Data-driven micromobility network planning for demand and safety

Abstract

Developing safe infrastructure for micromobility like bicycles or e-scooters is an efficient pathway towards climate-friendly, sustainable, and livable cities. However, urban micromobility infrastructure is typically planned ad-hoc and at best informed by survey data. Here, we study how data of micromobility trips and crashes can shape and automatize such network planning processes. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this tradeoff for the city of Turin. We find that a full focus on demand or safety generates different network extensions in the short term, with an optimal tradeoff in-between. In the long term, our framework improves overall network quality independent of short-term focus. Thus, we show how a data-driven process can provide urban planners with automated assistance for variable short-term scenario planning while maintaining the long-term goal of a sustainable, city-spanning micromobility network.

A Systematic Review of Sustainability Criteria in Infrastructure Development

“…It should be noted that in many cases, water management infrastructure was viewed by A total of 37 out of 106 of the articles discussed green infrastructure with an emphasis on greenery and natural vegetation in urban spaces, including streets, parks, walkways, urban forests, and walls and roofs of various buildings and structures ( [22][23][24], etc. ), as well as other aspects of nature-based solutions, biodiversity preservation, or facilitation in the urban environment [12,25,26].…”

“…With regards to energy infrastructure, authors emphasised the transition to zero-carbon or decarbonised solutions [33], which also include the use of smart technologies to reduce energy consumption [34], as well as just transition that considers the needs of socially vulnerable societal groups [35]. For transport, some of the most distinct topics for discussion included the planning and facilitation of more sustainable transport infrastructure [30,36], data-driven solutions that may help in the planning process [26], and the introduction of new transport solutions and related infrastructures-such as hydrogen transport [37] or self-driving cars [38]. At the same time, researchers noted that transport infrastructure has a broader role in facilitating sustainability not only from the environmental perspective but through the enhancement of mobility and connectivity which provide social benefits, such as access to work, education, healthcare, and other significant public services [39,40].…”

A Systematic Review of Sustainability Criteria in Infrastructure Development

“…With regards to energy infrastructure the authors emphasise transition to zero carbon or decarbonised solutions (Glynn et al, 2018) which also includes use of smart technologies to reduce energy consumption (Gagliardi et al, 2020), as well as just transition considering the needs of socially vulnerable society groups (Calvo et al, 2021). For transport, some of the most distinct topics for discussion include planning and facilitation of more sustainable transport infrastructure (Zannat et.al., 2020; Buehler et al, 2021), data-driven solutions that may help in the planning process (Folco et al, 2022), and introduction of new transport solutions and related infrastructures -such as hydrogen transport (Kohler et al, 2010) or self-driving cars (Marletto, 2019). At the same time, researchers note that transport infrastructure has a broader role in facilitating sustainability not only from the environmental perspective -that is done through enhancement of mobility and connectivity which provide social benefits, such as access to work, education, healthcare and other significant public services (Wataya & Shaw, 2019; Jones et al, 2015).…”

“…Studies of Table 1 show the diversity of focuses on infrastructure: construction sector (1,11,19,20), transportation systems (2,9), energy infrastructure (7,17), waste management (11), water security (12). However, a major problem with this kind of application is fragmentation (15,17) that does not allow assessing of synergy and incapability of the multi-infrastructure environment as shown in (8,16). The little agreement on what kind of assessment indicators of state interventions is required was identified to date as well (1 -6, 9, 10, 12 -15, 18).…”

Advances in geospatial approaches to transport networks and sustainable mobility

“…New approaches to help planning for better cycling infrastructure are actively being constructed. For instance, Folco et al (2023) developed a data-driven method combining empirical micro-mobility data and a network growth model (Szell et al, 2022) to simulate how improvements to existing cycling infrastructure align with the demand, and how possible investments to infrastructure influence safety as the network grows. In addition, Beecham et al (2023) developed a connected bikeability index that considers safety, comfort, attractiveness, and coherence, to understand whether different parts of London, UK, are better connected by bike than others.…”