Automated Estimation of Winter Driving Conditions

Baldwin, Michael E; Burris, Kevin D; Elmore, Kimberly L

doi:10.5703/1288284316867

i

Automated Estimation of Winter Driving Conditions

2018-10-01
By Baldwin, Michael E ; Burris, Kevin D ; Elmore, Kimberly L

File Language:

English

Details

Creators:

Baldwin, Michael E ; Burris, Kevin D ; Elmore, Kimberly L
Corporate Creators:

Purdue University. Joint Transportation Research Program ; University of Oklahoma. Cooperative Institute of Mesoscale Meteorological Studies
Corporate Contributors:

Indiana Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
Subject/TRT Terms:
Publication/ Report Number:

FHWA/IN/JTRP-2018/22
DOI:

https://doi.org/10.5703/1288284316867
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

Purdue University. Joint Transportation Research Program
Abstract:

There is great potential for improvements in traveler safety and satisfaction as new sources of information are incorporated into advanced analytics and prediction systems. It is critical for transportation agencies to be able to monitor weather conditions in real-time as well as over the long-term for purposes of maintenance, planning, and performance evaluation. Travelers also use this information to plan their routes, make decisions on timing, and improve their awareness of potential hazards. A machine learning model was developed in this project to automatically estimate winter driving conditions in real-time using weather information as input. This system can provide rapid updates of changing conditions and help reduce the effort required to report driving conditions during intense winter storms. The system performed well in an experimental evaluation during the 2017-18 season. Seasonal analyses of winter precipitation that incorporated crowd-sourced observations were also generated and displayed significant differences from previous research.
Format:

PDF
Funding:

SPR-3821
Download URL:

https://rosap.ntl.bts.gov/view/dot/61935/dot_61935_DS1.pdf
File Type:

[PDF - 1.65 MB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:0152b1d89c8f0838b38b73710c127dca9aadc2317f449cea3adbbcb0bb7f06f4

File Language:

English

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