Jeffrey W Muttart

Driving Without a Clue: Evaluation of Driver Simulator Performance During Hands-Free Cell Phone Operation in a Work Zone

Crashes continue to be a problem in work zones. Analyses have indicated that rear-end and sideswipe crashes are the most frequent. Investigators have hypothesized that distractions are often the cause of both types of crashes. These distractions will only increase as more drivers attend to other tasks, such as cell phone conversations. To address this issue, virtual worlds that reflect various work zone geometries were developed for an advanced driving simulator. The worlds contained 32 virtual work zones; 38 drivers navigated through these worlds. On one portion of a trip, drivers were asked to respond to a series of short sentences that mimicked a hands-free cell phone conversation. A lead vehicle ahead of the participant driver braked occasionally in the work zone activity area. Braking scenarios involved either the lead vehicle stopping after an advanced clue that traffic ahead would stop or the lead vehicle stopping for no apparent reason, most often after passing a roadside obstacle (potential distraction). Drivers not engaged in a cell phone task were able to reduce their speed earlier in response to a slowing lead vehicle than were drivers engaged in the cell phone task. The drivers not engaged in a cell phone task were also less likely to brake hard and more likely to make a mirror glance when changing lanes. Finally, they scanned almost twice as far to the left and right. Results strongly suggest that cell phone use reduces driver awareness and may increase the likelihood of a crash in work zone activity areas.

Backing collisions: a study of drivers' eye and backing behaviour using combined rear-view camera and sensor systems

Context Backing crash injures can be severe; approximately 200 of the 2,500 reported injuries of this type per year to children under the age of 15 years result in death. Technology for assisting drivers when backing has limited success in preventing backing crashes. Objectives Two questions are addressed: Why is the reduction in backing crashes moderate when rear-view cameras are deployed? Could rear-view cameras augment sensor systems? Design 46 drivers (36 experimental, 10 control) completed 16 parking trials over 2  days (eight trials per day). Experimental participants were provided with a sensor camera system, controls were not. Three crash scenarios were introduced. Setting Parking facility at UMass Amherst, USA. Subjects 46 drivers (33 men, 13 women) average age 29 years, who were Massachusetts residents licensed within the USA for an average of 9.3  years. Interventions Vehicles equipped with a rear-view camera and sensor system-based parking aid. Main Outcome Measures Subjects eye fixations while driving and researchers observation of collision with objects during backing. Results Only 20% of drivers looked at the rear-view camera before backing, and 88% of those did not crash. Of those who did not look at the rear-view camera before backing, 46% looked after the sensor warned the driver. Conclusions This study indicates that drivers not only attend to an audible warning, but will look at a rear-view camera if available. Evidence suggests that when used appropriately, rear-view cameras can mitigate the occurrence of backing crashes, particularly when paired with an appropriate sensor system.

Glancing and Stopping Behavior of Motorcyclists and Car Drivers at Intersections

For the past decade, motorcycle fatalities have risen while other motor vehicle fatalities have declined. Many motorcycle fatalities occurred within intersections after a driver failed to see a motorcyclist. However, little is known about the behavior of motorcyclists when they negotiate an intersection. A study was undertaken to compare the behavior at intersections of an experienced group of motorcyclists when they were operating a motorcycle with their behavior when they were driving a car. Each participant navigated a course through low-volume, open roads. Participants wore eye-tracking equipment to record eye-glance information, and the motorcycle and car were instrumented with an onboard accelerometer and Global Positioning System apparatus. Results showed that participants were more likely to make last glances toward the direction of the most threatening traffic before they made a turn when they were driving a car than when they were riding a motorcycle. In addition, motorcyclists were less likely to come to a complete stop at a stop sign than car drivers. These results suggested that motorcyclists were exposing themselves to unnecessary risk. Specifically, motorcyclists frequently failed to make proper glances and practice optimal riding techniques. The behavior of the motorcyclists was compared with the current Motorcycle Safety Foundation curriculum. The results suggested that threat-response and delayed-apex techniques should be added to the training curriculum.

