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Drug driving is recognised as a major road safety problem in many countries. In Australia, the primary response to this problem involved the adoption of roadside drug testing (RDT), which was modelled on the policies and practices used to conduct random breath testing (RBT) for alcohol. However, there remain important differences in the way that RDT and RBT are conducted, which might produce differential effects on drug and drink driving behaviour. In addition, various psychosocial factors are known to influence the two behaviours. Thus, there is a need to investigate the relative influence of legal and psychosocial factors on drug driving and explore how they may be similar or different to drink driving. Accordingly, this study utilised Deterrence Theory and Akers' Social Learning Theory, augmented by measures of dependence and a range of psychosocial factors, to examine the factors associated with self-reported drink and drug driving. An online survey was completed by 1394 licensed drivers from the three most populous states in Australia: Queensland, New South Wales and Victoria. Self-reported drink and drug driving became more likely as level of dependence increased. In relation to legal factors, direct experience of avoiding detection was the strongest predictor of self-reported drink and drug driving. Among the psychosocial factors, a significant positive relationship was found between holding favourable attitudes toward both drink driving and drug driving and self-reported behaviours. The findings suggest that applying legal sanctions in isolation without addressing the psychosocial rewards and punishments for the behaviours is not sufficient to reduce drug or drink driving. Future research should identify countermeasures that integrate deterrence and psychosocial principles in order to reduce these risky driving behaviours., Safety and Security Science

Fully automated vehicles (FAVs) have the potential to improve road safety and reduce traffic congestion and emissions. Most studies of acceptance of FAVs have focused on motor vehicle users, largely ignoring other road users, such as cyclists. This study investigates the factors that influence cyclists’ receptivity towards sharing roads with FAVs and their behavioural intentions in interactions with FAVs. The online survey collected information on participant demographics (e.g. age, gender, crash experience), self-reported on-road cycling behaviours (e.g. violations, errors, positive behaviours) and their receptivity towards sharing roads with FAVs (e.g. attitude, social norms, trust). Three typical cyclist-vehicle interaction scenarios were presented to test the cyclists’ intention to engage in self-protective behaviours (e.g. giving a hand signal, giving way or moving over) during the interaction with a FAV. Three hundred and fourteen Australian adults (106 females vs 208 males) who had ridden a bicycle at least once in the past year completed the survey. The results show that older cyclists and male cyclists had a lower receptivity towards sharing roads with FAVs than younger cyclists and female cyclists, respectively. Cyclists who reported being involved in a bicycle crash in the last two years and those who reported committing more errors on roads were more willing to share roads with FAVs. Cyclists who had a higher propensity to risky behaviours and positive behaviours were less likely to take intended self-protective behaviours during interaction with FAVs. Findings of the study provide some insights from the cyclist's perspective to facilitate the development and implementation of automated vehicles., Values Technology and Innovation, Safety and Security Science

Despite a strong reliance on enforcement approaches to prevent drug driving in Australia, this behaviour is still prevalent. The objective of this study was to investigate the influence of problematic drug use (i.e., showing indications of addiction), exposure to roadside drug testing, the use of detection avoidance strategies, and perceptions relating to alternative transport options on drug driving among illicit drug users. A total of 1,541 licensed drivers from the states of Queensland, New South Wales, and Victoria completed an online survey. The survey collected demographic and problematic substance use information, as well as items assessing drug driving behaviour. Cannabis was reported to be the most commonly used drug (36.0%); the most common drug of problematic use (27.9%), and the drug most often taken prior to driving (43.5%). Observing police operating Roadside Drug Tests (RDT) was more common among the participants than being tested by RDT (35.7% vs 23%). The results indicated a significant association between being a drug driver and observing or being tested by RDT. The drug drivers were significantly more likely to report using a range of strategies to avoid police detection than the non-drug drivers. Similarly, the drug drivers reported that it was more difficult for them to use various alternative transport options than the non-drug drivers. Decision tree analyses found that significant predictors of self-reported drug driving were problematic drug use, holding a provisional or probationary licence, earning a low- or middle-income, and using detection avoidance strategies like remaining watchful for police vehicles and taking back streets. The findings of this study suggest that ongoing improvements to drug driving enforcement will need to be complemented by health-based approaches designed to reduce drug abuse and dependence, and improvements to public transport, in order to achieve a sustainable reduction in drug driving., Safety and Security Science

