Urban transportation in Vietnam, dominated by fossil fuel-powered motorbikes, is causing severe air pollution, contributing to climate change, and posing a threat to public health. In response to these challenges, promoting the transition from traditional motorbikes to electric motorcycles (EMs) is considered a sustainable transportation solution, aligning with the global trend toward green development. However, to expand market share and enhance the acceptance of electric motorcycles, a deeper understanding of consumer perception and behavior is essential. This study aims to develop and test a research model based on the cognitive–affective–conative framework. Data collected from 506 conventional motorbike users in Vietnam were analyzed using the SEM method. The study employs a second-order model, grounded in the cognitive–affective–conative framework, to evaluate the relationship between perceived value and perceived cost with the intention to use electric motorcycles, mediated by the role of anticipated emotions. The findings clarify the role of perceived value and perceived cost in shaping customers' anticipated emotions, which significantly influence their intention to switch to electric motorcycles. These insights not only provide valuable information for manufacturers and policymakers but also contribute to shaping development and marketing strategies for electric motorcycles in the future.

The built environment elements in urban areas can have a significant impact on the performance of transport systems, including road safety. The primary objective of this research is to investigate the influence of the built environment on speeding behavior, as an indicator of road safety performance, using the city of Curitiba, Brazil, as the study's setting. The built environment comprises physical features within the city, such as development patterns and roadway designs, and can be categorized into six groups: density, diversity, design, destination accessibility, distance to transit, and demographics. The Geographically Weighted Regression (GWR) statistical model was employed to explore the correlation between built environment variables and the occurrence of speeding in a spatially nonstationary scenario. Additionally, Moran's I and Local Moran statistical methods were applied to investigate the spatial autocorrelation of speeding within the city. Data on speeding and location were collected through the application of a Naturalistic Driving Study. The measure of speeding was based on free-flow situations, considering the opportunity in which drivers could speed. In this study, the database included 1002 trips, 381.45 h of driving, and 9,443.83 km of travel within Curitiba and its metropolitan area from 2019 to 2021. The GWR model was applied using Curitiba's traffic analysis zones (TAZs) as the zonal level. GWR reduced residual spatial autocorrelation relative to the global linear model; however, the global model achieved a lower AICc. Only the variable “proportion of arterial roads” showed a statistically significant correlation with speeding at a 95 % confidence level, with an inverse correlation observed across 100 % of the TAZs. Furthermore, it was observed that speeding behavior in Curitiba exhibits spatial autocorrelation, justifying the use of the GWR model. Low-Low and High-High spatial clusters were identified, with statistically significant differences observed between them, including average income, density of commercial and service units, density of intersections, density of speed cameras, and traffic signal density. The characteristics of arterial roads in Curitiba, including infrastructure and traffic control, may be influencing the reduction of speeding behavior.

Connected and automated vehicles (CAVs) are an emerging technology expected to improve safety, efficiency, and accessibility outcomes for all road users. However, comprehensive and multi-group analyses of the technology still need to be undertaken by the government, car manufacturers, and researchers, particularly around social aspects such as justice and safety value disparities. This study explores car drivers’ and pedestrians’ perceptions of safety and justice in the current transport system and how the deployment of CAVs might disrupt them. Interviews were conducted with 30 participants in Australia, a car-dependent country. The participants were 18 car drivers and 12 pedestrians aged between 18 and 79. Participants predominantly identified as either pedestrians or car drivers, though some occasionally used the other mode. The interviews were recorded, transcribed, organised, and analysed using a reflexive thematic analysis. Three main themes were identified: (1) independence, (2) the transport system as a safety problem, and (3) the transport system as a justice problem. The analysis indicated that most participants preferred their current mode of transport due to perceived benefits and enjoyment. Car drivers often highlighted flexibility and independence, while pedestrians valued walkability and convenience. However, both groups expressed concerns about safety and justice in the current transport system, particularly regarding limited accessibility for people with disabilities and inadequate public transport. Finally, while both participants broadly supported the introduction of CAVs, many, especially pedestrians, expressed concerns about their potential to exacerbate existing disadvantages for vulnerable road users. This research finds that greater emphasis should be placed on increasing research on and planning for the impact of CAVs to ensure vulnerable groups’ concerns are addressed.

