Mary F. Lesch

The distraction effects of phone use during a crucial driving maneuver

Forty-two licensed drivers were tested in an experiment that required them to respond to an in-vehicle phone at the same time that they were faced with making a crucial stopping decision. Using test track facilities, we also examined the influence of driver gender and driver age on these dual-task response capacities. Each driver was given task practice and then performed a first block of 24 trials, where one trial represented one circuit of the test track. Half of the trials were control conditions in which neither the stop-light was activated nor was the in-vehicle phone triggered. Four trials required only stop-light response and a further four, phone response only. The remaining four trials required the driver to complete each task simultaneously. The order of presentation of specific trials was randomized and the whole sequence was repeated in a second block giving 48 trials per driver. In-vehicle phone response also contained an embedded memory task that was evaluated at the end of each trial circuit. Results confirmed our previous observation that in the dual-task condition there was a slower response to the light change. To compensate for this slowed response, drivers subsequently brake more intensely. Most importantly, we recorded a critical 15% increase in non-response to the stop-light in the presence of the phone distraction task which equates with increased stop-light violations on the open road. These response patterns varied by driver age and driver gender. In particular, age had a large effect on task components that required speed of response to multiple, simultaneous demands. Since driving represents a highly complex and interactive environment, it is not possible to specify a simplistic relationship between these distraction effects and outcome crash patterns. However, we can conclude that such in-vehicle technologies erode performance safety margin and distract drivers from their critical primary task of vehicle control. As such it can be anticipated that a causal relation exists to collision events. This is a crucial concern for all in-vehicle device designers and for the many safety researchers and professionals seeking to reduce the adverse impacts of vehicle collisions.

Driver-initiated distractions: examining strategic adaptation for in-vehicle task initiation.

Today, drivers are faced with many in-vehicle activities that are potentially distracting. In many cases, they are not passive recipients of these tasks; rather, drivers decide whether or not (or how) to perform them. In this study, we examined whether drivers, given knowledge of the upcoming road demands, would strategically delay performing in-vehicle activities until demands were reduced. Twenty drivers drove an instrumented van around a closed track that was divided into sections of varying demands and difficulty. Drivers were asked to perform one of four in-vehicle tasks (e.g., phone conversation; read a text message; find an address; pick up an object on the floor); however, they were free to decide when to initiate these tasks, provided they finish them before a given deadline. Although drivers were fully aware of the relative demands of the road, they did not tend to strategically postpone tasks--a finding that was consistent across the different tasks (p >.05). Rather, drivers tended to initiate tasks regardless of the current driving conditions. This strategy frequently led to driving errors. Given the control that drivers have over many in-vehicle distractions, interventions that focus on strategic decisions and planning may have merit.

Calibration of skill and judgment in driving: Development of a conceptual framework and the implications for road safety

Humans often make inflated or erroneous estimates of their own ability or performance. Such errors in calibration can be due to incomplete processing, neglect of available information or due to improper weighing or integration of the information and can impact our decision-making, risk tolerance, and behaviors. In the driving context, these outcomes can have important implications for safety. The current paper discusses the notion of calibration in the context of self-appraisals and self-competence as well as in models of self-regulation in driving. We further develop a conceptual framework for calibration in the driving context borrowing from earlier models of momentary demand regulation, information processing, and lens models for information selection and utilization. Finally, using the model we describe the implications for calibration (or, more specifically, errors in calibration) for our understanding of driver distraction, in-vehicle automation and autonomous vehicles, and the training of novice and inexperienced drivers.

On-Board Safety Monitoring Systems for Driving: Review, Knowledge Gaps, and Framework

INTRODUCTION Fatal highway incidents remain the leading type of fatal work-related event, carrying tremendous personal, social, and economic costs. While employers with a fixed worksite can observe and interact directly with workers in an effort to promote safety and reduce risk, employers with workers who operate a motor vehicle as part of their job have fewer options. New technologies such as on-board safety monitoring systems offer the potential to further improve safety. These technologies allow vehicle owners to collect safety-specific information related to a drivers on-the-road behavior and performance. While many such devices are being developed and implemented in both commercial fleets and private vehicles, the scientific examination of these devices has lagged by comparison. METHOD In the current paper, we: (a) describe the general features and functionality of current generations of on-board monitoring devices and how they might impact various driver behaviors; (b) review the current state of scientific knowledge specific to on-board devices; (c) discuss knowledge gaps and potential areas for future research, borrowing from the related domain of computer-based electronic performance monitoring (EPM); and (d) propose a framework that can be used to explore some of the human-system interactions pertaining to monitoring systems. IMPACT ON INDUSTRY Motor vehicle crashes can carry tremendous costs for employers, in terms of injury, disability, and loss of potentially productive work years. New technologies can offer tremendous benefits in terms of promoting safer on-the-road behaviors.

