Geovisualization of Traffic Congestion Patterns in Lagos Using Floating Car Data

Traffic congestion in Lagos represents one of the most economically costly urban mobility challenges in West Africa, estimated to cost billions of naira annually in fuel waste and productivity loss. This study applies geovisualisation techniques to analyse spatial and temporal patterns of road traffic congestion across Lagos using floating car data derived from GPS-enabled ride-hailing vehicles. One month of aggregated vehicle speed and location data contributed by a logistics technology partner are processed and mapped at the road segment level for morning peak, afternoon off-peak, and evening peak periods. Congestion severity indices are computed from the ratio of observed travel speed to free-flow speed for each segment, and choropleth and kernel density maps are produced to communicate spatial patterns at district level. Temporal animation of congestion evolution is created for the morning peak period across a typical weekday. Results identify the Carter Bridge, Third Mainland Bridge, Apapa port access roads, and the Lagos Island-Lekki expressway junction as the most persistently severe bottlenecks. Spatial clustering of congestion is associated with market activities, road narrowing at informal bus stops, and inadequate intersection control. The study demonstrates the utility of crowd-sourced GPS data for traffic intelligence in data-limited urban contexts and provides spatial outputs to the Lagos State Traffic Management Authority. Keywords: traffic congestion, geovisualisation, floating car data, Lagos, urban mobility.