Sustainable walkability in inner areas of Italy: a research proposal on AI-based simulation for older adults Frida Milella1,* , Eleonora Clarizia1 , Alessio De Pellegrin1 and Stefania Bandini1 1 Department of Informatics, Systems and Communication (DISCo), University of Milano-Bicocca, viale Sarca 336, Milano, 20126, Italy Abstract This paper aims at discussing the ongoing research activities that are being conducted on the use of AI-based solutions to promote walkability indexes in the Italian inner areas. Although social sustainability is an expected outcome of the walkability concept, the literature has focused on urban social sustainability and the development of socially sustainable urban communities, while attention to pedestrian-friendly rural areas is lacking. The paper examines existing research on the subject and emphasises the potential of agent-based simulation to create indicators that promote service accessibility and inclusion, specifically in terms of sustainable walkability in rural areas with a high density of older people. Keywords social sustainability, sustainable walkability, inner areas, artificial intelligence, agent-based simulation 1. Introduction proving pedestrian mobility is essential for promoting active ageing and enhancing the quality of life of older The significance of walking and the concept of walk- adults by facilitating social engagement and indepen- ability are becoming increasingly important in urban dence [13], as well as fostering a sense of community and planning, partly as a result of the increasing public de- reducing social isolation among older population [14, 15]. mand and the goal of sustainable urban development [1]. Furthermore, the incorporation of high-quality mobil- The concepts of walkability and walking are strongly ity conditions and accessibility in urban public spaces interconnected with the notions of the livability of local is essential in ageing, in order to ensure convenient ac- communities, as well as sustainability and its three fun- cess to services and promote conducive environments damental dimensions: economic, social, and environmen- for social interaction [16, 17, 13]. In particular, it is im- tal [1]. Owing to a long-standing focus on tackling en- perative to guarantee that older people have easy acces- vironmental issues, the field of sustainability has placed sibility to healthcare services [18, 19], as to effectively considerable emphasis on the convergence of environ- improving and safeguarding their general state of health mental and economic factors [2]. In contrast, the social and well-being [19]. Currently, the issue of accessibility aspects of sustainability are frequently acknowledged to healthcare is being studied from a user-centered ap- but receive limited analysis [2, 3], often being perceived proach and is being integrated with a personal mobility as the least strong and least clearly defined element [2]. aspect [20]. Indeed, recently, there has been a rise in Social sustainability is concerned with promoting de- the number of studies examining the quality of public velopment that encourages social engagement, social spaces and their impact on the capacity of older adults inclusion, and cultural enrichment [3], and walkability is to walk and access services and activities [13], acknowl- an essential component in the pursuit of social sustain- edging accessibility as a contributing component in ur- ability [4]. The concept of a walkable neighbourhood is ban social sustainability [5]. Nevertheless, the accessi- indeed frequently discussed in literature as a key element bility to services is contingent upon the geographical in promoting urban social sustainability and the devel- aspect [21], with rural communities need to face chal- opment of socially sustainable urban communities [5, 6] lenges in terms of accessibility to services as a result of (e.g., [7, 8, 9, 10, 11]). their frequent disconnection from main centres of in- The importance of social sustainability is becoming frastructure [22, 21]. The existing body of research on increasingly important in an ageing population [12]. Im- walkability is predominantly concerned with urban and Ital-IA 2024: 4th National Conference on Artificial Intelligence, orga- metropolitan areas [23, 24, 25] making it less applicable to nized by CINI, May 29-30, 2024, Naples, Italy rural, small urban, or semi-urban communities which do * Corresponding author not have access to pedestrian spaces of the same nature $ frida.milella@unimib.it (F. Milella); e.clarizia@campus.unimib.it as major cities [26, 25]. The geographical characteristics (E. Clarizia); a.depellegrin@campus.unimib.it (A. D. Pellegrin); and sizes of rural areas differ from those of urban areas, stefania.bandini@unimib.it (S. Bandini)  0000-0002-0522-2804 (F. Milella); 0000-XXXX-XXXX-XXXX which makes it difficult to measure the walkability of (E. Clarizia); 0000-XXXX-XXXX-XXXX (A. D. Pellegrin); rural areas using the neighborhood-level geography typi- 0000-0002-7056-0543 (S. Bandini) cally used in research [25]. This implies that research on © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings the influence of walkability on socially sustainable com- demographic fragility caused by an ageing population, munities should take into account the local conditions physical and ecological instability resulting from insuf- of