Project

Understanding and prioritizing crash contributing factors - Analyzing naturalistic driving data and self-reported crash data for car safety development

Real world data on driver behavior in normal driving and critical situations are essential for car safety development. Data collection and analysis methods that provide insight into the prevalence of crash contributing factors (e.g., drowsiness

Driving context influences drivers' decision to engage in visual–manual phone tasks: Evidence from a naturalistic driving study

Introduction

Visual–manual (VM) phone tasks (i.e., texting, dialing, reading) are associated with an increased crash/near-crash risk. This study investigated how the driving context influences drivers' decisions to engage in VM phone tasks in

Driving context and visual-manual phone tasks influence glance behavior in naturalistic driving

Naturalistic driving studies show that drivers engaged in complex visual-manual tasks face an increased risk of a crash or near-crash. Tasks that require many glances and a high proportion of long glances away from the road are of special concern for

What can the drivers' own description from combined sources provide in an analysis of driver distraction and low vigilance in accident situations?

Abstract Accident data play an important role in vehicle safety development. Accident data sources are generally limited in terms of how much information is provided on driver states and behaviour prior to an accident. However, the precise limitations vary

Nonresponse analysis and adjustment in a mail survey on car accidents

Statistical accident data plays an important role for traffic safety development involving the road system, vehicle design, and driver education. Vehicle manufacturers use data from accident mail surveys as an integral part of the product development

Real world data on driver behaviour in accidents and incidents: Evaluating data collection and analysis methods for car safety development

Real world data is important for safety development within the road transportation system. For car safety development in particular, methods to collect and analyse real world data on driver behaviour from normal driving, incidents and accidents are needed

Dialling, texting, and reading in real world driving: When do drivers choose to use mobile phones?

Mobile phone use is the most debated and studied form of driver distraction. Naturalistic driving studies have shown that the risk of being involved in a near-crash or crash increases during manual and visual interaction with a mobile phone (e.g., when

Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM)

To develop relevant road safety countermeasures, it is necessary to first obtain an in-depth understanding of how and why safety-critical situations such as incidents, near-crashes, and crashes occur. Video-recordings from naturalistic driving studies