Neural Networks to Estimate Crashes at Zonal Level for Transportation Planning
The focus of this paper is on development of crash estimation models at traffic analysis zone (TAZ) level as a function of land use characteristics. Crash data and land use data for 765 TAZs with a total of 9,799 crashes (includes 20 fatal crashes, 3,227 injury crashes and 6,552 property damage only crashes) in the City of Charlotte, Mecklenburg County, North Carolina were used in the development of statistical and neural network models. Negative Binomial models (with log-link) were developed as data was observed to be over-dispersed while the neural network models developed are based on a multilayered, feed-forward, back-propagation design for supervised learning. Demographic/socio-economic characteristics (population, the number of household units and employment), traffic indicators (trip productions and attractions), and, on-network characteristics (center-lane miles by speed limit) were observed to be correlated to land use characteristics, and, hence were not considered in the development of TAZ level crash estimation models. Models were developed to estimate the total number of crashes as well as crashes based on severity (total injury and property damage only crashes). The results from comparison of models for performance evaluation indicate that back propagation neural network models ensured significantly lower errors when compared to statistical models. The neural network approach can be particularly suitable for their better predictive capability, whereas the statistical models could be used for mathematical formulation or understanding the role of explanatory variables in estimating crashes. The developed methodology and results can be used to incorporate safety into long range transportation plans and land use decisions so as to minimize anticipated crashes in the future. The models developed using the methodology can also be used to examine the effect of changes in land use characteristics (new development or re-zoning) on safety.
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Supplemental Notes:
- Abstract used by permission of Association for European Transport.
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Corporate Authors:
Association for European Transport (AET)
1 Vernon Mews, Vernon Street, West Kensington
London W14 0RL, -
Authors:
- Duddu, Venkata R
- Pulugurtha, Srinivas S
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Conference:
- European Transport Conference 2012
- Location: Glasgow , Scotland
- Date: 2012-10-8 to 2012-10-10
- Publication Date: 2012
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 15p
- Monograph Title: European Transport Conference 2012
Subject/Index Terms
- TRT Terms: Crash severity; Fatalities; Land use; Neural networks; Traffic analysis zones; Traffic crashes
- Uncontrolled Terms: Property damage
- Geographic Terms: Charlotte (North Carolina)
- Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning; I81: Accident Statistics;
Filing Info
- Accession Number: 01542173
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 29 2014 11:26AM