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In this study we collect and analyze data on how hands-free automated lane centering systems affect the controllability of a hazardous event during an operational situation by a human operator. Through these data and their analysis, we seek to answer the following questions: Is Level 2 and Level 3 automated driving inherently uncontrollable as a result of a steering failure? Or, is there some level of operator control of hazardous situations occurring during Level 2 and Level 3 automated driving that can reasonably be expected, given that these systems still rely on a driver as the primary fall back. The controllability focus group experiments were carried out using an instrumented MY15 Jeep® Cherokee with a prototype Level 2 automated driving system that was modified to simulate a hands-free steering system on a closed track with speeds up to 110kph. The vehicle was also fitted with supplemental safety measures to ensure experimenter control.

Vehicle headlamps and roadway lighting are the major sources of illumination at night. These sources affect contrast - defined as the luminance difference of an object from its background - which drives visibility at night. However, the combined effect of vehicle headlamps and intersection lighting on object contrast has not been reported previously. In this study, the interactive effects of vehicle headlamps and overhead lighting on object contrast were explored based on earlier work that examined drivers’ visibility under three intersection lighting designs (illuminated approach, illuminated box, and illuminated approach + box). The goals of this study were to: 1) quantify object luminance and contrast as a function of a vehicle’s headlamps and its distance to an intersection using the three lighting designs; and, 2) to assess whether contrast influences visual performance and perceived visibility in a highly dynamic intersection environment.

This study evaluated the effectiveness of alternative workload-based interventions intended to restore driver alertness following drowsy episodes. Unlike traditional drowsy driving studies, this experiment did not target sleep-deprived individuals, but rather studied normally rested drivers under the assumption that low-workload environments could trigger drowsy driving episodes. The study served as a proof of concept for varying the nature and onset of countermeasure interventions intended to disrupt the drowsiness cycle. Interventions to combat drowsiness attempted to target driver workload, either physical or cognitive, and included two primary treatment conditions: 1) physical workload to increase driver steering demands and 2) trivia-based interactive games to mentally challenge drivers. A benchmark comparison condition using music was also investigated to contrast the relative influence of workload-based interventions with passive listening to musical arrangements.

The rapid development of driver assistance systems, such as lane-departure warning (LDW) and lane-keeping support (LKS), along with widely publicized reports of automated vehicle testing, have created the expectation for an increasing amount of vehicle automation in the near future. As these systems are being phased in, the coexistence of automated vehicles and human-driven vehicles on roadways will be inevitable and necessary. In order to develop automated vehicles that integrate well with those that are operated in traditional ways, an appropriate understanding of human driver behavior in normal traffic situations would be beneficial. Unlike many research studies that have focused on collision-avoidance maneuvering, this paper analyzes the behavior of human drivers in response to cut-in vehicles moving at similar speeds. Both automated and human-driven vehicles are likely to encounter this scenario in daily highway driving.

This study evaluated the performance of heavy vehicle crash avoidance systems (CASs) by collecting naturalistic driving data from 150 truck tractors equipped with Meritor WABCO OnGuardTM or Bendix® Wingman® AdvancedTM products. These CASs provide drivers with audio-visual alerts of potential conflicts, and can apply automatic braking to mitigate or prevent a potential collision. Each truck tractor participated for up to one year between 2013 and 2015. Videos of the forward roadway and drivers’ faces were collected along with vehicle network data while drivers performed their normal duties on revenue-producing routes. The study evaluated the performance of CAS activations by classifying them into three categories based on whether a valid object was being tracked and whether drivers needed to react immediately.

This study presents a long-term examination of the effects of two types of perceptual-cognitive brain training programs on senior driver behavior and on-road driving performance. Seniors (70+) engaged in either a Toyota-designed in-vehicle training program based on implicit learning principles or a commercially available computer-based training program developed by Posit Science. Another group served as a no-contact control group; total enrollment was 55 participants. Participants completed a series of four experimental sessions: (1) baseline pre-training, (2) immediate post-training, (3) 6-9 months post-training, and (4) 12-16 months post-training. Experimental metrics taken at each session included measures of vehicle control and driver glance behavior on public roads.