Transport policy research has been developed systematically since the second half of the 20th century, when urban planning and transportation systems became critical components of economic development and urbanization. The field has evolved through a wealth of diverse publications and scholarly contributions. Our comprehensive guide synthesizes the state of the art in 20 major categories of transport policy research, identified based on a data-driven categorization. Each category is represented by a leading expert in the field, providing a rigorous assessment of the state of the art on an area together with an identification of challenges to inform future research and policymaking. Aggregated analysis reveals six major trends in policy research, namely: Adaptability, Network Integration, Sustainability, Wireless Connectivity, Equity, and Resilience — combined to form the word ANSWER, with each component being crucial to understanding and addressing the field's multifaceted challenges. Our guide aims to provide answers to pressing challenges and serve as an essential, accessible reference regarding transport policy research for academics, policymakers, and industry stakeholders alike.

Large Language Models have attracted global attention due to their capabilities in understanding, knowledge synthesis, and generating contextually relevant responses, mimicking certain aspects of human reasoning. Although LLMs have demonstrated feasibility in performing autonomous driving tasks in simulated and real-world environments, little is known about their safety and ethical decision-making. To address these questions, we propose a novel framework for evaluating and interpreting the ethical decision-making mechanism of LLM-driven autonomous vehicles. Our study investigates the ethical dilemma of prioritizing saving pedestrians or passengers inspired by the Moral Machine Experiment. We used a stated preference survey to include factors of group size, age, gender, fatality risk, and pedestrian behavior to create 13,122 choice scenarios (a full factorial design) to analyze responses from advanced LLMs, including the GPT-4 series models from OpenAI and Mistral-Large from Mistral AI. Our findings reveal significant differences in the decision-making process and preferences for saving road users among these LLMs. Using a binary logit model to interpret GPT-4′s decisions, we found that the estimated number of deaths, age, and gender significantly affect the model's choices. The decision tree method was also applied to analyze LLMs’ decision-making processes, uncovering potential ethical standards and conditions considered by the models. This study provides valuable insights into ethical considerations in AI systems and thus facilitates the responsible development of AI in autonomous vehicles.

The rise of ChatGPT has prompted concerns over users’ agency when revealing personal data to artificial intelligence. This study examined users’ likelihood of disclosing their data to ChatGPT in physical and mental health scenarios. Participants (N = 216) completed a repeated measures survey where they viewed four vignettes of hypothetical scenarios and were asked to imagine disclosing health information (physical and mental health) at two sensitivity levels (low and high self-disclosure). A repeated measures ANOVA revealed participants were significantly more likely to provide their data when the information required low-disclosure than high-disclosure. Furthermore, participants were significantly more likely to report uploading their health information in the physical health scenario than in the mental health scenario. The findings suggest ChatGPT users exercise caution in disclosing data to the platform. Reluctance to upload information in sensitive scenarios reduces the training data for large language models, resulting in potential stagnation in technology development.

In the expanding food delivery sector, particularly in Asia, where motorcycles are preferred for their efficiency, there has been an alarming rise in traffic safety incidents involving delivery riders. This increase highlights the need for a comprehensive understanding of safety outcomes within the industry, encompassing both organizational and personal factors. Our study, using data from 401 motorcycle delivery riders in Vietnam, addresses this gap with a conceptual model based on the Safety Climate Model. This model assesses the impact of safety climate, knowledge, and motivation on rider safety performance. Our findings reveal that factors like management values, effective safety communication, and quality safety equipment are crucial in creating a positive safety climate. This climate significantly boosts safety participation and compliance among riders. Furthermore, the study confirms that safety climate indirectly influences safety outcomes through safety knowledge and motivation. These results illustrate the dynamic between organizational practices and individual behaviors in determining safety in the food delivery industry. The study underscores the need for a holistic approach to safety, extending beyond equipment provision to include management commitment, communication, and motivational incentives. Implementing such comprehensive strategies is vital for enhancing rider safety, contributing to a safer work environment, and reducing safety–critical incidents among food delivery riders.

