The paper describes research activities of monitoring, modeling, and planning of people mobility in Rome during the Covid-19 epidemic period from March to June 2020. The results of data collection for different transport modes (walking, bicycle, car, and transit) are presented and analyzed. A specific focus is provided for the subway mass transit, where 1 m interpersonal distancing is required to prevent the risks for Covid-19 contagion together with the use of masks and gloves. A transport system model has been calibrated on the data collected during the lockdown period –when people's behavior significantly changed because of smart-working adoption and contagion fear– and was applied to predict future mobility scenarios under different assumptions on economic activities restarting. Based on the estimations of passenger loading, a timing policy that differentiates the opening hours of the shops depending on their commercial category was implemented, and an additional bus transit service was introduced to avoid incompatible loads of the subway lines with the required interpersonal distancing.
Carrese, S., Cipriani, E., Colombaroni, C., Crisalli, U., Fusco, G., Gemma, A., et al. (2021). Analysis and monitoring of post-COVID mobility demand in Rome resulting from the adoption of sustainable mobility measures. TRANSPORT POLICY, 111, 197-215 [10.1016/j.tranpol.2021.07.017].
Analysis and monitoring of post-COVID mobility demand in Rome resulting from the adoption of sustainable mobility measures
Carrese S.;Cipriani E.;Fusco G.;Gemma A.;Mannini L.;Petrelli M.;Saracchi S.
2021-01-01
Abstract
The paper describes research activities of monitoring, modeling, and planning of people mobility in Rome during the Covid-19 epidemic period from March to June 2020. The results of data collection for different transport modes (walking, bicycle, car, and transit) are presented and analyzed. A specific focus is provided for the subway mass transit, where 1 m interpersonal distancing is required to prevent the risks for Covid-19 contagion together with the use of masks and gloves. A transport system model has been calibrated on the data collected during the lockdown period –when people's behavior significantly changed because of smart-working adoption and contagion fear– and was applied to predict future mobility scenarios under different assumptions on economic activities restarting. Based on the estimations of passenger loading, a timing policy that differentiates the opening hours of the shops depending on their commercial category was implemented, and an additional bus transit service was introduced to avoid incompatible loads of the subway lines with the required interpersonal distancing.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