2011 - 56th L. Ray Buckendale Lecture Driver distraction has become an important topic in society and the research community. A telltale sign of how driver distraction has impacted society is evidenced by the designation of the term "distracted driving" as Webster's New World® College Dictionary 2009 Word of the Year. Since the release of a key study directed at commercial vehicle drivers, there have been two U.S. Department of Transportation summits to address the topic, in addition to legislation banning texting-while-driving in commercial motor vehicles. Given that "driver distraction" is a construct without a consensus definition, many studies on driver distraction have focused on its fundamental and theoretical underpinning, which is a critical first step in understanding the phenomenon.

To help drivers monitor the road and to reduce blind spots, Camera/Video Imaging Systems (C/VISs) display live video from cameras mounted on the truck's exterior to drivers using displays inside the truck cabin. This study investigated drivers' performance with C/VISs in a real-world trucking operation. Twelve commercial drivers' performance with and without a C/VIS was continuously recorded while they each drove for four months. Half of the drivers used a commercially available C/VIS that had a side-view camera on each fender. The other drivers used an advanced C/VIS (A-C/VIS) that had side-view cameras, a rear-view camera, and night-vision capabilities. This paper presents the study's final results and expands on the preliminary results that were previously reported. Detailed analyses of drivers' involvement in Safety-Critical Events (SCEs), their lane change performance, and their opinions of the C/VISs are presented.

An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

Vehicle-to-vehicle (V2V) communication systems can enable a number of wireless-based vehicle features that can improve traffic safety, driver convenience, and roadway efficiency and facilitate many types of in-vehicle services. These systems have an extended communication range that can provide drivers with information about the position and movements of nearby V2Vequipped vehicles. Using this technology, these vehicles are able to communicate roadway events that are beyond the driver's view and provide advisory information that will aid drivers in avoiding collisions or congestion ahead. Given a typical communication range of 300 meters, drivers can potentially receive information well in advance of their arrival to a particular location. The timing and nature of presenting V2V information to the driver will vary depending on the nature and criticality of the scenario.

On-board Camera/Video Imaging Systems (C/VISs) for heavy vehicles display live images to the driver of selected areas to the sides, and in back of the truck's exterior using displays inside the truck cabin. They provide a countermeasure to blind-spot related crashes by allowing drivers to see objects not ordinarily visible by a typical mirror configuration, and to better judge the clearance between the trailer and an adjacent vehicle when changing lanes. The Virginia Tech Transportation Institute is currently investigating commercial motor vehicle (CMV) driver performance with C/VISs through a technology field demonstration sponsored by the National Highway Traffic Safety Administration (NHTSA) and the Federal Motor Carrier Safety Administration (FMCSA). Data collection, which consists of recording twelve CMV drivers performing their daily employment duties with and without a C/VIS for four months, is currently underway.

Camera/Video Imaging Systems (C/VISs) display video captured from cameras mounted on the truck's fenders and trailer to drivers using displays mounted inside the truck cabin. C/VISs provide a countermeasure to blind-spot related crashes by allowing drivers to see objects not ordinarily visible by a typical mirror configuration. They also support drivers in determining the clearance between the trailer and an adjacent vehicle when performing a lane change. The National Highway Traffic Safety Administration (NHTSA) and the Federal Motor Carrier Safety Association (FMCSA) have collaboratively funded research on the development of C/VISs that operate during the day, as well as enhancing C/VISs to operate at night and in inclement weather. This paper presents the work performed in developing a C/VIS capable of being used in an eight-month technology field demonstration (TFD), which will allow the measurement of driver behavior with the C/VIS in a revenue-producing environment.

Driver distraction, defined here as engaging in a secondary task or activity that is not central to the primary task of driving, has been shown to be a contributing factor for many crashes. The secondary tasks and other activities in which drivers choose to engage while driving is also known to be highly varied, including very complex activities(e.g., text messaging on a cellular device) to very simple activities (e.g., selecting a radio preset). Several important distinctions affect the relative risk of engaging in these tasks. Recent data from large-scale instrumented vehicle studies (i.e., “naturalistic” driving studies like the recently released “100 car study” (1)) have begun to provide data where the relative risk, in terms of crash and near crash involvement, can be directly assessed for differing secondary tasks. These data have provided some important insights into the features that create risk.

