Is a flick-through enough? A content analysis of Advanced Driver Assistance Systems (ADAS) user manuals.

Advanced Driver Assistance Systems (ADAS) are being developed and installed in increasing numbers. Some of the most popular ADAS include blind spot monitoring and cruise control which are fitted in the majority of new vehicles sold in high-income countries. With more drivers having access to these technologies, it is imperative to develop policy and strategies to guarantee the safe uptake of ADAS. One key issue is that ADAS education has been primarily centred on the user manual which are not widely utilised. Moreover, it is unclear if user manuals are an adequate source of education in terms of content and readability. To address this research gap, a content analysis was used to assess the differences in ADAS-related content and readability among the manuals of the highest selling vehicles in Australia. The qualitative findings showed that there are seven themes in the user manuals: differences between driving with and without ADAS, familiarisation requirements, operational limits of the ADAS, potential ADAS errors, behaviour adaptation warnings, confusion warnings, and malfunction warnings. The quantitative analysis found that some of the manuals require several years of education above the recommended for a universal audience (>8 years) to be understood. Additionally, there is a notable number of text diversions and infographics which could make comprehension of the user manual difficult. This investigation shows that there is a lack of standardisation of ADAS user manuals (in both content and delivery of information) which requires regulatory oversight. Driver ADAS education needs to be prioritised by policymakers and practitioners as smart technology continues to increase across the transport system. It seems that current strategies based on user manuals are insufficient to achieve successful adoption and safe use of these technologies.

Driver knowledge of cycling-related road rules in Queensland, Australia.

OBJECTIVES: Violations of road rules are common in bicycle-motor vehicle crashes, but little is known about how much this results from lack of knowledge of the rules. This article addresses the research questions of how well do drivers know the road rules related to interacting with cyclists, and what factors influence their level of knowledge. METHODS: An online survey compared drivers who reported riding bicycles on Queensland roads in the previous 12 months ("cyclists": n = 2,839) and those who did not ("drivers": n = 4,070). A list of 10 plausible road rules (four were not actual rules) relating to interactions between motor vehicles and bicycles was presented, and participants were asked "Which of the following road rules applies in Queensland?" The response options for each item were "Yes," "No," and "I don't know". RESULTS: The percentages correct varied markedly across the rules, from 86.5% to 38.7% for cyclists and from 72.2% to 20.9% for drivers. Incorrect responses were generally more common than "Don't know" responses (cyclists: 22.3% incorrect, 9.8% "Don't know"; drivers: 29.9% incorrect, 19.6% "Don't know"). The hierarchical regression analysis confirmed that cyclists had better road rule knowledge than drivers. In the cyclist-only model, more frequent riding was significantly associated with better road rule knowledge but explained only 3% of the total variance. Older cyclists and those living in more urbanized areas had better knowledge but age and location of residence together added only 1% to the variance explained. In the driver-only model, knowledge was better for male, older, more educated participants and those living in more urbanized areas but these variables together accounted for only 5% of the variance. CONCLUSIONS: The results of this study suggest that improving knowledge of some current road rules could be beneficial for cycling safety but for some other rules, improved knowledge could be detrimental for cycling safety and changing the rules to reflect shared perceptions of safe behavior may be more beneficial. For each of the rules, further research is needed to examine the links between knowledge and compliance, and the influence of compliance on the risks of bicycle-motor vehicle crashes and near misses.

Assessing driver acceptance of technology that reduces mobile phone use while driving: The case of mobile phone applications.

The nature of the road environment requires drivers to be vigilant and attentive. Distracted driving is a primary concern, as it threatens the safety of road users. However very little research has been conducted into interventions to combat such an issue. Existing interventions such as police enforcement and legislation appear to have limited effect. The use of mobile phone applications to assist in limiting driver distraction is an alternative intervention that is currently gaining traction. With a great array of potential benefits, such as reducing road toll, these applications can be readily available to all road users. Despite the positive implications, it is vital that drivers accept the use of such a technology for the intervention to be effective. Therefore, understanding driver acceptance is an important step in implanting such applications. To assess this, the present study examines the utility of two versions of the Technology Acceptance Model (TAM), the Theory of Planned Behaviour (TPB) and the Unified Theory of Acceptance and Use of Technology (UTAUT) for understanding the acceptance of technology designed to reduce distraction. Participants were presented with two different applications and responded to questions that indicated their attitudes towards the factors included in the TAM, TPB and UTAUT, alongside their intent to use the technology. A total of 731 participants responded to the survey, and their responses analysed. The results indicated that overall, Davis' (1985) TAM was slightly better in explaining behavioural intent for both Mobile Phone Application (MPA) 1 and MPA 2, explaining 66.1% and 68.7% of the variance, respectively. Davis' (1989) TAM and the TPB were close behind, while the UTAUT explained the least variance in behavioural intent of all the models. Overall, the findings of this study provide support for using psychological theories to assess the acceptance of mobile phone applications.