Figure 3

Disaggregated analysis. (a) Distribution of the normalised individual TTE for the city of Milan: the distribution of normalised individual TTE can be represented by the analytical distribution (6). The solid line is obtained by using the parameters \(\alpha= 0.19\) and \(\beta= 1.00\). (b) Normalised TTE distributions disaggregated according to home location: the position of the main mobility hub (home) influences the average value of T but not the distribution scaled by that value. For the ’Zona C’ we have \(\langle T \rangle= 1.520\pm0.009\mbox{ h}\), for the city center we have \(\langle T \rangle= 1.482\pm0.004\mbox{ h}\) while for the periphery we have \(\langle T \rangle= 1.416\pm0.003\mbox{ h}\) (errors correspond to the s.e.m.). (c) Normalised TTE distributions disaggregated according to classification of the mobility network: the role of home influences only the average value of T: selecting people whose mobility is characterised by more than one hub in their mobility network (we look for people with a percentage greater than 25% of round trips not starting and ending at home). Such people have \(\langle T \rangle= 1.72\mbox{ h}\), whereas people with a single mobility hub have only \(\langle T \rangle= 1.24\mbox{ h}\). (d) TTE distributions disaggregated according to the number of mobility days: these disaggregated distributions have a similar decaying in the tails, i.e. they have similar value of β (as a guide for the eye, the dashed line represents an exponential decay with the characteristic timescale β for Milan). Differences emerge instead in the behaviour of short TTE: people that use the car more regularly, have longer TTEs, since they perform more trips.