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The National Academies

NCHRP 22-47 [Active]

Incorporating Driver Behavior and Characteristics into Safety Prediction Methods

  Project Data
Funds: $600,000
Staff Responsibility: Richard Retting
Research Agency: University of North Carolina at Chapel Hill
Principal Investigator: Raghavan Srinivasan
Effective Date: 9/1/2020
Completion Date: 3/1/2023

BACKGROUND

 

Driver behavior and characteristics represent some of the most influential contributing factors to traffic crashes.  However, current safety analysis tools primarily incorporate infrastructure-related factors affecting crashes.  This creates a problem for those considering safety applications since some of the most important factors are not included.  This could lead to safety solutions that may not work as well as intended.  In the Highway Safety Manual (HSM), the measures of driver characteristics are divided into several categories such as attention and information processing, vision, perception-reaction time, and speed choice.  Police officers usually report driver characteristics such as gender, age, speeding, blood alcohol content, seat belt use, and distracted driving.  While several studies have evaluated the impact of these factors on crash severity, there is a need to incorporate these factors in widely implemented crash prediction methods to achieve a better picture of the true potential effects on crash severity and frequency for decisions in planning, design, and operations. 


Research is needed to develop a methodology to incorporate a wide variety of factors related to driver behavior and characteristics into crash prediction methods to allow for a more comprehensive assessment of existing and expected safety performance, for use in design and operational decision-making, and incorporation into the HSM and other safety tools and guidelines.

 

OBJECTIVE

 

The objective of this research is to develop a methodology to incorporate driver characteristics and behavior into safety prediction methods that can be used to estimate the expected crash frequency and severity related to infrastructure features for use in planning, design, and operational decisions.  The predictive method(s) shall be suitable for inclusion as part of the HSM as a tool to quantify safety performance across modes.

 

Note: During the methodology development process, the contractor shall plan and provide for pilot testing by multiple agencies as approved by NCHRP.

 

RESEARCH STATUS:

Research for this project is ongoing.

 

 

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