Distraction in road traffic: How Czech media covers the issue

Road users' inattention is one of the leading factors that contribute to crashes. It has been thoroughly researched from many perspectives, but there is limited information about the factors that influence risk perception and road users' attitudes. These factors are formed by personal and mediated experience, but education and public awareness play important roles. In this context, media seems to significantly influence risk perception and it may result in behavioural changes. This study aimed to review the coverage of driver inattention in the Czech media to analyse how it covers different types of inattention. Both quantitative and qualitative content analyses were conducted, and the sources of inattention mentioned in media reports were coded. We found the following: distraction is the most often reported inattention subtype; the media often communicates illegal behaviour, such as mobile phone handling; the preventive and educational potential of media coverage seems to not be fully utilized; and media reports are often focused on specific crashes, consequences, and immediate causes. Other risky aspects or inattention contributory factors tend to be neglected.

Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies

Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

Performance in Takeover and Characteristics of Non-driving Related Tasks during Highly Automated Driving in Younger and Older Drivers

This paper aims to examine the effect of age and various characteristics of non-driving related activities during highly automated driving on subsequent performance in notified takeovers among younger and older drivers. The paper presents new analyses of data collected in our earlier study (Clark & Feng, 2016). Non-driving-related activities that participants voluntarily chose to engage in during automated driving were categorized according to their cognitive dimensions in information processing. Using hierarchical multiple regressions, we analyzed the effect of driver age, total duration and number of engagement in non-driving-related activities, the duration and cognitive dimensions of the last activity prior to takeover on average speed during takeover and the response time to a takeover notification. We found that older drivers speed was negatively predicted by age while their response time to a notification was not predicted by any factor. In contrast, younger drivers showed a trend of positive relationship between age and average speed and the characteristics of the last task engagement explained a significant portion of the variance of response time to a notification.

Real-world personal conversations using a hands-free embedded wireless device while driving: effect on airbag-deployment crash rates

A wireless device embedded in the vehicle allowed the user to engage in a personal hands-free conversation (HFC), and automatically placed an emergency notification call to an OnStar call center if the vehicle was involved in a crash in which its airbag deployed. A database stored the exact counts, start timestamps, and billed durations of all HFC and airbag notification calls. In 30 months of naturalistic driving, there were 91 million HFC calls from an average of 323,994 drivers per month who made calls. There were 14 airbag deployments in 276 million driver-minutes of HFC conversation for an exposed incidence rate of 5.08 airbag crashes per 100 million driver-minutes. There were 2,023 airbag deployments in an estimated 24.7 billion driver-minutes of no HFC conversation for a not-exposed incidence rate of 8.18 airbag crashes per 100 million driver-minutes. The crash incidence rate ratio (IRR) is the ratio of these two rates or 0.62 (95% C.I. 0.37 to 1.05). Sensitivity analyses controlled for the impact on the crash IRR of estimated time spent driving per day and calls by passengers. Counting all crashes as much as 20 minutes later than a call as related to that call gave similar results. We conclude that for personal conversations using a hands-free embedded device the risk of an airbag crash is somewhere in a range from a moderately lower risk to a risk near that of driving without a recent personal conversation. These results are not consistent with the large increase in crash risk reported in epidemiological studies using the case-crossover method.