A driving simulator study was conducted to assess whether real-time feedback on a driver's state can influence the driver's interaction with in-vehicle information systems (IVIS). Previous studies have shown that IVIS tasks can undermine driver safety by increasing driver distraction. Thus, mitigating driver distraction using a feedback mechanism appears promising. This study was designed to te...

The intelligent vehicle community has devoted considerable efforts to model driver behavior, and in particular to detect and overcome driver distraction in an effort to reduce accidents caused by driver negligence. However, as the domain increasingly shifts towards autonomous and semi-autonomous solutions, the driver is no longer integral to the decision making process, indicating a need to ref...

Prior research has documented the manner in which a variety of driving performance measures are impacted by concurrent cell-phone use as well as the influence of age and gender of the driver. This current study examined the extent to which different driver groups are aware of their associated performance decrements. Subjects' confidence in dealing with distractors while driving and their rating...

Driver distraction can arise from sources internal as well as external to the driver. In this paper we describe a study (in progress) designed to examine the influence of internal distraction, created by cognitive tasks, on drivers’ visual behavior and vehicle control. Sixteen drivers will drive a city route while carrying out tasks of varying cognitive complexity. The tasks and their responses...

Human errors due to distraction are a direct cause or a contributing factor in a majority of vehicle crashes and impacts. Visual-manual secondary tasks are critical according to naturalistic driving studies. NHTSA’s recently proposed Design Guidelines with purpose to limit potential driver distraction from secondary, non-drivingrelated, visual-manual tasks performed on integrated electronic dev...

Our work on modeling driver behavior in a cognitive architecture has benefited greatly from two types of integration: composition of independently developed theories and models into the framework of a cognitive architecture, and generalization of common elements of theories and models into higher-level constructs within the architecture. This chapter highlights three ways in which integration b...

Human Machine Interfaces (HMIs) are the communication devices between invehicle applications and the driver. Frequently, independent HMIs are used for different applications which may cause information overload situations at the driver. Hence, a common HMI design that determines the application interface with an HMI Manager that provides rules for prioritizing information from different applica...

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponso...

There is little agreement in the scientific literature about what the terms "driver distraction" and "driver inattention" mean, and what the relationship is between them. In 2011, Regan, Hallett and Gordon proposed a taxonomy of driver inattention in which driver distraction is conceptualized as just one of several processes that give rise to driver inattention. Since publication of that paper,...

This chapter discusses our research efforts in tracking driver distraction using multimodal features. A car equipped with various sensors is used to collect a database with real driving conditions. During the recording, the drivers were asked to perform common secondary tasks such as operating a cell phone, talking to another passenger and changing the radio stations. We analyzed the difference...