## 6 Discussion and Conclusions
### Main Takeaways, Relevance, and Future Directions  
This review provides a comprehensive synthesis of empirical and experimental studies on PST variability at the PTI. The main takeaways are as follows:  
* Infrastructure design and passenger behavior are deeply intertwined. Elements such as door width, gap dimensions, platform markings, and seating arrangements have a measurable impact on PST and crowd flow dynamics.
* Accessibility improvements benefit all passengers. Features designed for passengers with reduced mobility (PRMs)--such as wider doors and level boarding--also enhance efficiency and comfort for the broader passenger base.
* Low-cost, evidence-based interventions can deliver significant benefits, including reductions in PST by up to 35%, as shown in experimental studies.
* New analytical frameworks like Level of Interaction (LOI) complement traditional LOS metrics, providing richer insights into crowd dynamics and informing design decisions.  
These findings matter now because urban transit systems face growing pressure from rising demand, aging infrastructure, and a societal imperative for inclusivity. With rapid urbanization and increasing diversity in user needs, transport agencies must adopt human-centered, data-driven approaches to optimize operations and ensure equitable access. Furthermore, the lingering gap between academic insights and policy implementation underscores an urgent need for stronger integration of empirical evidence into design standards and operational protocols.  
Future work can build on this review by
* Conducting longitudinal studies to observe behavioral adaptation to design interventions under real-world conditions;
* Expanding experimental research to diverse cultural and operational contexts, particularly in developing countries where PTI challenges may differ significantly;
* Exploring interdisciplinary solutions by involving urban planners, psychologists, engineers, and policymakers to co-create inclusive PTI environments;
* Leveraging emerging technologies, such as AI-based tracking and simulation tools, to model complex crowd dynamics and predict intervention outcomes at scale.  
By advancing these research directions, the field can move closer to realizing PTIs that are not only efficient but also resilient and inclusive, supporting the sustainable growth of urban transit systems worldwide.  
Conceptualization, V.A., A.P., V.M. and S.S.; methodology, F.G. and S.S.; software, S.S.; validation, S.S.; formal analysis, S.S. and V.A.; investigation, V.A., A.P., V.M. and S.S.; resources, A.P.; data curation, A.L. and F.G.; writing--original draft preparation, S.S.; writing--review and editing, A.L. and F.G.; visualization, A.L., F.G. and S.S.; supervision, V.A., A.P., V.M. and S.S.; project administration, S.S.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.  
This research received funding from Concurso DI Investigacion Asociativa Interdisciplinaria 2025, proyecto codigc: 039.776/2025, Pontificia Universidad Catolica de Valparaiso, Chile.  
**Acknowledgments:** Authors would like to thank all researchers from the Mobility and Transport Laboratory at Pontificia Universidad Catolica de Valparaiso, Chile.  
**Conflicts of Interest:** The authors declare no conflicts of interest.