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In alignment with the European Union’s Vision Zero initiative to eliminate road fatalities by 2050, leveraging technological advancements becomes crucial for addressing the challenges of vulnerable road users (VRUs), and for mitigating the impact of human error. Despite increasing scholarly interest in applications of extended reality (XR), a research gap persists, particularly in the role of XR in transportation safety. Therefore, the aim of the study was to fill this gap through a systematic literature review to evaluate comprehensively the potential scope and practical applicability of XR technologies in enhancing the safety of VRUs.

A systematic review was undertaken, following PRISMA guidelines meticulously, in which 80 relevant articles from databases, such as Scopus and Science Direct, were identified and analysed.

The results of the analysis revealed the potential of XR beyond pedestrians and cyclists, and highlighted a lack of research about the impact of XR with regard to the personal traits or abilities of VRUs. The results of a thorough analysis confirmed the potential of XR as a promising solution for an approach to collaborative co-creation in addressing the safety challenges of VRUs. In addition, the integration of eye-tracking with virtual reality emerged as a promising innovation for enhancing the safety of vulnerable road users.

Theoretical implications include enhancing the understanding of applications of XR in VRUs’ safety and providing insights into future research possibilities and methodological approaches. Valuable insights into search strategies and inclusion-exclusion criteria can guide future research methodologies.

Practically, the findings from the study offer insights to assist urban planners and transportation authorities in incorporating XR technologies effectively for VRUs safety. Identifying areas for further development of XR technology could inspire innovation and investment in solutions designed to meet the safety needs of VRUs, such as enhanced visualisation tools and immersive training simulations.

The findings of previous research underscore the vast potential of XR technologies within the built environment, yet their utilisation remains limited in the urban transport sector. The intricacies of urban traffic scenarios pose significant challenges for VRUs, making participation in mobility studies hazardous. Hence, it is crucial to explore the scope of emerging technologies in addressing VRUs issues as a pre-requisite for establishing comprehensive safety measures.

A lesson has been learned from the pandemic experience that less damages to the environment and realizing more social responsibilities would be the direction of the post-pandemic period globally. The purpose of this study is to focus on identifying the appropriate determinants of the proposed urban travel behavior model to develop Smart Mobility in Smart Cities to protect the environment. Potential to realize Smart Cities with infrastructure development has been explored in this study if road users are keen to combat climatic change which is clear from the challenges of flattening the infection rate through the enforcement of rules and regulations by the various government.

The proposed urban travel behavior model includes sub-drivers for each of the main drivers in the theory of interpersonal behavior (TIB). These sub-drivers emphasize in forming intentions to perform the behavioral changes while driving on urban roads during COVID-19 and post-pandemic periods. A primary online survey was conducted among road commuters in the most crowded place in Malaysia, the Greater Kuala Lumpur. A total of 383 respondents who frequently drive on road during the past one year were surveyed for this study. This data analysis of this quantitative study applied a partial least squares-structural equation modeling approach to determine the significant findings and results.

The significant findings of the study reveal that environmental consciousness and timely deviation in driving during traffic congestion are positively and significantly influencing the travel behavior performance (TBP) of commuters on urban roads. On the other hand, wet conditions due to weather, narrow road infrastructure and habits of road commuters are negatively influencing TBP. Social responsibility is positively and significantly influencing TBP through the mediating effect of the intention of road commuters’ behavior.

The current environmental concerns and societal adherence efforts in breaking the chain of the infectious COVID-19 among people can be manifested to develop Smart Cities with less air and noise pollution in the future. In this context, the present study proposes an urban travel behavior model and tests for its suitability of a greener and cleaner environment for the benefit of future generations. The limitation of the present study is that travel hazards are not included in the framework, as it is a topic of its own volume.

It is timely to implement Smart Mobility on road business models for Smart Cities as the consequences of the pandemic make us to realize the importance of environmental concerns and the social responsibilities of everyone. TIB considers four drivers, namely, attitude, subjective norm, affect and habit which induce intention to perform behavioral decisions. The novelty of the present study is the development of sub-drivers for these four drivers in the context of the urban travel behavior model.

The Traffic Safety Culture (TSC) approach has been applied primarily in high-income countries (HICs), yet the great majority of the burden of road trauma falls on low- and middle-income countries (LMICs), where it constitutes a humanitarian crisis. The UN Decade of Action for Road Safety established road safety in LMICs as a priority issue and launched a plan to address it. Road safety has subsequently been incorporated into the international development agenda via the Sustainable Development Goals. Characteristics of road user behavior, governance, infrastructure, enforcement, and health services in LMICs have led to assertions that many lack a “safety culture” or, more specifically, a “traffic safety culture.” While this invites the suggestion that a TSC approach would have value in LMICs, the question raised in this chapter is whether a psychosocial approach like TSC, developed and applied in HICs, is transferable to LMICs. This is first explored by examining the critique of the assumption that commonly studied psychological processes are universal, noting examples that are relevant to road safety. Cross-cultural psychology studies show that some of the psychological processes commonly studied in HICs differ in important ways in LMICs, while broader comparative research based on anthropology and sociology demonstrates the important influence of religious and cultural factors, economic and infrastructure conditions, institutional capacity and governance. The sociological construct of governmentality provides insight into why public compliance with traffic safety law may be lower in LMICs, and why this situation is likely to take a protracted period of time to change. Given the broader context of road safety in LMICs, the Road Safety Space Model (RSSM) provides a useful framework for identifying the economic, institutional, social, and cultural factors that influence a particular road safety issue in a particular country. This has implications for methodological approaches to TSC in LMICs, as less structured, more ethnographic methods are arguably more appropriate. An analysis of a typical TSC model, drawing on research from LMICs, demonstrates that the model assumes a particular hierarchy of elements (values, behavioral beliefs, normative beliefs, prototypical image, control beliefs), and relationships between them, which may not be true in LMICs. It is therefore more challenging to apply TSC in LMICs, particularly making the transition from identification of the TSC values and beliefs that lead to behavior to the development of an intervention to bring about changes in behavior. TSC is undoubtedly a promising approach in LMICs; however, its first steps should incorporate qualitative approaches and recognize the wide range of factors that are relevant to TSC; use of the RSSM would facilitate such a process. There is scope for further research to refine models of TSC, to determine the best mix of methods to use, and to explore the role of governmentality and its implications for TSC. In the interim, practitioners should strive to understand and take into account the broader social and cultural factors that influence behavior in the particular LMIC where they are working.