Details:

Creators:
Singh, Dharamveer ; Zaman, Musharraf M. ; White, Luther
Singh, Dharamveer ; Zaman, Musharraf M. ; White, Luther Less -
Corporate Creators:
University of Oklahoma
Corporate Contributors:
Oklahoma. Dept. of Transportation. Planning & Research Division
Subject/TRT Terms:
[+]
Mathematical Models Neural Networks (Computer Science)--Oklahoma Rural Highways Speed And Delay Studies Speed Limits Speed Limits--Mathematical Models Speed Limits--Oklahoma Traffic Regulations Traffic Safety Traffic Speed
Publication/ Report Number:
FHWA-OK-11-07
Resource Type:
Tech Report
Geographical Coverage:
Oklahoma
Edition:
Final report; Oct. 2008-Dec. 2010.
Corporate Publisher:
Oklahoma. Dept of Transportation
Abstract:
Traffic operation on two-lane rural highways and setting posted speed limits are some of the difficult tasks faced by the

Oklahoma Department of Transportation (ODOT) and other transportation agencies. The present study was undertaken to

develop artificial neural network (ANN) models to predict 85th percentile speed (V85) of two-lane rural highways in Oklahoma.

Several input parameters, namely, roadway characteristics, traffic conditions, and accident experience were considered in

developing the ANN models. Physical characteristics of road include, surface width (SW), shoulder type (ST), and shoulder

width (SHW). Traffic parameters cover average daily traffic (ADT), posted speed (PS), and V85. Pavement condition includes

skid number (SN), and international roughness index (IRI). The location collision rate, statewide collision rate (overall, fatal, and

injury), and percentage unsafe speed drivers (USD) were covered in the accident data.

Data from a total of 241 two-lane rural highway sites were collected and used in developing the ANN models. The

following four different ANN models were developed: Model 1 includes Posted Speed but does not include Accident Data; Model

2 includes neither Posted Speed nor Accident Data; Model 3 includes both Posted Speed and Accident Data; and Model 4 does

not include Posted Speed but includes Accident Data. Model 1 included physical characteristics of road, and traffic parameters

including PS, while Model 2 covered all the parameters included in Model 1 except PS. Similarly, Model 3 considered accident

data with all the parameters included in Model 1. Model 4 used all the parameters included in Model 3 excluding PS. The

developed models provided an overall accuracy of more than 90%. For example, Model 1 and Model 2 developed without

accident data gave an overall accuracy of 97%, and 91.5%, respectively. Similarly, Model 3 and Model 4 developed using

accident data resulted in an overall accuracy of 97.5%, and 94.1%, respectively. It was found that inclusion of accident data

improves the performance of the model only marginally.

The present study was pursued with the goal that ANN models for V85 would provide a cost effective alternative for

estimating site-specific V85 of two-lane rural highways in Oklahoma. Also, the developed models are expected to be useful for

prediction of V85 when roadway characteristics and/or traffic operational factors change.


Format:
PDF
Funding:
ODOT SPR Item Number 2211
Collection(s):
US Transportation Collection
Main Document Checksum:
[+]
urn:sha256:a13c69a8c838a27fb708e70fa6d3056b7a7171d15411ef418b6011e520a021e6
Download URL:
https://rosap.ntl.bts.gov/view/dot/23203/dot_23203_DS1.pdf
File Type:

Supporting Files

• No Additional Files

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