accessibility, i.e. broaden the focus to include rural ficient handling of semi-natural resources, and under- communities as well. utilization of a significant amount of land resources in Furthermore, a recent systematic review of the liter- numerous localities. ature [27] on the role of AI-powered and sensor-based Walkability metrics gauge the level of pedestrian- technologies in assisting informal carers (often volun- friendly in a neighborhood’s built environment, and walk- teers or relatives) who provide care for older adults, re- ability evaluation is employed to evaluate this friendli- vealed a lack in the reviewed literature concerning the ap- ness [35]. Several walkability indices have been created plication of location-based technologies for older adults to objectively assess the features of the built environment residing in remote regions, suggesting to focus on ex- that promote walking habits [36]. These indices range ploring the integration of emerging technologies, such from ones that concentrate on urban form factors at the as AI and Geographic Information System (GIS) [28], to neighbourhood level (such as population density, land improve healthcare for informal carers and older adults use diversity, and street connectivity) to those that focus in rural regions. Similarly, a second systematic review on urban design factors at the street level (such as the by the authors [29] determined that employing innova- size and layout of streets, the design and condition of tive strategies to create outdoor spaces that cater to the buildings, and street furniture) [36]. However, walkabil- needs of adults in need of care, while also providing addi- ity in rural communities presents a unique challenge as tional support to their informal carers, has the potential its theoretical and practical basis has not been thoroughly to provide significant assistance to these carers. examined in this specific context [25]. This presents a This article aims to discuss the ongoing research on substantial opportunity for the Italian territory, as in- the use of AI-based technologies to enhance a sustain- ner areas comprise over 4,000 municipalities and over able walkability in inner areas of Italy. This research is a 20 percent of the country’s resident population, or ap- component of the ongoing project called “Care provision proximately 60 percent of the national territory [37]. On across different territorial contexts”1 . Its objective is tothe other hand, there is a clear need for more research address the current lack of walkability indexes for inner focused on rural older adults and their connection to the areas by investigating the potential of AI-based tech- community, as the current evidence is insufficient [38, 39]. nologies and promoting the achievement of a sustainable The high occurrence of residential proximity, with family walkability in inner areas within an ageing society. members living together and multigenerational house- holds, has created a strong intergenerational exchange and family support system for older adults requiring 2. Walkability and Inner Areas care in rural areas [33]. This makes these areas highly promising for the development of new walkability in- The term rural is commonly understood to refer to areas dices aimed at creating socially sustainable communities. with a small population, few settlements, and remote- Our research activity is indeed being focused on studying ness [30]. However, there is no consensus among aca- how AI-based solution can aid in developing sustainable demics on whether all of these characteristics need to be walkability indexes in Italian inner areas. present together in order to define a settlement as rural, or if it is enough for just one of these elements to be present [30]. A significant portion of the Italian territory 3. AI-based solutions to improve is organised spatially according to “minor centres", which are commonly of small size and frequently provide resi- walkability in Italian inner dents with limited access to essential services [31]. The areas: the intended value of characteristics of this territory can be summarised using the term “inner areas" [31] which overlap with the iden- using agent-based simulations tification of rural regions that face a notable deficiency Scholarly literature provides several examples of using in the provision of essential services [32, 33]. However, Artificial Intelligence (AI) techniques to assess walkabil- inner areas exhibit three primary attributes [34]: socio- ity. For instance, scholars employed machine learning 1 (ML) techniques to evaluate the state of sidewalks, as a This publication was produced with the co-funding of Euro- pean Union – Next Generation EU, in the context of the Na- substantial predictor of a pedestrian-friendly neighbour- tional Recovery and Resilience Plan, PE8 Conseguenze e sfide hood, through the analysis of pedestrians’ physiological dell’invecchiamento", Project Age-It (AGE - IT - A Novel Public- responses as gathered by wearable accelerometers [35]. private Alliance to Generate Socioeconomic, Biomedical and Tech- Several studies have examined the integration of deep nological Solutions for an Inclusive Italian Ageing Society- Age- learning (DL) with environmental sensors to evaluate ing Well in an Ageing Society) - AGE-IT- PE00000015 CUP: H43C22000840006 the walkability of