Objectives: Understanding the risks associated with electric motorcycles (EMs) is essential for developing effective mobility and safety strategies in an era of increasing motorcycle use and the shift toward electric vehicles. In this research, we investigate the prevalence of crashes among EM and conventional motorcycle (CM) users, as well as factors contributing to the crashes. Methods: This study uses primary survey data from 972 motorcyclists (481 EM and 491 CM riders) collected in December 2023 in Hanoi, Vietnam. It compares the frequency of risky riding behaviors and crash types between the 2 groups. Additionally, 2 binary logit regression models are applied to identify factors associated with crashes in the past 12 months for EM and CM riders. Results: The results suggest that the prevalence of respondents who did not experience crashes (56.1%), minor crashes (68.8%), serious crashes with injury (80.9%), and hospitalization (91.1%) for EM riders was significantly higher than that for CM users. CM riders tend to engage in many risky riding behaviors more frequently than EM riders. Higher frequencies of speeding, smoking, and neglecting turn signals were related to greater crash risk in both groups. Red light running was a particular risk factor of crash prevalence for EMs only. Older EM users were more likely to experience a crash, and CM users traveling longer and living in urban districts were found to be linked to higher crash prevalence. Conclusions: Transitioning from CMs to EMs in Vietnam may offer some safety benefits, such as cautious behavior by EM riders and lower speeds, but there are no major differences in crash prevalence between the groups. Risky behaviors like speeding, smoking, and neglecting turn signals increase crash risks for both; red light running is a particular concern for EM riders and longer travel distances and urban residency for CM users. Targeted interventions, proper training, and licensing are essential, with attention to older EM riders’ vulnerabilities and the risks faced by CM users in urban areas and on long trips.

There is a plethora of technology currently available that have the ability to notify individuals of traffic enforcement locations while they are driving. This technology has the potential to undermine legal deterrent efforts for preventing risky driving behaviours. However, drivers’ experiences using this technology and the trajectories through which this might interfere with deterrence for road rule violations are largely unexplored areas. As such, the present study aimed to explore two research questions: 1) what type of technology is used and how is it used, and 2) how does drivers’ use of this technology influence deterrence for road rule violations. In total, 58 Queensland licenced drivers who use technology that informs them of legal enforcement while driving participated in focus groups. To consider differences in use between ages, the sessions were conducted in three different age groups: 17–25 years, 26–49 years, and 50+ years. Reflexive thematic analysis was applied to the data, resulting in eight recognised themes. The findings highlighted that for most drivers, the primary purpose of using the technology was for navigation, while being notified of enforcement locations was a secondary purpose. In addition, the use of this technology encouraged road rule compliance for some yet was used as a strategy to avoid being caught for road rule violations for others. The findings have a number of practical and theoretical implications, demonstrating the complex interplay between technology used for enforcement notifications, its role in deterring road rule violations, and the principles of responsible innovation.

Despite the anticipated benefits, the rollout of Connected and Automated Vehicles (CAVs) is likely to encounter numerous challenges, including public readiness to adopt and coexist with these vehicles. This study utilised a cross-sectional survey of 384 Australian residents aged 18 to 82 (M = 42.93, SD = 15.48) to assess public perceptions and support for policies designed to enhance safety and justice in interactions between CAVs and vulnerable road users (VRUs) such as pedestrians, cyclists and people with disabilities. Participants evaluated 15 policies (identified through a structured, expert-informed process as a preliminary stage) across five evaluation dimensions: acceptability for improving safety within the transport system, acceptability for improving justice within the transport system, perceived improvement of safety for all VRUs, perceived improvement of justice for all VRUs, and willingness to support each policy. Data were analysed using descriptive statistics, cluster analysis, and hierarchical regression models. Policies focusing on systemic improvements, such as VRU-focused infrastructure and technology enhancements, received strong public support. Public preferences align with policies promoting fairness and inclusivity, while punitive measures and VRU-burdening policies were resisted. Cluster analysis identified three groups: VRU-burdening policies (low support), VRU-centric safety policies (moderate support), and VRU-focused infrastructure and technology policies (high support). Regression analyses revealed that factors such as age, transport accessibility, and disability influenced policy support. A content analysis revealed a strong preference for prioritising public transport investment, implementing inclusive urban designs, and establishing robust ethical frameworks. The findings highlight the need for policies that prioritise VRU safety and justice in CAV deployment. Support for inclusive, non-punitive measures points to the importance of fairness and system-wide reforms. To transition toward a safer, more equitable transport system, the study suggests the potential for more radical, community-driven policies and increased transparency in CAV development.

