian safety improvements. Data mining techniques, a new sampling strategy, and automated video processing methods were adopted to demonstrate a holistic approach that can be applied to identify facilities with highest need of improvement. To estimate pedestrian and bicyclist counts at intersections, exposure models were developed incorporating explanatory variables from a broad spectrum of data sources. Intersection-related crashes and estimated exposure were used to quantify risk, enabling identification of high-risk signalized intersections for walking and bicycling. The modeling framework and data sources used in this study will be beneficial in conducting future analyses for other facility types, such as roadway segments, and also at more aggregate levels, such as traffic analysis zones.
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting datasets available at: https://doi.org/10.15787/VTT1/IUTNDS; https://rosap.ntl.bts.gov/view/dot/65456
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Corporate Authors:
Safety through Disruption University Transportation Center (Safe-D)
Virginia Tech Transportation Institute
Blacksburg, VA United States 24060San Diego State University
San Diego, CA United StatesTexas A&M Transportation Institute
Texas A&M University System
3135 TAMU
College Station, TX United States 77843-3135Virginia Tech Transportation Institute
Blacksburg, Virginia United StatesOffice of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Jahangiri, Arash
- 0000-0002-8825-961X
- Hasani, Mahdie
- 0000-0003-3787-0547
- Sener, Ipek Nese
- 0000-0001-5493-8756
- Munira, Sirajum
- 0000-0002-4953-2628
- Owens, Justin
- 0000-0001-5872-3939
- Appleyard, Bruce
- 0000-0003-2105-8079
- Ryan, Sherry
- 0000-0002-9839-9958
- Turner, Shawn M
- 0000-0002-5717-7742
- Machiani, Sahar Ghanipoor
- 0000-0002-7314-2689
- Publication Date: 2019-11
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Appendices; Figures; References; Tables;
- Pagination: 60p
Subject/Index Terms
- TRT Terms: Bicycling; Crash data; Cyclists; Data mining; Global Positioning System; High risk locations; Mobile applications; Pedestrian safety; Signalized intersections; Traffic safety; Video cameras; Walking
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 01725717
- Record Type: Publication
- Report/Paper Numbers: 01-003
- Contract Numbers: 69A3551747115/Project 01-003
- Files: UTC, NTL, TRIS, ATRI, USDOT
- Created Date: Dec 20 2019 4:23PM