BACKGROUND 

Driver behavior and characteristics are influential contributing factors to traffic crashes, but current safety analysis tools primarily incorporate infrastructure-related factors affecting crashes. The lack of behavior and characteristic information can create a problem when 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 AASHTO 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. However, these characteristics are provided at a very high level. 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 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 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 AASHTO HSM and other safety tools and guidelines.

OBJECTIVE

The objective of this research is to continue and complete the work begun under NCHRP Project 22-47 to develop a methodology to incorporate driver characteristics and behavior into safety prediction methods to estimate the expected crash frequency and severity related to infrastructure features for use in planning, design, and operational decisions.

Status: Work has been initiated. Phase I Tech Memo is expected in August 2024.