  Shared Mobility Services (SMS), e.g., Demand-Responsive Transit (DRT) or
ride-sharing, can improve mobility in low-density areas, often poorly served by
conventional Public Transport (PT). Such improvement is mostly quantified via
basic performance indicators, like wait or travel time. However, accessibility
indicators, measuring the ease of reaching surrounding opportunities (e.g.,
jobs, schools, shops, ...), would be a more comprehensive indicator. To date,
no method exists to quantify the accessibility of SMS based on empirical
measurements. Indeed, accessibility is generally computed on graph
representations of PT networks, but SMS are dynamic and do not follow a
predefined network. We propose a spatial-temporal statistical method that takes
as input observed trips of a SMS acting as a feeder for PT and summarized such
trips in a graph. On such a graph, we compute classic accessibility indicators.
We apply our method to a MATSim simulation study concerning DRT in
Paris-Saclay.