urban streets [40], have explored the utilisation of Streetview Image and semantic segmenta- models into Digital Twins environments with GIS-based tion to create a walkability evaluation index [41] or have analysis, maybe allowing for a deeper understanding of estimated walkability measures at a street level [42]. Fur- older adults personal mobility also in inner areas. In thermore, a few studies have suggested a network-based this regard, Liu et al [49] recently examined the benefits measure of walkability that incorporates road network of employing agent-based models (ABM) as a quantita- structure and user opinions using machine learning tech- tive tool for assessing walkability due to their inclusion niques with the aim to get predictive models that yield of subjective aspects, integration of many parameters, comprehensive walkability scores at a spatial level [43]. and capacity to distinguish between various populations. Other studies have suggested novel methods for utilis- Similarly, Bandini et al [50] conducted a study with the ing pre-trained models to create adaptable models that purpose to evaluate the walkability of the city of Milan can predict walkability scores for cities that were not by simulating the age-driven pedestrian dynamics, which included in the original training process [44]. involve various behaviours such as different speeds and The scientific publications on walkability studies have crossing behaviour. Badland et al. [51], instead, devised significantly expanded over the past twenty years [45]. an agent-based modelling tool that integrated the advan- However, our current study is revealing that scholarly tages of Service Area Approach mapping to examine the research on the use of AI algorithms to evaluate walkabil- correlation between amenity access and neighbourhood ity in rural areas, and especially in the Italian inner areas, walkability while also enabling the testing of various is under-investigated. Nonetheless, AI has significant planning scenarios. Therefore, given that agent-based potential for evaluating the pedestrian-friendliness of simulation models simulate the actions and interactions inner areas. Geographical information, socio-economic of individual agents from various demographic groups data, and pedestrian behavioural patterns can be utilised in a specific environment, the incorporation of AI tech- through the application of ML algorithms to provide niques may have the potential to accurately depict the walkability scores that are specifically customised for pedestrians’ mobility patterns or the barriers for their the distinct attributes of inner areas and ageing pop- personal mobility at each age categories, contributing to ulation. Some existing studies in urban context have attain our goal to define a sustainable walkability concept highlighted the need of using Geographical Information in Italian inner areas for older population. Systems (GIS) to define an index that measures the walk- ability of older people and supports the creation of ad- vanced simulation models based on AI [46]. In a similar 4. Conclusions vein, another study assessed the emotional experience of Although social sustainability is an expected outcome pedestrians, specifically focusing on older adults, propos- of the walkability concept, the literature has focused on ing an “affective walkability” indicator [47]. The aim was urban social sustainability and the development of so- to investigate how safe, comfortable, and walkable an cially sustainable urban communities, while attention environment was, within the context of promoting social to pedestrian-friendly rural areas is lacking. Moreover, and active inclusion of older adults in urban areas. Based there exists a dearth of scholarly publications both in on this, our research activity is being focused on studying walkability metrics targeted to rural communities and villages in Italian inner areas, including Premeno (VB) in the use of AI-based techniques to promote pedestrian and Petrella Tifernina (CB), with a high aged population friendliness in rural areas. The article reviews some of density. Our goal is to understand the factors that af- the currently available contributions on the topic and fect walkability in inner areas and its accessibility, and highlights the potential of agent-based simulation to de- how the integration of AI techniques can promote so- velop indicators that facilitate service accessibility and cial inclusion and equity of access to healthcare services, inclusivity, i.e., sustainable walkability in rural areas with ie a sustainable walkability in these areas. Indeed, one a significant older population density. Further research potential benefit of integrating AI-based tools, such as will be carried out using multiple case studies to derive a remote sensing or GIS technologies, is the provision of generalised research methodology for the specific context comprehensive mapping and geographical analysis. This of Italian inner areas. information can be utilised to guide targeted measures that improve the walkability of inner areas by revealing crucial details regarding pedestrian access, connectivity, References and safety. In addition, according to a recent systematic review of the literature [48] the combination of wear- [1] A. Baobeid, M. Koç, S. G. 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