Planning Demand-Responsive Transit to reduce inequality of accessibility

Accessibility measures how well a location is connected to surrounding opportunities. We focus on accessibility provided by Public Transit (PT). There is an evident inequality in the distribution of accessibility between city centers or close to main transportation corridors and suburbs. In the latter, poor PT service leads to a chronic car-dependency. Demand-Responsive Transit (DRT) is better suited for low-density areas than conventional fixed-route PT. DRT can thus reduce accessibility inequality, but this potential has not yet been exploited. On the contrary, planning DRT without care to inequality (as in the methods proposed so far) may further exacerbate the accessibility gap in urban areas. To the best of our knowledge, this paper is the first to propose a DRT planning strategy, aimed at the reduction of the inequality of the accessibility distribution. This objective is more complex than the usual generalized cost minimization. To achieve it, we combine a graph representation of conventional PT and a Continuous Approximation (CA) model of DRT. The two are combined in the same multi-layer graph, on which we compute accessibility. We then devise a scoring function to estimate the need of each area for an improvement, appropriately weighting population density and accessibility. Finally, we provide a bilevel optimization method, where the upper level is a heuristic to allocate DRT buses, guided by the scoring function, and the lower level performs transit assignment. Numerical results in a simplified model of 3 different cities show that inequality in the distribution of accessibility, measured with the Atkinson index, is reduced more than 20%.