Spatial and temporal variations in hourly traffic volumes: A case study of cars, cyclists, and pedestrians in Bristol

Understanding spatial and temporal patterns of road users in cities is essential for transportation planning and infrastructure design. While recent studies have increasingly examined multimodal traffic dynamics, few have explored how simultaneous counts of multiple road-user types vary across both space and time using high-resolution, long-term data. We collect hourly counts of cars, cyclists and pedestrians at 58 locations in Bristol, UK, from January to December 2024. The data were preprocessed to ensure completeness and consistency, including aggregation to an hourly resolution and the creation of two complementary datasets: one containing absolute counts that reflect actual traffic intensity, and another containing normalized counts that emphasize relative temporal variations while eliminating the influence of differing absolute magnitudes across road-user types. Dynamic Time Warping (DTW) was then applied to quantify temporal similarities between traffic time series from different locations, followed by hierarchical clustering to group locations with comparable temporal patterns. Our findings show that the primary road user varies by location but remains consistent over time. Cyclists have the lowest traffic volume in all locations throughout the year. The daily, weekly and monthly patterns of car and pedestrian numbers differ across locations and clustering suggests locations can be grouped to some extent but also that there is high variability in the recorded traffic patterns. Normalising the data is useful for capturing differences in trends of low-traffic road users but disregards the information on absolute values of traffic volumes. This study contributes a substantial data set on urban traffic, it offers valuable insights into the long-term spatial and temporal characteristics of traffic volumes at the example of Bristol. We suggest this could inform urban planning and traffic management strategies, contributing to more effective transportation systems in urban environments.