Marco Migliore

Microtransit is a shared mobility service that operates between fixed-route transit and ride-hailing. It operates with a fleet of vans or minibuses within a service zone that is usually located in a rural or suburban car-oriented area with a transport demand that is temporally and spatially dispersed. Microtransit often expects customers to walk a short distance to pick-up/drop-off (PUDO) locations. The PUDO points need to be quickly, easily, and safely reachable by pedestrians. Thus, PUDO locations must be chosen after analyzing the walkability of the suburban area served by microtransit. This paper presents a comparison of macroscale and microscale indicators to assess the walkability of suburban neighborhoods where microtransit has to be introduced. We chose three suburban neighborhoods (Partanna Mondello, Tommaso Natale, and Mondello) in Palermo, Italy, as a study area, aiming to identify the best places to locate PUDO stops for a microtransit service. A GIS database has been built associating each link with a series of qualitative and quantitative attributes. Finally, we developed a walkability index that indicates the attractiveness of specific locations in terms of intermodal walkability. We also identified the critical pedestrian links that need actions to improve their walkability.

Adapting to climate change and mitigating its impacts are the main challenges for cities today. One objective that the European Commission has set in recent decades is reducing climate change inaction, and several political actions have been implemented. Among these actions, the Covenant of Mayors led to the development and adoption of Sustainable Energy and Climate Action Plans (SECAPs) by many cities worldwide. A challenge that local authorities must face during the development of a SECAP is the identification of the policies to be included in the plan. This paper presents a case study to show the validity of using a hybrid analytic hierarchy process (AHP) approach and various geographic information system (GIS)-based methods to support local authorities in the decision-making process during the development of SECAPs. These methods can improve participation among the community and stakeholders, at the same time making it possible to choose the best actions to reduce emissions and energy consumption and optimally allocate financial resources.