Introduction: Chemsex, the use of psychoactive substances to enhance sexual experience, is most prominent in gay, bisexual and other men who have sex with men (GBMSM). This study explores the prevalence of chemsex in Australian GBMSM (N = 632) and its associations with psychosexual and psychosocial health. Methods: A cross-sectional online survey was conducted. Measures included demographics, psychological distress, attitudes toward sexuality (Sex-Positivity-Negativity Scale), sexual self-esteem, LGBT Community Connectedness, and sexual behaviors. Data were analyzed using descriptive statistics, ANOVA, and chi-square tests. Results: One-third (32.3%) reported engaging in chemsex in the past year. Those engaged in chemsex were younger and more likely to identify as Indigenous Australians. They reported higher levels of psychological distress, sex negativity, sexual self-esteem and satisfaction with their sex life. Men engaged in chemsex reported a lower degree of connectedness to the LGBT community and were more likely to report adventurous sexual behaviors, including group sex and creating pornographic imagery. Discussion: The association between chemsex and health is complex. While some men report higher sexual self-esteem and satisfaction, their reported involvement in chemsex also correlates with increased psychological distress and lower community connectedness; however, the directionality of associations is unclear and may reflect complex or bidirectional dynamics. Conclusions: Engagement in chemsex is common among Australian GBMSM and is associated with a range of mental health, sexual wellbeing, and social connection outcomes. These findings highlight the importance of developing informed, community-based public health strategies that reflect the complexity of chemsex practices and diverse experiences of men engaged in chemsex.

Promoting public transport is widely regarded as a key strategy for advancing sustainability. However, concerns about women's safety continue to pose a significant barrier to its regular use. A growing number of studies have highlighted the vulnerability of female commuters to harassment and crime, yet there is limited evidence on how these experiences –and the fears they generate– translate into changes in travel behavior. This knowledge gap makes it difficult to develop evidence-based interventions. Accordingly, this study examined the interrelations between sexual harassment, fear of crime, and travel-related behavioral adaptations among female public transport users in Spain. The analysis was based on a cross-sectional sample of 720 female public transport commuters. The average age of participants was 29 years. They responded to an e-survey addressing commuting patterns, perceptions of safety, and behavioral responses. Our results suggest that both direct and indirect experiences of harassment are consistently associated with higher levels of fear of crime, which in turn influence changes in travel behavior. Specifically, fear of crime was found to partially mediate the relationship between harassment and travel-related adaptations. These findings provide further insight into how psychological and contextual factors shape women's use of public transport, and highlight the need to address not only actual incidents but also the broader perception of insecurity.

Perceived accessibility refers to individuals’ subjective perception of how easy it is to reach destinations using a specific mode of transport. As such, understanding the effect of perceived accessibility on travel behavior is essential for creating transport systems and urban environments that are efficient, equitable, and sustainable. This study develops a new integrated model by combining the Norm Activation Model (NAM), the Theory of Planned Behavior (TPB), perceived risk, and perceived accessibility. This enhanced model offers a comprehensive understanding of the factors influencing individuals’ intentions to switch to urban train systems. Additionally, the moderating effects of perceived accessibility on the link between personal, contextual factors and switching intention are also explored. The model developed is tested using data obtained from a sample of 535 individuals in Hanoi, Vietnam. This is particularly important because more research in low- and middle-income countries (LMICs) is needed to address the sustainability challenges these nations face due to their dependency on motorized private transport. The findings show that subjective norms have the strongest effect on the intention, followed by personal norms, attitude, and perceived accessibility. This study also confirms the moderating role of perceived accessibility on the link between attitude and switching intention, while the other hypotheses regarding the moderating effects of perceived accessibility are not supported by the findings. These insights aim to inform policymakers and public transport authorities in developing targeted strategies to promote sustainable urban mobility in Vietnam.

