Modelling Public Transport Corridors with Aggregate and Disaggregate Demand

Traditional microeconomic modeling of public transport (usually a single line) has been based on aggregated demand description, that is, total ridership along a line and average journey length. This way, aggregation is spatial rather than temporal, as most public transport systems are designed for the period of largest demand. With this approach, various authors have formulated optimization models whose goal is to maximize social benefit or minimize total costs (considering both users and operators), finding optimal levels for the decision variables such as frequency, vehicle size, number of bus stops and spacing between lines. Presently, it is feasible to capture more precise demand patterns in cases where either the payment device or the specialized infrastructure in buses and stations can provide not only passenger counts, but also exact identification of the origin and destination of the passenger journey (RFID cards along with wide-range devices on bus doors, cameras, etc.).