The dataset, supplied by Compass IoT, is composed of vehicle journeys undertaken in several UK cities during the month of October 2023. The dataset describes urban mobility phenomena such as road safety and near-misses. The data helps understand where drivers are hard braking or swerving, and profile risk. Such an understanding can have impact in improved road design and reduction of road traffic injuries. The data also helps understand travel times, trip distribution, UK travel routes, speed, and hourly volumes. Moreover, this dataset can improve understanding of mobility behaviour, minimize commute times, increase individual productivity, transportation planning, and reduce greenhouse gas emissions and lower energy consumption.

This dataset provides a large sampling of vehicle journeys across a variety of different highly populated areas of the UK. Each record, corresponding to one vehicle journey, includes vectors corresponding to time, location (lat/long), and even recorded speed -- a first among CDRC-held datasets. Similar vectors with recorded acceleration, deceleration, and g-forces from swerving are often present as well.

Additionally, a distinction is made between cars, light commercial vehicles, and heavy commercial vehicles, so these differing vehicle types can be filtered or analysed separately. Vehicle make and model are sometimes present as well, providing further opportunity for fine-grained analysis of these journeys. For instance, driving behaviors such as speeding, acceleration, and deceleration of vehicles can be measured using the fine-grained journeys, and tailored by vehicle types, road environment, and connected vehicle environment. Based on this spatial-temporal dataset and measurement, some targets should be formulated such as optimize speeding behaviors and promote traffic safety, reduce acceleration and deceleration driving to reduce carbon emission and energy use, optimize road and urban environment to promote transportation efficiency and reduce traffic congestion.