Assessing driver drowsiness and providing timely alerts is the basis for drowsy driver monitoring systems. Though technologies are available that claim to reliably provide this function, they tend to be single-metric systems that may not be sufficiently robust for real-world operation. To address this issue, a prototype system that integrated two drowsiness measures was developed. The prototype combined machine-vision-based drowsy driver monitoring technology and the analysis of driver/vehicle performance parameters with the goal of more reliably assessing driver drowsiness. The prototype concept, called PERCLOS+, used PERCLOS (a slow eye-closure measure) in combination with lane deviation (to assess driver performance). Based on preliminary on-road tests, the prototype was found to be more robust than a single-metric system.

The injury outcome of a front-front two-vehicle crash will be a function of crash-specific, vehicle-specific, and occupant-specific parameters. This paper focuses on a preliminary methodology that was used to evaluate the potential for benefits in making vehicle-specific changes to improve the compatibility of light vehicles across the fleet. In particular, the effect on injury rates of matching vehicle frontal stiffness was estimated. The front-front crash data for belted drivers in the lighter vehicles in the crash from ten years of NASS-CDS data were examined. The frontal stiffness of each vehicle was calculated using data taken during full frontal rigid barrier tests for the U.S. New Car Assessment Program (NCAP), and only crashes coded in the CDS as “no override” were considered.

In crashes between heavy trucks and light vehicles, most of the fatalities are the occupants of the light vehicle. A reduction in heavy truck stopping distance should lead to a reduction in the number of crashes, the severity of crashes, and consequently the numbers of fatalities and injuries. This study made use of the National Advanced Driving Simulator (NADS). NADS is a full immersion driving simulator used to study driver behavior as well as driver-vehicle reactions and responses. The vehicle dynamics model of the existing heavy truck on NADS had been modified with the creation of two additional brake models. The first was a modified S-cam (larger drums and shoes) and the second was an air-actuated disc brake system. A sample of 108 CDL-licensed drivers was split evenly among the simulations using each of the three braking systems. The drivers were presented with four different emergency stopping situations.

Approximately 28,000 crashes involving combination unit trucks occur each year when they are making lane changes, merges, or turns. One contributing factor in these crashes is inadequate visibility for truck drivers. Recent advances in video technology have heightened the prospect of improving commercial vehicle safety by improving drivers' vision around the truck. For such video systems to be implemented on heavy trucks, the systems/driver interface should be demonstrated as viable through research. This paper presents the Camera/Video Imaging Systems (C/VISs) developed at Virginia Tech Transportation Institute (VTTI), the methodology used to test them, and some results obtained.

This paper discusses radio usage habits observed during analysis of 700 hours of video sampled from the 100-Car Naturalistic Driving Study database. Analysts used large-scale printouts of each vehicle's radio faceplate and recorded interactions based on video analysis of hand movement and location (without the assistance of audio recordings). The duration and specific manipulations or adjustments were recorded for each interaction. The results summarize the length and type of interactions, most often-used controls, and total percentage of time drivers interacted with the radio.

This research compared driver detection performance with low-beam halogen headlamps supplemented by a General Motors production Night Vision system to low-beam halogen headlamps alone. This research was conducted with 18 participants between the ages of 40 and 70 years on a 3.2km (2-mile) section of closed road. Participants encountered seven scenarios, including crossing or standing pedestrians dressed in either white or black clothing. Additional scenarios included pedestrians in a curve and near an oncoming glare vehicle, as well a tire tread. Results indicated that the GM Night Vision system improved drivers' detection distances in nearly all pedestrian scenarios examined.

To address the issue of fatigued truck drivers, the U.S. Department of Transportation sponsored research to develop a Drowsy Driver Warning System. This system has been under development for several years and is at a point where it is ready for a Field Operational Test. The experimental plan calls for 102 drivers, each operating one of 34 instrumented heavy trucks for 16 weeks. Each vehicle is instrumented with video cameras and a variety of sensors to capture driver input/performance. This paper describes the method being used to conduct the study, including an overview of the data collection instrumentation.