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Modelling of Interactions Between Pedestrians and Vehicular Traffic to Promote Active Mobility: The Case of San Benedetto Neighbourhood in Cagliari (Italy)
22nd International Conference on Computational Science and Its Applications , ICCSA 2022 ; 13380 LNCS:453-468, 2022.
Article in English | Scopus | ID: covidwho-2013910
ABSTRACT
The COVID-19 has significantly led to changes in the mobility needs and in user travel behavior, due to the measures adopted to reduce the spread of the virus. While on the one hand this has resulted in a reduction in the number of trips, on the other this has entailed an increase in the use of the private car, considered as the safest form of transportation in urban contexts. Thus, administrations and policy makers have to promote actions and strategies to encourage soft mobility (i.e. walking and cycling), viewed as solutions to reduce transport emissions and ensure social distancing. This often implies the need for a redesign of urban spaces as pedestrians experience uncomfortable or unsafe situations about the surrounding environment. Within this framework, the paper proposes a methodological framework to evaluate the interactions between pedestrians and vehicular traffic using a microsimulation approach. The analyzed case study concerns a road intersection within the S. Benedetto neighbourhood in Cagliari (Italy). A scenario assessment has been performed through the computation of several performance indicators related both to private transport (i.e. level of service and emissions) and pedestrian users (i.e. density;speed and crossing time). The comparative analysis of results demonstrates that this research approach could represent a flexible and effective tool in guiding administrations through the decision-making process during the planning and development of projects for redevelopment of urban spaces and the promotion of soft mobility. Further research will focus on an extended study area, by modelling the behaviour of different categories of pedestrians and introducing in-field data. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 22nd International Conference on Computational Science and Its Applications , ICCSA 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 22nd International Conference on Computational Science and Its Applications , ICCSA 2022 Year: 2022 Document Type: Article