Linear Regression Crash Prediction Models: Issues and Proposed Solutions

Rakha, H.; Arafeh, M.; Abdel-Salam, A.G.; Guo, F.; Flintsch, A.M.; Virginia Tech Transportation Institute

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Linear Regression Crash Prediction Models: Issues and Proposed Solutions

2010-05-01
By Rakha, H. ; Arafeh, M. ; Abdel-Salam, A.G. ; ...

[PDF-472.13 KB]

English

Details You May Also Like

Details:

Creators:

Rakha, H. ; Arafeh, M. ; Abdel-Salam, A.G. ; Guo, F. ; Flintsch, A.M.

Rakha, H. ; Arafeh, M. ; Abdel-Salam, A.G. ; Guo, F. ; Flintsch, A.M. Less -
Corporate Creators:

Virginia Tech Transportation Institute
Subject/TRT Terms:

[+]

Accident Data Accident Risk Forecasting Accident Studies Highways Highway Safety Linear Regression Analysis Linear Regression Model Mathematical Prediction Negative Binomial Novice Data Aggregation Regression Analysis--Mathematical Models Research Hub Safety And Human Factors Traffic Accidents Traffic Safety Zero Inflated Negative Binomial General Linear Models
Publication/ Report Number:

VT-2008-02
Resource Type:

Tech Report
Geographical Coverage:

United States ; Virginia

United States ; Virginia Less -
TRIS Online Accession Number:

01164268
Edition:

Final report.
Corporate Publisher:

Virginia. Dept. of Transportation ; United States. Dept. of Transportation. Research and Innovative Technology Administration

Virginia. Dept. of Transportation ; United States. Dept. of Transportation. Research and Innovative Technology Administration Less -
NTL Classification:

NTL-SAFETY AND SECURITY-Accidents;NTL-SAFETY AND SECURITY-Highway Safety;
Abstract:

The paper develops a linear regression model approach that can be applied to crash data to predict vehicle crashes. The proposed approach involves novice data aggregation to satisfy linear regression assumptions; namely error structure normality and homoscedasticity. The proposed approach is tested and validated using data from 186 access road sections in the state of Virginia. The approach is demonstrated to produce crash predictions consistent with traditional negative binomial and zero inflated negative binomial general linear models. It should be noted however that further testing of the approach on other crash datasets is required to further validate the approach.
Format:

PDF
Funding:

DTRS99-G-003
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:ae669d338931837a94013b4c5c9d254445091d7d6013e4a543a4a59cb34b52a4
Download URL:

https://rosap.ntl.bts.gov/view/dot/25646/dot_25646_DS1.pdf
File Type:

No Additional Files

More +

Linear Regression Crash Prediction Models: Issues and Proposed Solutions

Details:

Supporting Files

You May Also Like