Predicting Route Choices of Drivers Given Categorical and Numerical Information on Delays Ahead: Effects of Age, Experience, and Prior Knowledge

In recent years there has been a considerable increase in the systems used to provide real-time traffic information to motorists. Examples of such systems include dynamic message signs and 511 travel information systems. However, such systems can be used to reduce congestion—one of their primary purposes—only if one can predict the route choices of drivers as a function of the information displayed. This simulator study looks at the diversion pattern that occurs when delays are reported ahead on the main route and how these diversion patterns vary as a function of delay times (for numerical delay signs), message content (for categorical delay signs), use of 511, and drivers’ familiarity with the alternative route travel times across two different age groups. For numerical delay signs, the study shows that one can reliably predict the diversion frequencies at the different delays and across the different ages; then it is possible for traffic engineers to know ahead of time how likely it is for drivers to take an alternative route. For categorical delay signs, the findings indicate that drivers’ knowledge of the alternative route travel time affects the choices of older versus younger or middle-aged adults differently. When the times are not known, the two groups behave differently; when the times are known, the groups behave similarly. This finding suggests that traffic engineers should try where possible to present the alternative route travel times as well as the delays on the main route.

Influence of Taillight Brightness on the Ability to Recognize Closing Speed, Closing Distance, and Closing vs. Separating

Rear-end crashes contribute to a large percentage of fatal collisions in the United States. However, every rear-end collision cannot be classified as a single type of crash. Some crashes may be caused due to human error while some crashes may be attributed to a human inability to recognize closing speed well. Observers were shown two 4-second video clips of a commercial vehicle closing on a slow-moving vehicle on an unlit highway. The lead vehicle was depicted at distances of 91m (300 ft), 128m (420 ft) and 152m (500 ft). Closing speeds of 40 km/h (25 mph) and 105 km/h (65 mph) were depicted. The taillights on the lead vehicle were randomly shown as bright, or 80% dimmer which is typical of older taillights or aged retroreflective materials. Results showed that observers’ ability to recognize closing from separating worsened with increased distance, dimmer taillights and lower closing speeds. Observers perceived brighter taillights to be closer. Also, at greater distances, observers did not recognize closing speeds as well.

Panel Discussion – Factors related to perceiving the relative speed of leading vehicles in high-speed rear-end crashes

Forensic human factors practitioners are often engaged to offer expert opinions in cases involving rear-end collisions. Such collisions represent approximately 25% of all automobile crashes and have done so for many years. The sad fact is that people run into the backs of slow moving or stopped vehicles with a low, but persistent probability. According to the 100-car study, the probability is 1 in 1.84 million miles traveled (Americans drive a total of about 3 trillion miles per year). A number of researchers have examined the circumstantial and perceptual issues related to rear-end crashes in an effort to understand why drivers have such a difficult time perceiving the relative speed of leading vehicles. Results from these studies are often cited in expert reports and testimony. In particular, the “looming threshold” established in these studies is sometimes used to establish the expectation of braking or steering responses. However, when reconstruction data are used to calculate looming thresholds, the values are usually much higher than those obtained in controlled studies. It is unclear whether these data represent the same phenomenon. The purpose of this panel discussion is to examine the breadth of data related to rear-end crashes and offer insight into the discrepancy between reconstruction and experimental results.

Developing an Adaptive Warning System for Backing Crashes in Different Types of Backing Scenarios

Young children are overrepresented in run-over backing crashes. The research goal was to propose a backing warning system based upon drivers’ backing behavior that was sensitive to different backing scenarios. A backing collision avoidance model that is sensitive to different backing scenarios needs to consider how drivers accelerate and respond to unanticipated hazards while backing. To develop a backing warning system that supplements the abilities of a driver, the drivers response times and backing acceleration were recorded in a field experiment in two different backing scenarios (short backing, e.g., a parking lot, and long backing, e.g., a driveway). The results show that those backing a long distance reached greater peak velocities than those backing short distances. Drivers traveling at greater speeds require greater warning distances than are offered by current backing sensor systems. Additionally, driver brake reaction times and braking latency times were much longer when backing than is typical when responding to hazards and driving forward. From the findings, a backing warning algorithm is proposed that may be optimized for short and long backing scenarios based upon the brake reaction times, braking latencies, peak speeds, and acceleration behaviors of the short and long backers, respectively.