In recent years, the relationship between academia and the fossil fuel industry has become a focal point of intense debate. This concern arises from the fear that corporate funding might skew research activities. A significant development in this area is the adoption of policies by a Dutch university, and discussions in several others, prohibiting research funded by the fossil fuel industry. These policies aim to safeguard academic freedom and integrity. Despite this, there has been little discussion on the myriad challenges, implications, and possible unintended consequences, particularly in the realm of safety-and-security research. As such, this manuscript delves into the complex transition towards a fossil-fuel-free society, examining it through the lenses of safety science and sociotechnical systems. It emphasizes the vital importance of collective responsibility in ensuring systemic safety and security as we navigate towards achieving the sustainable development goals. This journey requires a delicate balance between the objectives of safety and sustainability, along with a deep understanding of the security implications of decreasing our dependence on the fossil fuel industry. The strategy of distancing academic research from fossil fuel industries, commonly seen as a positive step, also demands a nuanced consideration of its broader impacts, including the setting of precedents for addressing other existential and systemic risks. Instead, we argue for the establishment of robust governance structures rooted in restorative justice principles. Such frameworks can facilitate productive dialogue with underrepresented groups, motivate the fossil fuel industry towards sustainable practices, and safeguard the integrity of scholarly research. This approach not only addresses immediate concerns related to fossil fuels but also lays the groundwork for a more inclusive and equitable model of climate risk research, essential for tackling the multifaceted challenges of our era.

Population aging is a macrosocial trend with growing implications for mobility and public health. In the coming decades, many countries are expected to experience a marked increase in the average age of their populations, raising new challenges for healthcare and mobility systems. The promotion of active mobility, widely supported in the literature for its role in maintaining health in later life, has gained visibility. However, it remains unclear whether existing digital tools, such as lifestyle apps, effectively contribute to this goal. Methods: This study examined the effectiveness of applications and tools designed to promote walking among older adults through a systematic literature review, complemented by additional sources, including sentiment analysis of user reviews. Results: Many walking apps offer features such as step tracking and personalization, but few address both physical activity and social isolation simultaneously. Available evidence suggests potential benefits in gait quality, balance, and reduced sedentary behavior in specific contexts. User feedback also points to high satisfaction, especially with simple and accessible interfaces. However, the scientific literature supporting these outcomes remains limited in scope and generalizability. Conclusion and practical insights: This multi-source review suggests that walking apps may support more active lifestyles among older adults, though current evidence is not yet conclusive. Future app development should prioritize usability and incorporate features that address both physical and social well-being, while ensuring accessibility and affordability for a broader range of users.

Drivers should react quickly in dilemma zones at signalized intersections, where ill-timed decisions may result in rear-end or angular collisions with other vehicles. Recent advancements in connected vehicle (CV) technologies, particularly cellular vehicle-to-everything (C-V2X), are expected to enhance driver decision-making by providing real-time traffic information. Despite this, most previous studies have not considered the latest C-V2X specifications, leaving critical questions unanswered about how drivers interact with and benefit from this technology in dilemma-zone scenarios. To address this gap, this study builds a co-simulation platform that integrates Unity and VISSIM to simulate four communication conditions: (1) no communication (baseline), (2) perfect communication (green-light countdown), (3) interrupted communication (green-light countdown with loading delays), and (4) communication loss due to the absence of smart infrastructure (out of service information). Sixty-two licensed drivers participated in four randomized trials, each with multiple unpredictable green-to-yellow transitions designed to capture dilemma-zone responses. Driving performance was assessed in terms of stop-or-go decisions and red-light running outcomes. Results of the random parameters binary logit model for stop-or-go decisions indicate that, compared to no communication, drivers are more inclined to proceed through the intersection when communication is lost. In contrast, perfect communication and communication interruption generally reduce this tendency. Furthermore, significant interaction effects revealed the observed heterogeneity, indicating that drivers with specific driving histories respond differently under communication interruption and loss conditions. For the red-light running outcomes, the descriptive analysis shows that under the perfect communication condition, the proportion of red-light running decreases by 3.44% among drivers. Interestingly, even interrupted communication leads to a 2.19% decrease in the proportion of red-light running outcomes. These findings demonstrate the complex ways in which C-V2X-based information can influence driver decisions, emphasizing the need for robust implementation strategies that are context-aware. This study sheds light on how drivers interact with emerging C-V2X systems and provides insights for road authorities and policymakers seeking to enhance safety and reduce crash risks at signalized intersections.

