Electric micromobility systems such as e-bikes and e-scooters represent sustainable mobility options especially for specific classes of travelled distances. Moreover, the coverage and accessibility of transit services can be expanded through the implementation and promotion of these systems. Therefore, transport engineering is dealing with the development of new tools to support the forecast of the potential demand both for door-to-door trips and its integration with transit. With respect to these incoming research challenges, the paper proposes a methodology to investigate private mobility through floating car data (FCD) to identify the potential demand that can be shifted from cars to electric micromobility (e-micromobility) systems while also exploring the opportunity to increase transit usage. The benefits of such methodology have been evaluated on a real large test case, i.e. Rome (Italy), through an FCD dataset of about 240,000 monitored vehicles. The developed methodology is parametric and, thus, it can be easily transferred to other city contexts taking into consideration the compatibility of the local network infrastructures and the micromobility solutions. In Rome, it was estimated that the potential demand for e-micromobility can reach a maximum value of about 20% of weekday-trips, while about 10% of the morning peak trips could potentially be interested in a multimodal trip (i.e. mass transit services and e-micromobility for the access/egress). Results can be adopted by local authorities, transport companies and electric mobility providers to optimize infrastructural measures or the location of shared e-scooters and e-bikes to increase potential e-micromobility demand, as well as to increase the number of multimodal mobility options.

Nigro, M., Castiglione, M., Maria Colasanti, F., De Vincentis, R., Valenti, G., Liberto, C., et al. (2022). Exploiting floating car data to derive the shifting potential to electric micromobility. TRANSPORTATION RESEARCH. PART A, POLICY AND PRACTICE, 157, 78-93 [10.1016/j.tra.2022.01.008].

Exploiting floating car data to derive the shifting potential to electric micromobility

Nigro M.;Castiglione M.;De Vincentis R.;Liberto C.;
2022

Abstract

Electric micromobility systems such as e-bikes and e-scooters represent sustainable mobility options especially for specific classes of travelled distances. Moreover, the coverage and accessibility of transit services can be expanded through the implementation and promotion of these systems. Therefore, transport engineering is dealing with the development of new tools to support the forecast of the potential demand both for door-to-door trips and its integration with transit. With respect to these incoming research challenges, the paper proposes a methodology to investigate private mobility through floating car data (FCD) to identify the potential demand that can be shifted from cars to electric micromobility (e-micromobility) systems while also exploring the opportunity to increase transit usage. The benefits of such methodology have been evaluated on a real large test case, i.e. Rome (Italy), through an FCD dataset of about 240,000 monitored vehicles. The developed methodology is parametric and, thus, it can be easily transferred to other city contexts taking into consideration the compatibility of the local network infrastructures and the micromobility solutions. In Rome, it was estimated that the potential demand for e-micromobility can reach a maximum value of about 20% of weekday-trips, while about 10% of the morning peak trips could potentially be interested in a multimodal trip (i.e. mass transit services and e-micromobility for the access/egress). Results can be adopted by local authorities, transport companies and electric mobility providers to optimize infrastructural measures or the location of shared e-scooters and e-bikes to increase potential e-micromobility demand, as well as to increase the number of multimodal mobility options.
Nigro, M., Castiglione, M., Maria Colasanti, F., De Vincentis, R., Valenti, G., Liberto, C., et al. (2022). Exploiting floating car data to derive the shifting potential to electric micromobility. TRANSPORTATION RESEARCH. PART A, POLICY AND PRACTICE, 157, 78-93 [10.1016/j.tra.2022.01.008].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/405486
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