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Becoming a parent is one of the most important transitional experiences in adulthood that has significant implications for new parents’ mental and physical health and psychosocial development. A growing body of research examines how men transition to fatherhood and balance their work and family obligations in complex contemporary societies. However, this phenomenological evidence remains under-theorised from the life-course development perspective. In this paper, a semiotic cultural approach to life-course transitions is used to explore how a sample of educated and employed Australian men in heterosexual relationships experienced and made sense of their fatherhood and work and family conflicts. Thematic analysis of semi-structured interviews with 20 fathers highlights how these fathers attempt to navigate between multiple, ambiguous and sometimes contradictory societal expectations about fatherhood, while also struggling to balance their desires to be a ‘good father’ with their wives and partners’ attempts to be a ‘good mother’, thus evidencing the weak cultural guidance of transition to fatherhood. The analysis shifts the focus away from developmental outcomes and moves towards understanding the semiotic processes through which development occurs in the complex intertwinement between person and their environment. The discussion of men’s dilemmas about fatherhood also underscores the future orientation of human development and highlights how persons are actively and intentionally involved in this movement towards an unpredictable but imagined future.

Driver education and training are longstanding initiatives for novices to attain a driver license. More recently however, we demand more of such initiatives, expecting they can better prepare young novices to be safer in the early months and years of independent driving. In this chapter, we explore historical and current trends and evidence for these initiatives, both one-on-one and group-based initiatives, in the context of an established theoretical best-practice framework, the Goals for Driver Education. Beyond this, we highlight current lack of attention to driver education and training needs with current advances in driver support technologies in vehicles—both for novices but also experienced drivers. Moreover, we acknowledge the rapidly shifting climate of change towards increased vehicle automation and more livable cities. We argue the need to move beyond the current generalization that most driver education and training efforts are ineffective, to promote more nuanced successful approaches, and ways to best maximize the value of driver education and training to increase driver safety in a changing world.

Automated vehicles are an emerging technology that operate with differing levels of automatic control (SAE levels). The current study explored participants’ acceptance of a conditional (Level 3) automated vehicle (AV) before and after riding as a passenger for 10 min on open, public roads in uncontrolled traffic. Additionally, participants were asked to rate the riskiness (perceived risk) of a variety of vehicle maneuvers, such as turning, accelerating, and braking when approaching an intersection. We predicted that participants would report higher acceptance ratings and lower perceived risk ratings after experiencing the AV compared to pre-trip ratings. Further, we predicted that participants riding in the front-passenger seat would report higher ratings for risk compared to participants sitting in the rear-passenger or rear-driver seats. Sixty participants from South-East Queensland, Australia (aged 21–82 years; Mage = 45.78; 23 female) took part in the study. Compared to pre-trip responses, participants reported statistically higher ratings for acceptance, as well as statistically lower ratings for perceived risk with respect to specific vehicle maneuvers performed while in automated mode. Differences were detected between seats for perceived risk, but these results were less clear. Increases in acceptance and decreases in risk were also detected as the number of false hazards detected by the vehicle increased. Overall, these findings suggest that acceptance towards AVs may increase, and expectations of risk related to AV maneuvers may decrease, after participants have experienced the vehicles firsthand, on an open, public road in an uncontrolled traffic environment.

Drivers who have higher levels of hazard perception skill also tend to have fewer crashes. Training designed to improve this skill has therefore been proposed as a strategy for reducing crash risk. To date, however, hazard perception training has only been evaluated in supervised settings. This means that improvements in hazard perception skill resulting from such training may not generalize to unsupervised situations, which may limit opportunities for large scale roll-out via automated delivery methods. In the present study, we investigated whether a brief video-based training intervention could improve hazard perception skill when drivers completed it online without supervision. The training involved drivers watching videos of traffic scenes, while generating a commentary of what they were searching for, monitoring, and anticipating in each scene. Drivers then compared their own commentary to a pre-recorded commentary generated by an expert driver, hence allowing for performance feedback without an instructor present. A convenience sample of 93 drivers (who did not receive any performance-related incentives) participated in a randomized control study. The training was found to significantly improve response times to hazards in stimuli from the official hazard perception test used for driver licensing in Queensland, Australia, which is known to predict crash involvement. That is, the training was effective in improving hazard perception skill (Cohen’s d = 0.50), even though participants were aware that no one was monitoring the extent to which they engaged in the intervention. Given that the training could, in principle, be deployed at scale with minimal resources (e.g. via any online platform that allows video streaming), the intervention may represent a practical and effective opportunity to improve road safety.

Driver education providers may utilise technologies such as driving simulators to augment their existing courses. Understanding the perceptions that young drivers and parents have of simulators may help to make simulator-based driver education more accepted and more likely to be effective. Young drivers and parents completed an online questionnaire that included a “simulator invention” visualisation task. Items based on the Goals for Driver Education framework investigated perceptions of the most appropriate skill type, while others examined the most suitable target group for simulator training, and timing in relation to completing a formal driver education course for simulator training to occur. Both groups perceived that simulators were most appropriate for training a combination of physical, traffic, psychological, and social driving skills with learner drivers during attendance at a novice driver education program. Young drivers and parents had similar perceptions regarding the amount that each skill type should be trained using a simulator. Understanding the perceptions of young drivers and parents, and especially those who are somewhat naïve to the use of driving simulators, may aid in the introduction and administration of simulator training and may increase the effectiveness of driver education as a crash countermeasure.

Railway level crossing closures can disrupt traffic flow significantly, especially in peak hours. The current increases in road and rail traffic worsen the situation and can result in congestion known to significantly increase road users’ travel times. In this study, seven of the most problematic level crossings around Brisbane, Australia, were surveyed. The effectiveness of a set of treatments was tested and discussed using computer simulation models. The study found that the variability of warning times is the major cause of unnecessary boom gate downtime. Our observations showed that warning times could be reduced by 10–40 s on average for each crossing activation at the investigated sites. A major cause for the variability in warning times are trains stopping at stations that are not equipped with express train identification, and actual train speeds being lower than posted line speeds. Various tested treatments were found to be effective at reducing level crossing closure duration and reducing the variability in warning times, resulting in travel times reducing by 7–57% for road users, depending on the level crossing considered. This study shows the potential for the short to medium-term treatment of congestion issues at active level crossings, which are necessary with the current increased rail and road traffic flows.

The introduction of advanced technologies into novice driver education may improve its efficacy as a young driver crash countermeasure. Underpinned by the Goals for Driver Education and the Technology Acceptance Model, and using a mixed-methods approach, this thesis examined how young drivers, professional driver educators, and parents perceive five advanced technologies used for professional driver education, with a particular focus on driving simulators. Findings suggest that the perceptions of these groups are largely aligned. However, there is complexity in the way they view some technologies, particularly medium fidelity driving simulators and PC-based hazard perception training.

Crashes at railway level crossings are often catastrophic in terms of the number of fatalities and 23 serious injuries in a single event, especially if they involve heavy vehicles and derailment of 24 passenger trains (1 - 3). While representing a small proportion of crashes, a person or a vehicle is 25 hit by a train approximately every three hours in the US. Despite the recognition that a wide range of factors contribute to crashes at level 27 crossings , international investigations have consistently indicated that the major cause of level 28 crossing collisions is the road user (5), and that non - compliance with warning devices is 29 implicated in the majority of level crossing crashes (6 ; 7). Another main contributor to crashes is 30 the type of crossing and the warning infrastructure employed (e.g. 8; 9 - 13).