In low- and middle-income countries, electric motorcycles (EMs) are not generally well accepted in the community as many infrastructural, technological, and psychosocial barriers remain unaddressed. A greater understanding of adoption barriers perceived by motorcycle riders can help devise strategies, such as policy and behavioural change interventions, to increase the uptake of EMs. This study aimed to investigate the risk dimensions of EM adoption and integrate them into the Theory of Planned Behaviour to model users’ intention to adopt EMs. A multi-group analysis was also conducted to examine the moderating effect of demographic characteristics on the proposed model. The data were collected from two cities in Vietnam, making this one of the region's first theory-based studies on the electrification of the transport system. The outcomes of the structural equation modeling affirmed that the psychosocial variables outlined in the Theory of Planned Behaviour (i.e., attitudes, perceived behavioural control, and social norms) and perceived risk significantly influence the behavioural intention to adopt EMs. These findings hold significance for policymakers and manufacturers as they provide valuable insights into the factors that can be targeted to enhance the adoption of EMs. This represents a crucial step towards advancing sustainability goals in low- and middle-income countries.

The growth of the electronic economy has significantly transformed the food industry by offering alternative ways for customers and restaurants to interact and conduct transactions through online platforms. This shift has catalysed the growth of the food delivery sector, commonly referred to as P-hailing in Malaysia. However, this development has been accompanied by an increasing incidence of road traffic crashes involving food delivery motorcycle riders. The aim of this study was to compare the prevalence of risky riding behaviours between food delivery and non-food delivery motorcycle riders during rush hours using an observational study conducted in Shah Alam, Selangor, Malaysia. Observations were made during peak hours at six signalised intersections, with a total of 4,950 motorcycle riders observed, 52.3 percent of whom were identified as food delivery riders. Categorical data analysis methods were employed to assess differences in risky riding behaviours between these groups. The odds ratios for food delivery riders compared to non-food delivery riders were higher for mobile phone use while stopped (2.66 times higher), and mobile phone use while moving (2.49 times higher). In contrast, helmet non-use and running red lights was less common among food delivery riders. Although both groups exhibited higher percentages of signal violation and stopping beyond designated lines, no statistically significant differences were observed between the groups for these behaviours. These results provide critical evidence for policymakers, enforcement authorities, and platform providers to inform the development of targeted interventions and policies aimed at mitigating risky riding behaviours and enhancing the safety of both food delivery and non-food delivery riders.

The rise of ChatGPT has emphasized the need for an improved conceptual understanding of users’ agency when interacting with artificial intelligence (AI) systems for healthcare. Australian ChatGPT users (N = 216) completed a repeated measures online survey. Hierarchical regression analyses assessed the influence of demographic factors (age and gender), Technology Acceptance Model constructs (perceived usefulness and perceived ease of use), and extended variables (trust, privacy concerns) on users' behavioral intentions to use ChatGPT for physical and mental healthcare. The proposed model was partially supported: the findings emphasized the need to establish user trust in ChatGPT and its perceived usefulness in both areas of healthcare. Privacy concerns were a significant predictor of intentions to use ChatGPT for mental healthcare with perceived ease of use predicting intentions to use ChatGPT for physical healthcare. The findings indicate predictors of uses of AI cannot be generalized across healthcare types and unique drivers should be considered.

Introduction: The advancement of advanced driver assistance systems (ADAS) aims to enhance driving safety, efficiency, and convenience. However, their potential remains underutilized as drivers frequently disengage or avoid using these systems. This study investigates the phenomenon of ADAS disuse, encompassing situational disengagement and systematic avoidance, through in-depth interviews with SAE Level 2 automated vehicle drivers. Method: Using thematic analysis, we identified nine key themes influencing disuse across three domains: Driving task (strategic, tactical, and operational level of driving tasks); Human (sense of control, knowledge, trust, and responsibility); and Environment (road users and road situation). Results: Drivers cited discomfort with system aggressiveness, lack of trust in detection capabilities, and incompatibility with their driving styles as critical factors. Environmental complexities, such as construction zones and pedestrian-heavy areas, further exacerbated disengagement. Additionally, legal and moral responsibility emerged as influences on drivers’ preferences for manual control. Conclusions: Our findings underscore the need for adaptive, user-centered designs prioritizing trust, transparency, and context-sensitive system behaviors. By addressing these barriers, ADAS can achieve safer and more consistent adoption, supporting broader goals of accident prevention and traffic efficiency. Practical Applications: This study provides insights for enhancing ADAS design and fostering driver confidence, paving the way for their effective integration into modern mobility solutions.