Classifying Potential Multimodal Hubs in the Milan Metropolitan Area. A scalable tool for addressing Multimodality in the inner cities.

Abstract

Introduction

The concept of a multimodal mobility hub as a transport node, where the physical integration between transport services, intelligent technologies, and data-driven solutions allows users to combine several mobility options (Graf et al., 2022; Geurs et al., 2023) and its different typologies (Weustenenk & Mingardo, 2023), has recently gains space both in the Mobility Urban Agendas and in the academic domain.

Multimodal Hubs in Literature

In the Urban Mobility Agendas, the policy for implementing multimodality supports the integration of active mobility (i.e., walking and cycling) with public transport and micro-sharing mobility options to limit the use of private cars and change the hierarchy of mobility choices pyramid (Edmonton, 2023). In the academic domain, by updating a reflection on the spatial role of the transport nodes, started in the 1990s (Amar, 1989; Bertolini, 1999; Joseph, 1995; Kokoreff, 2002), the aim is devoted to investigating and operationalizing their potentialities as an "interface between the transport networks and the spatial structure of an area," including a range of transport and urban components (CoMoUK, 2019).

The transport node is an essential component of the transport network. It simultaneously is part of a spatial setting, representing the place where the accessibility offered by the transport supply may support the individual opportunities to perform activities, reach essential activities, and participate in social life (van Wee, 2011). This addresses the analytical approaches that go beyond established formats for combining the transport performances of the nodes with the variable densities and rhythms of users and uses, also related to the permanently or temporarily inhabited areas inside and around them.

Aims

By exploring the complementary dimensions associated with the transport node, including its suitable locations (Blad et al., 2022) and the profiles of the users and their needs (Bosehans et al., 2021; Bell, 2019; Tran and Draeger, 2021), the paper proposes the outcomes of an ongoing research finalized to develop an evidence-based strategy for planning and designing urban multimodal mobility hubs in the Milan metropolitan area.

The gap in research

On Urban Mobility discourse, several studies tried to cluster multimodal hubs into “typologies” (Arlington County, 2021; ARUP, 2020; Crowther et al., 2020; Grade et al., 2016; Metropolitan Transportation Commission, 2021). The typology of Multimodal Mobility Hub is beneficial to give an overview of the functions, sizes, and locations of the available multimodal hubs. However, the multimodal hubs typology does not support enough evidence-based policies, as they consider only the hub without looking into the context or the potential users.

Methodology

This paper proposes a multidimensional analysis framework to fill this gap left by typologizing the Multimodal Hubs. It analyzes potential Hubs based on Standard Mobility and Urban data that can make methodology scalable and applicable to different contexts, not just to the case study (Milan Metropolitan Area). The paper defines indicators that characterize the Multimodal hub drive from the literature (Geurs et al., 2023); then, the methodology mobilizes the accessibility of potential mobility hubs by applying the accessibility by proximity index (Lanza et al., 2023). Both dimensions are used as input (Bertolini, 1999) node/place classification model. Then, in unbalanced conditions, examine the "People" dimension. This dimension aims to explore users’ needs and practices to better understand the selected hub's functionality. The process is done through a digital and on-site survey, followed by active participation through a digital platform to discuss possible changes.

Results

The result is to indicate the status of Multimodality for each station based on their multimodality characteristics and the characteristics of the relevant context; further, it characterizes the people's needs and mobility practices. This paves the road to an evidence-based co-design for Multimodal Mobility hubs.