The Effect of Feedback on Attitudes Toward Cellular Phone Use While Driving: A Comparison Between Novice and Experienced Drivers

Objectives: To assess and compare the effectiveness of a simulation-based approach to change drivers’ attitudes toward cellular phone use while driving for younger novice and older experienced drivers. Methods: Thirty young novice drivers were tested on a driving simulator in this study. Their performance in dealing with driving tasks was measured for a single task and dual tasks (driving while using a cellular phone) and compared to 30 older experienced drivers tested previously in another study. Half of the younger drivers received video-based feedback regarding their performance in the two conditions, with an emphasis on the contribution of dual-tasking to degraded performance. The other half did not receive any performance feedback. Drivers’ perceptions and attitudes toward cellular phone use while driving were investigated by a questionnaire before, immediately after, and again one month following the simulation-based testing for both groups of drivers (feedback; no feedback) Results: All drivers (including the novice and experienced) reported willingness to engage in driving and talking on a cellular phone in some situations. The simulated driving test showed that a secondary cellular phone task significantly degraded driving performance for both the novice and the experienced drivers. The feedback treatment group (both the novice and the experienced) showed significant attitude change toward cellular phone use while driving (toward being less favorable), whereas the control group had no attitude change. At the one-month follow-up, the benefit of feedback was sustained more so in the experienced driver group than the novice driver group, although both groups still benefited relative to the control conditions. Conclusions: Simulation-based feedback training is promising for short-term education in novice drivers but may be more effective in the long-term for drivers with higher levels of experience. Drivers with more experience appear to have a greater, more sustained benefit from the training than novices. Additional research is needed to better tailor this education method toward novice drivers. Impact: Simulation-based participative education approach through feedback needs to be better tailored toward novice drivers.

Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems

Advanced Driver Assistance Systems (ADAS) are intended to enhance driver performance and improve transportation safety. The potential benefits of these technologies, such as reduction in number of crashes, enhancing driver comfort or convenience, decreasing environmental impact, etc., have been acknowledged by transportation safety researchers and federal transportation agencies. Although these systems afford safety advantages, they may also challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the implementation of these systems into the transportation system. Recognizing the need for research into the factors affecting driver acceptance, this study assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT) for modelling driver acceptance in terms of Behavioral Intention to use an ADAS. Each of these models propose a set of factors that influence acceptance of a technology. Data collection was done using two approaches: a driving simulator approach and an online survey approach. In both approaches, participants interacted with either a fatigue monitoring system or an adaptive cruise control system combined with a lane-keeping system. Based on their experience, participants responded to several survey questions to indicate their attitude toward using the ADAS and their perception of its usefulness, usability, etc. A sample of 430 surveys were collected for this study. Results found that all the models (TAM, TPB, and UTAUT) can explain driver acceptance with their proposed sets of factors, each explaining 71% or more of the variability in Behavioral Intention. Among the models, TAM was found to perform the best in modelling driver acceptance followed by TPB. The findings of this study confirm that these models can be applied to ADAS technologies and that they provide a basis for understanding driver acceptance.

Safety Warnings for Automation

Automated systems can provide tremendous benefits to users; however, there are also potential hazards that users must be aware of to safely operate and interact with them. To address this need, safety warnings are often provided to operators and others who might be placed at risk by the system. This chapter discusses some of the roles safety warnings can play in automated systems, from both the traditional perspective of warnings as a form of hazard control and the perspective of warnings as a form of automation. During this discussion, the chapter addresses some of the types of warnings that might be used, along with issues and challenges related to warning effectiveness. Design recommendations and guidelines are also presented.

Drivers’ trust in an autonomous system Exploring a covert video-based measure of trust

Drivers’ trust in automation will likely determine the extent that autonomous and semi-autonomous vehicles are adopted, and once adopted, used properly. Unfortunately, previous studies have typically utilized overt subjective measures in determining an individual’s level of trust in automation. The current study aims to evaluate a covert behavioral measure of trust based on drivers’ body (head, hand, and foot) movements as they experience a simulated autonomous system. Videos of drivers interacting with an autonomous driving system in a driving simulator were coded. Body movement counts and average durations were derived from this coding and these data were compared across quartile rankings (based on self-reported trust) to examine body movements’ sensitivity to drivers’ level of trust. Results suggest body movements are not sensitive to individual differences in reported trust. Future work should further examine the utility of this covert behavioral metric by further examining situational differences.

Drivers’ calibration in self-evaluated performance The role of task-related workload and scale specificity

Drivers tend to hold favorable or optimistic views of their skills and abilities (e.g., Horswill et al., 2004), which can lead to situations where over-confident drivers are ill-equipped (Gregersen, 1996). In addition to general self-evaluations of skills, drivers can also make erroneous estimates of their own performance and of current task demands, possibly leading to poor decisions or failures to adjust behavior to mitigate risk (e.g., Horrey et al., 2015). Gaps between perceptions, self-evaluations and objective measures have been likened to the notion of calibration.

Impact of Feedback on Drivers' Attitudes towards Driving while Distracted: A Study in China

The distracting effects of concurrent cell-phone use on driving performance are well-documented. However, as the effects of distraction are not always easily observed (e.g., as in the instance of a “missed” event), many drivers may not believe that the issue is relevant to them. In the current study, 30 participants in China completed driving tasks in a driving simulator with/without a concurrent cell phone task. Following the trial, fifteen of them were shown video-based feedback of their performance (the feedback group). The other 15 participants (the control group) received no feedback. Attitudes towards cell phone use while driving were assessed prior to participation in the simulator study, immediately after receiving feedback, and one-month later. Following feedback, participants provided lower ratings of safety associated with cell-phone use while driving, lower ratings of ease of using a cell phone while driving, higher ratings of their own distractibility, and a decreased intention to use a cell phone while driving in the future relative to the control group. Effects of feedback continued to be observed one month later. Future research should examine whether the effects of feedback observed here are predictive of actual driving behavior.