In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance.

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22-48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers' lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance.

Characteristics of the road and surrounding environment in metropolitan shopping strips: association with the frequency and severity of single-vehicle crashes.

OBJECTIVES: Modeling crash risk in urban areas is more complicated than in rural areas due to the complexity of the environment and the difficulty obtaining data to fully characterize the road and surrounding environment. Knowledge of factors that impact crash risk and severity in urban areas can be used for countermeasure development and the design of risk assessment tools for practitioners. This research aimed to identify the characteristics of the road and roadside, surrounding environment, and sociodemographic factors associated with single-vehicle crash (SVC) frequency and severity in complex urban environments, namely, strip shopping center road segments. METHODS: A comprehensive evidence-based list of data required for measuring the influence of the road, roadside, and other factors on crash risk was developed. The data included a broader range of factors than those traditionally considered in accident prediction models. One hundred and forty-two strip shopping segments located on arterial roads in metropolitan Melbourne, Australia, were identified. Police-reported casualty data were used to determine how many SVC occurred on the segments between 2005 and 2009. Data describing segment characteristics were collected from a diverse range of sources; for example, administrative government databases (traffic volume, speed limit, pavement condition, sociodemographic data, liquor licensing), detailed maps, on-line image sources, and digital images of arterial roads collected for the Victorian state road authority. Regression models for count data were used to identify factors associated with SVC frequency. Logistic regression was used to determine factors associated with serious and fatal outcomes. RESULTS: One hundred and seventy SVC occurred on the 142 selected road segments during the 5-year study period. A range of factors including traffic exposure, road cross section (curves, presence of median), road type, requirement for sharing the road with other vehicle types (trams and bicycles), roadside poles, and local amenities were associated with SVC frequency. A different set of risk factors was associated with the odds of a crash leading to a severe outcome: segment length, road cross section (curves, carriageway width), pavement condition, local amenities and vehicle, and driver factors. The presence of curves was the only factor associated with both SVC frequency and severity. CONCLUSIONS: A range of risk factors were associated with SVC frequency and severity in complex urban areas (metropolitan shopping strips), including traditionally studied characteristics such as traffic density and road design but also less commonly studied characteristics such as local amenities. Future behavioral research is needed to further investigate how and why these factors change the risk and severity of crashes before effective countermeasures can be developed.

Reliability of ICD-10 external cause of death codes in the National Coroners Information System.

Availability of ICD-10 cause of death codes in the National Coroners Information System (NCIS) strengthens its value as a public health surveillance tool. This study quantified the completeness of external cause ICD-10 codes in the NCIS for Victorian deaths (as assigned by the Australian Bureau of Statistics (ABS) in the yearly Cause of Death data). It also examined the concordance between external cause ICD-10 codes contained in the NCIS and a re-code of the same deaths conducted by an independent coder. Of 7,400 NCIS external cause deaths included in this study, 961 (13.0%) did not contain an ABS assigned ICD-10 code and 225 (3.0%) contained only a natural cause code. Where an ABS assigned external cause ICD-10 code was present (n=6,214), 4,397 (70.8%) matched exactly with the independently assigned ICD-10 code. Coding disparity primarily related to differences in assignment of intent and specificity. However, in a small number of deaths (n=49, 0.8%) there was coding disparity for both intent and external cause category. NCIS users should be aware of the limitations of relying only on ICD-10 codes contained within the NCIS for deaths prior to 2007 and consider using these in combination with the other NCIS data fields and code sets to ensure optimum case identification.

Learning and retention of associations between auditory icons and denotative referents: implications for the design of auditory warnings.

OBJECTIVE: This study examined the way in which the type and preexisting strength of association between an auditory icon and a warning event affects the ease with which the icon/event pairing can be learned and retained. BACKGROUND: To be effective, an auditory warning must be audible, identifiable, interpretable, and heeded. Warnings consisting of familiar environmental sounds, or auditory icons, have potential to facilitate identification and interpretation. The ease with which pairings between auditory icons and warning events can be learned and retained is likely to depend on the type and strength of the preexisting icon/event association. METHOD: Sixty-three participants each learned eight auditory-icon/denotative-referent pairings and attempted to recall them 4 weeks later. Three icon/denotative-referent association types (direct, related, and unrelated) were employed. Participants rated the strength of the association for each pairing on a 7-point scale. RESULTS: The number of errors made while learning pairings was greater for unrelated than for either related or direct associations, whereas the number of errors made while attempting to recall pairings 4 weeks later was greater for unrelated than for related associations and for related than for direct associations. Irrespective of association type, both learning and retention performance remained at very high levels, provided the strength of the association was rated greater than 5. CONCLUSION: This suggests that strong preexisting associations are used to facilitate learning and retention of icon/denotative-referent pairings. APPLICATION: The practical implication of this study is that auditory icons having either direct or strong, indirect associations with warning events should be preferred.