David M. Cades

Driver Distraction and Advanced Vehicle Assistive Systems (ADAS): Investigating Effects on Driver Behavior

The component technologies of Advanced Driver Assistive Systems (ADAS) are becoming increasingly automated, with systems capable of operating in concert in multiple driving environments. However, how these systems affect a driver’s ability to safely, efficiently, and comfortably operate a vehicle remains unclear. We investigated the effects of ADAS [specifically Lane Departure Warning (LDW)] on driving performance while participants performed a secondary task (mental math) designed to simulate cognitive effort while driving. The experiment was conducted on a closed-course test track in an instrumented vehicle. Results suggest that cognitive engagement influenced driver control of the vehicle. Effects of cognitive engagement in a secondary task were not mitigated by the presence of LDW. We discuss our results in the framework of a continued need for active input and control from the human operator in vehicles with assistive technologies.

Effects of Mobile Technology Use on Walking

Objective: The goal of this study was to evaluate the efficacy of combining cognitive and kinematic measurements to study the effects of mobile technology use on walking. Background: It has previously been shown that being distracted by a cell phone, or other mobile technology, can have a negative impact on activities such as crossing a street and may also alter gait patterns. While the negative effects of cell phone use on driving have been extensively studied, research into the distracted pedestrian is lacking. Method: Twelve adults walked down an office corridor without using a cell phone (BASELINE) and while performing a secondary cognitive task under two conditions. The secondary task involved answering simple multiplication problems through either text messaging (TEXT) or while talking on the phone (VOICE). Participants’ gait patterns were measured using a GAITRite gait pad LEGSys wearable wireless sensors. Results: In the TEXT condition, participants walked more slowly and had shorter strides. There was no significant difference between the VOICE and BASELINE condition. Participants answered more multiplication problems per trial in the VOICE condition as compared to the TEXT condition. Excluding typos, error rates for the multiplication problems were not significantly different between the TEXT and VOICE conditions. Conclusion: This study demonstrated that the effect of reading and responding to text messages on gait was able to be detected utilizing methods that do not require strictly sterile laboratory settings. This serves as a proof of concept for researchers to bring the study and evaluation of distracted walking into the naturalistic environments in which it actually occurs. Application: This proof of concept will serve as a roadmap towards moving the study of gait and distraction from simple observational studies in naturalistic environments to specific quantitative analysis of people performing real world tasks in real world settings.

Differing Perceptions of Advanced Driver Assistance Systems (ADAS)

The extent to which drivers’ attitudes toward the use of autonomous vehicle systems can be influenced by various driver factors (e.g., driver age, experience with the systems, etc.) has yet to be firmly established. To investigate driver perceptions and acceptance of advanced vehicle systems, the current research examined initial and repeated exposure to systems while driving under various commonly encountered on-road situations (e.g., emergency braking). Somewhat surprisingly, driver perceptions of safety when driving vehicles with assistive technologies diminished following repeated exposure to the technologies. However, when drivers were afforded more extensive experience, they reported a heightened appreciation of the systems—especially drivers who might benefit most from this assistance (e.g., distracted or older drivers).

Gaze behavior during curb approach: The effect of mobile device use while walking

Mobile device use is becoming increasingly prevalent during everyday activities. The simultaneous use of such technology while performing various activities may increase risk of human error and accidents, such as falls. In addition to effects on cognitive and attentional resources, mobile device use may influence visual behavior, thus affecting the user’s ability to perceive obstacles in the environment and respond appropriately. The purpose of this study was to examine the influence of texting on gaze behavior during the approach and negotiation of a simulated curb. Wireless eye-tracking was used to record gaze during locomotion, with and without concurrent texting. Semantic Gaze Mapping (SMI, Inc.) was used to co-register participants’ gaze to different areas of interest (AOIs). Texting resulted in significant reductions in gaze dwell time on the curb and the number of times the curb was fixated. These findings suggest that mobile device use may have a negative effect on navigation during locomotion by reducing visual attention to task-relevant areas along the future path of travel.

Eye Tracking Evaluation of Driver Visual Behavior with a Forward Collision Warning and Mitigation System

As Advanced Driver Assistance Systems (ADAS) technologies become more commonplace and monitor an increasing number of aspects of the visual environment for drivers, typical driver visual behavior is likely to shift accordingly. Research on drivers’ responses to vehicles equipped with different ADAS technologies is required to evaluate how these systems influence driver visual behavior. The current study analyzed eye tracking metrics collected as part of a larger test track evaluation of drivers’ responses to a simulated emergency lead vehicle braking event while driving a vehicle equipped with a forward collision warning and mitigation (FCWM) system. In the experiment, driver behavior was examined both with and without concurrent performance of a secondary arithmetic task conducted on a hands-free cell phone. We found that participants experienced a startle response (as indicated by pupil dilation) at the time of the emergency event, which indicates the event was an effectively surprising experimental manipulation. We also found that participants predominantly fixated the lead vehicle, although participants performing the secondary task fixated the lead vehicle less often. All participants fixated the head-up display (HUD) rarely and briefly. However, older drivers spent more time fixating the HUD than younger drivers.

Consumer perceptions, understanding, and expectations of Advanced Driver Assistance Systems (ADAS) and vehicle automation

Consumers are faced with an increasingly complex decision process as novel safety technologies become commonplace in new vehicles. Consumers’ knowledge of these systems is potentially limited given the recent introduction and constant evolution of ADAS. We examined consumers’ understanding and perceptions of ADAS and vehicle automation in a national survey. Our analysis focused on consumers’ understanding of how certain driving tasks that can be automated (e.g., steering, braking, navigation, etc.) maps onto proposed levels of vehicle automation. Additionally, we report what sources of information and methods of education consumers prefer to utilize when learning about new safety systems. These data can inform new driver training, public policy and transportation goals of how best to educate the motoring public about new vehicle technologies and the capabilities of next-generation automated vehicles as well as facilitate public acceptance of higher levels of vehicle automation.

Seeing is Believing: The Use of Data Visualization to Identify Trends for Cycling Safety

Big data sets can be cumbersome and difficult to understand. User-centered and interactive graphical displays help communicate messages from large and complex data as well as provide a new method to identify data trends outside of tabular or statistical analysis. Human factors researchers can utilize data visuals to not only develop but also answer questions that previously proved difficult through visual exploration. This approach is especially relevant to the field of surface transportation research where complex plots can incorporate both temporal and geospatial data in an easy-to-digest format. As a proof of concept, this paper demonstrates how bike-sharing and historical bicycle collision incidents can meaningfully merge to produce graphical displays that readily identify and communicate potential infrastructure problems for safety. Through the use of Bayesian modeling and geospatial mapping, our analysis identifies two primary trends worth further consideration and research to consider for cyclist safety in Chicago.