Movements of cyclists and m.otor vehicles at intersections involve a wide variety of potential conflicting interactions. In Australia, the high numbers of motor vehicles, particularly light passenger vehicles, mixed with cyclists results in many bicycle-light passengervehicle (LPV) crashes (3,135 crashes during 2002-2014). About 68% of cyclist deaths at Australian intersections in 2016 were due to crashes between bicycles and LPVs (DITRLDG, 2016). The high number ofLPV crashes among fatalities among cyclists is an increasing safety concem. When an LPV collides with a cyclist, the resulting impact forces in.tluence the probability of cyclist injury severity outcom.e. Therefore, the goa1 at intersections should be to understand whether and which particular crash patterns are more injurious, in order to better inform approaches to reduce the impact forces to levels that do not result in severe injury outcomes. To examine how crash pattem (or mechanism) influences the injury severity of cyclists in bicycle-motor vehicle crashes at intersections, researchers typically describe the crash mechanism in terms of crash types, such as angle crashes, head--on crashes, rear-end crashes, and sideswipe crashes (e.g., Kim et al., 2007; Pai, 2011 ). While crash types explain crash mechanisms to some extent, this study hypothesiz.es that the trajectories of the crash involved vehicles may provide additional information because they better capture the movements of the vehicles prior to collision. Furthermore, it is argued that injury pattem might be in.tluenced by vehicle travel direction and manoeuvre (Isaksson-Hellman and Wemeke, 2017). For example, when a car is moving straight ahead it is likely to have a higher speed than when it is turning, and if cyclists are struck at a higher impact speed, they tend to sustain more severe injury (Badea-Romero and Lenard, 2013). While many studies have evaluated the association between cyclist injwy severity and crash types, the factors that m

Micro-mobility use, such as electric scooters (e-scooters), offers convenience and environmental benefits (Christoforou et al., 2021; Vestri, 2021) and it has increased over the last five years following the introduction of shared e-scooter schemes in the United States in 2017 (Christoforou et al., 2021 ). Following the introduction of shared e-scooters there has been an observed increase in the number of people choosing to use personal devices (Haworth et al., 2021). E-scooters are typically used more for transport (Sanders et al., 2020), often replacing active travel modes than motor vehicle use (Sanders et al., 2020) although that is location-dependent (Wang et al., 2022). The use of shared and personal e-scooters is primarily associated with travel time and money savings, as well as the enjoyability of the transport mode (Christoforou et al., 2021 ). Perceived lack of safety has been shown to influence consumer acceptance (Kopplin et al., 2021). E-scooter riders have been shown to be at risk of trauma to the head and extremities (Bauer et al., 2020), although little is known about the events leading to trauma (e.g., fall as a result of rough terrain, collision with a vehicle). Protective equipment can reduce the risk of incidents (e.g., improving visibility of vulnerable road users) or lessen the risk of injury (e.g., helmets). Generally, little is known regarding the use of helmets and other protective equipment by e-scooter riders, except when injuries occur. Trauma studies have reported low ( 4.4%; Trivedi et al., 2019) to moderate (46%; Mitchell et al., 2019) use of helmets. While the majority of e-scooter presentations occur during evenings (Vemon et al., 2020), little is known about the use of reflective equipment by scooter riders. The aim of this paper is to explore factors that influence the use of protective equipment, including helmets and reflective equipment, by e-scooter riders. [From: Introduction]

Many studies have examined the level of risk perceived by cyclists when they are being passed by motor vehicles (e.g., Beck et al., 2021; Rasch et al., 2022) and others have reported that drivers with negative attitudes towards cyclists self-report higher levels of driver aggression towards cyclists (e.g., Delbosc et al., 2019; Fruhen & Flin, 2015; Haworth et al., 2018). However, self-reported behaviours may not reflect a driver's observable behaviour (Fruhen et al., 2019). Lamondia and Duthie (2012) proposed that LPD is an indicator of the driver's degree of respect for a cyclist but other driver factors may also be important. Little is known about how accurately drivers canjudge lateral passing distance (Haworth et al., 2018) or whether some unsafe passes could simply reflect poor driver understanding of cyclist needs when sharing roadways. The general finding that LPDs are lower when there are parked cars or oncoming vehicles (Rubie et al., 2020), suggests that drivers may leave inadequate LPDs if they perceive that moving into the opposite side of the road poses a risk to themselves or their vehicle. Rasch et al. (2022) is one of the few studies to measure drivers' perceptions of the risk to themselves in overtaking cyclists. Some studies have examined how different motor vehicle speeds influence perceived risk of the passing motor vehicle for cyclists (Apasnore et al., 2017; Garcia et al., 2020; Llorca et al., 2017; Rasch et al., 2022) or drivers (Rasch et al., 2022), generally finding that cyclists perceive higher motor vehicle speeds are more hazardous. This paper examines (1) whether negative attitudes towards cyclists influence perceptions ofrisk: to the cyclist in passing events, (2) the factors associated with driver perceptions of the risk to themselves, and (3) if increases in motor vehicle speed are associated with higher levels of perceived risk to the cyclist and driver in the passing event. [From: Introduction]

Naturalistic driving studies (NDS) are a method in transportation research that is increasingly used to bridge the gap between epidemiological research (e.g., using population crash databases) and individual level or experimental research (e.g., self-reported surveys or driving simulators). This article begins with defining NDS and providing a brief overview of NDS methods, including the strengths, limits and the unique ethical issues involved in conducting NDS. Following this, five case studies from Australia, Canada, China, the European Union, and the United States are presented, along with a synthesis of the lessons they have learned. The article concludes with a discussion of what the future of NDS may look like.