1. Report No.
FHWA-RD-97-106
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2. Government Accession No.
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3. Recipient's Catalog No.
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4. Title and Subtitle STATISTICAL MODELS OF ACCIDENTS ON INTERCHANGE RAMPS
AND SPEED-CHANGE LANES
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5. Report Date |
6. Performing Organization
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7. Author(s)
K.M. Bauer and D.W. Harwood
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8. Performing Organization Report No.
3195-02
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9. Performing Organization Name and Address
Midwest Research Institute
425 Volker Boulevard
Kansas City, Missouri 64110-2299
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10. Work Unit No. (TRAIS)
3A5A
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11. Contract or Grant No.
DTFH61-92-C-00031
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12. Sponsoring Agency Name and Address
Office of Safety and Traffic Operations Research and
Development
Federal Highway Administration
6300 Georgetown Pike
McLean, Virginia 22101-2296
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13. Type of Report and Period Covered
Final Technical Report
May 1994 - July 1997
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14. Sponsoring Agency Code
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15. Supplementary Notes
Contracting Officer's Technical Representative (COTR):
Joe Bared, HSR-20
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16. Abstract
The objective of this research was to develop statistical
models for defining the relationship between traffic accidents and
highway geometric design elements and traffic volumes for interchange
ramps and speed-change lanes. The data base used to develop the models
consisted of data for interchange ramps and speed-change lanes in
the State of Washington and was obtained from the FHWA Highway Safety
Information System. Additional geometric design features were obtained
from the review of interchange diagrams. Data on other geometric design
features, such as the ramp grades and horizontal curvature, were collected
for a sample of ramps from aerial photographs and other existing highway
agency files.
The statistical modeling approaches used in the research
included Poisson and negative binomial regression. Regression models
to determine relationships between accidents and the geometric design
and traffic volume characteristics of ramps were difficult to develop
because the observed accident frequencies for most ramps and speed-change
lanes are very low. The regression models developed, based on the
negative binomial distribution, explained between 10 and 42 percent
of the variability in the accident data, with the negative binomial
distribution providing a poor to moderate fit to the data. However,
most of that variability was explained by ramp Annual Average Daily
Traffic (AADT). Other variables found to be significant in some models
included mainline freeway AADT, area type (rural/urban), ramp type
(on/off), ramp configuration, and combined length of ramp and speed-change
lane.
The best models obtained for predicting accident frequencies
were those obtained when modeling the combined accident frequency
for an entire ramp, together with its adjacent speed-change lanes.
These models provided a better fit than separate models for ramps
and speed-change lanes. Models developed to predict total accidents
generally performed slightly better than did models to predict fatal
and injury accidents.
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17. Key Words
Accident Modeling |
Poisson Regression |
Traffic Accidents |
Negative Binomial |
Geometric Design |
Regression |
Interchange Ramps |
Speed-Change Lanes |
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18. Distribution Statement
No restrictions. This document is available to the public
through the National Technical Information Service, Springfield, Virginia
22161.
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19. Security Classif. (of this report)
Unclassified
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20. Security Classif. (of this page)
Unclassified
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21. No. of Pages
163
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22. Price
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