Jon Hankey

Design of the In-Vehicle Driving Behavior and Crash Risk Study: In Support of the SHRP 2 Naturalistic Driving Study

This report describes the study design for the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS). Using a sophisticated recording package installed in vehicles, it will collect information on the day-to-day driving of about 3,100 volunteer drivers for up to 2 years. Participants will be recruited in six sites throughout the United States. In this report, potential users of the SHRP 2 NDS data or its findings will find information about the participant recruitment plan, informed consent and data protection procedures, driver assessment tests, the capabilities of the data acquisition system (DAS), quality control, and project management.

Naturalistic Driving Study: Descriptive Comparison of the Study Sample with National Data

This report provides a descriptive comparison of data from the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS) sample and national data. The primary objective of the SHRP 2 NDS is to support analyses relating crash risk to driver, vehicle, roadway, and environmental characteristics. Since age is one of the most important driver characteristics, this objective is best supported by adequate sample sizes across all age groups. The national population of drivers has the greatest number of drivers in the middle age groups and progressively fewer in the younger and older ages. In contrast, the NDS oversampled younger and older drivers. In addition, the NDS oversampled newer-model-year vehicles because these vehicles provided useful data through their vehicle networks. It is important for users of the NDS data to have information on the relationship of the NDS sample to the national population. In general, many statistics taken directly from the NDS sample will not be nationally representative unless they are adjusted to account for relevant characteristics of the NDS sample.

Naturalistic Driving Study: Alcohol Sensor Performance

This report analyzes the performance of a passive alcohol sensor included in the head unit of the data acquisition system used in the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS). Driver impairment is a critical issue in traffic safety, and the ability to identify alcohol-impaired drivers would be valuable for users of the NDS data. The sensor responds to the presence of alcohol in the cabin air. A positive sensor reading can come from many sources: alcohol from the breath of a driver or other occupant, an open container of an alcoholic beverage, aftershave lotion or perfume, windshield wiper fluid, and even some fast food. On the other hand, open windows may dissipate alcohol from an impaired driver’s breath before it reaches the sensor. Thus, the sensor can produce a positive reading when the driver is sober and can produce a negative reading for an alcohol-positive driver. The objective of this report is to evaluate the sensor performance under several scenarios with known driver alcohol levels and to investigate the feasibility of developing an algorithm to identify potentially alcohol-impaired drivers based on the sensor output.

Improving Driver Safety through Naturalistic Data Collection and Analysis Methods

The design of a safe transportation system requires numerous design decisions that should be based on data acquired by rigorous scientific method. Naturalistic data collection and analysis methods are a relatively new addition to the engineers toolbox. The naturalistic method is based on unobtrusively monitoring driver and vehicle performance under normal, everyday, driving conditions; generally for extended collection periods. The method generates a wealth of data that is particularly well-suited for identifying the underlying causes of safety deficiencies. Furthermore, the method also provides robust data for the design and evaluation of safety enhancement systems through field studies. Recently the instrumentation required to do this type of study has become much more cost effective allowing larger numbers of vehicles to be instrumented at a fraction of the cost. This paper will first provide an overview of the naturalistic method including comparisons to other available methods. The focus of the paper then shifts to review the evolution of the data acquisition systems (DAS) and methods that have enabled naturalistic data collection. The goal is to provide readers with an understanding of how technology and unique partnerships has allowed the naturalistic data collection method to mature.