  Modelling, simulation, and forecasting offer a means of facilitating better
planning and decision-making. These quantitative approaches can add value
beyond traditional methods that do not rely on data and are particularly
relevant for public transportation. Lagos is experiencing rapid urbanization
and currently has a population of just under 15 million. Both long waiting
times and uncertain travel times has driven many people to acquire their own
vehicle or use alternative modes of transport. This has significantly increased
the number of vehicles on the roads leading to even more traffic and greater
traffic congestion. This paper investigates urban travel demand in Lagos and
explores passenger dynamics in time and space. Using individual commuter trip
data from tickets purchased from the Lagos State Bus Rapid Transit (BRT), the
demand patterns through the hours of the day, days of the week and bus stations
are analysed. This study aims to quantify demand from actual passenger trips
and estimate the impact that dynamic scheduling could have on passenger waiting
times. Station segmentation is provided to cluster stations by their demand
characteristics in order to tailor specific bus schedules. Intra-day public
transportation demand in Lagos BRT is analysed and predictions are compared.
Simulations using fixed and dynamic bus scheduling demonstrate that the average
waiting time could be reduced by as much as 80%. The load curves, insights and
the approach developed will be useful for informing policymaking in Lagos and
similar African cities facing the challenges of rapid urbanization.
