Speakers
Description
Pedestrian-friendly cities are crucial for sustainable urban development, as they prioritise walkability through safe, accessible, and appealing environments that promote healthier lifestyles and reduce reliance on motorised transport. These cities enhance social cohesion, economic activity, and public health by fostering active transportation modes and creating more liveable neighbourhoods. Achieving these outcomes requires a comprehensive understanding of pedestrian behaviour, including movement patterns and influencing factors. Pedestrian-oriented urban strategies contribute to improving health and safety by reducing vehicle-related accidents (Mendzina & Vugule, 2020a; Singhal, 2018; Varsha et al., 2023a), promoting social inclusion and equity (Eledeisy, 2023), and advancing sustainability by prioritising environmentally friendly transport modes (Handy, 2020). Increasingly, governments align these strategies with the Sustainable Development Goals (Singhal, 2018; Jeong et al., 2023; United Nations, n.d.) through effective policies that emphasise pedestrian mobility in public spaces (Reyes-Norambuena et al., 2024). In this context, data-driven analysis of pedestrian movement is vital for improving urban safety, planning, and economic performance, enabling resource prioritisation for impactful micro-level infrastructure improvements.
This paper directly addresses the critical gap in the current application of pedestrian data to strategically guide investment decisions in urban infrastructure. It investigates how data-driven insights can be effectively harnessed to prioritise resource allocation towards historically underserved areas, thereby promoting equity and fostering social justice. Specifically, this research tackles key questions, including: How can granular pedestrian data be used to identify and prioritize areas requiring investment in pedestrian infrastructure? How can such data inform resource allocation decisions to maximise impact? And how well does existing pedestrian infrastructure currently align with observed usage patterns? To address these pressing questions, this study leverages the power of integrated data analysis, combining pedestrian activity data gathered from Wi-Fi sensors with detailed geospatial data on existing pedestrian infrastructure within Loughborough town centre.
To gain a comprehensive understanding of the spatial dynamics of pedestrian movement and infrastructural needs, we classified our analysis into four distinct categories: Underutilised Areas, characterized by high pedestrian traffic coupled with inadequate infrastructure; Neglected Areas, demonstrating low pedestrian activity and a corresponding lack of suitable infrastructure; Effective Support Zones, exhibiting both high pedestrian traffic and robust, well-maintained infrastructure; and Overburdened Areas, struggling with high pedestrian volume that significantly outstrips the capacity of the existing infrastructure. This nuanced classification powerfully demonstrates the superiority of our data-driven analytical framework over traditional, less informed methods. By offering a precise and comprehensive evaluation of the relationship between pedestrian movement and infrastructural provision, this research reveals strategic opportunities to address spatial inequities and foster the creation of more inclusive and equitable urban environments. Specifically, the findings enable the development of targeted and evidence-based resource allocation plans to improve pedestrian infrastructure, focusing particular attention on underserved and overburdened areas. Ultimately, this data-driven approach promotes more equitable, sustainable, and pedestrian-friendly urban environments, leading to demonstrably fairer spatial outcomes and significantly enhanced urban planning decisions.
Keywords: Inclusive Cities, Spatial Equity, Data-Driven Decision Making, Pedestrian Activity, Pedestrian-Oriented Infrastructure.
References
1.Eledeisy, M. (2023). Inclusive Neighbourhoods in a Healthy City: Walkability Assessment and Guidance in Rome. In Urban Book Series: Vol. Part F813. https://doi.org/10.1007/978-3-031-29515-7_85
2.Handy, S. (2020). Making US cities pedestrian- and bicycle-friendly. Transportation, Land Use, and Environmental Planning, 169–187. https://doi.org/10.1016/B978-0-12-815167-9.00009-8
3.Jeong, I., Choi, M., Kwak, J., Ku, D., & Lee, S. (2023). A comprehensive walkability evaluation system for promoting environmental benefits. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-43261-0
4.Mendzina, E., & Vugule, K. (2020). Importance and planning of pedestrian streets in urban environment. Landscape Architecture and Art, 16(16), 80–86. https://doi.org/10.22616/j.landarchart.2020.16.08
5.Reyes-Norambuena, P., Martinez-Torres, J., Nemati, A., Hashemkhani Zolfani, S., & Antucheviciene, J. (2024). Towards Sustainable Urban Futures: Integrating a Novel Grey Multi-Criteria Decision-Making Model for Optimal Pedestrian Walkway Site Selection. Sustainability (Switzerland), 16(11). https://doi.org/10.3390/su16114437
6.Singhal, M. (2018). Walkability and Legislation: How supportive is the legislative framework as regards pedestrian concerns in the Indian cities? Proceedings of ICACE. https://doi.org/10.5176/2301-394X_ACE18.24
7.United Nations. (n.d.). Sustainable Development Goals. Retrieved January 6, 2025, from https://sdgs.un.org/goals
8.Varsha, T. C., Sajja, S., Ramya Aruna Siri, B., Prasad, G. H., & Kashyap Tejo Sai, E. (2023). Pedestrian behaviour analysis at intersection in Vijayawada for road user safety and infrastructure design. IOP Conference Series: Earth and Environmental Science, 1280(1). https://doi.org/10.1088/1755-1315/1280/1/012048
| Best Congress Paper Award | Yes |
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