1Hz GPS Tracking Data on Minibus Taxi Paratransit Vehicles in South Africa

Published: 16 June 2022| Version 1 | DOI: 10.17632/xt69cnwh56.1
Christopher Hull,


To date, GPS tracking data for minibus taxis has only been captured at a sampling frequency of once per minute. This is the first GPS tracking data captured on a per-second (1 Hz) basis. Minibus taxi paratransit vehicles in South Africa are notorious for their aggressive driving behaviour characterised by rapid acceleration/deceleration events, which can have a large effect on vehicle energy consumption. Infrequent sampling cannot capture these micro-mobility patterns, thus missing out on their effect on vehicle energy consumption (kWh/km). We hypothesised that to construct high fidelity estimates of vehicle energy consumption, higher resolution data that captures several samples per movement would be needed. Estimating the energy consumption of an electric equivalent (EV) to an internal combustion engine (ICE) vehicle is requisite for stakeholders to plan an effective transition to an EV fleet. Energy consumption was calculated following the kinetic model outline in "The bumpy ride to electrification: High fidelity energy consumption estimates for minibus taxi paratransit vehicles in South Africa". Six tracking devices were used to record GPS data to an SD card at a frequency of 1Hz. The six recording devices are based on the Arduino platform and powered from alkaline battery packs. The device can therefore operate independently of any other device during tests. The acquired data is separately processed after the completion of data recording. Data captured is initiated with the press of a button, and terminated once the vehicle reached the destination. Each recorded trip creates an isolated file. This allows for different routes to be separately investigated and compared to other recordings made on the same route. There are 62 raw trip files, all found in the attached 'raw data' folder under the corresponding route and time of day in which they were captured. The raw data includes date, time, velocity, elevation, latitude, longitude, heading, number of satellites connected, and signal quality. Data was recorded on three routes, in both directions, for a total of six distinct routes. Each route had trips recorded in the morning (before 11:30AM) , afternoon (11:30AM-4PM) and evening (after 4PM). The processed data is available in the 'Processed Data' folder. In addition to the raw data, these processed data files include the displacement between observations, calculated using Geopy's geodesic package, and the estimated energy provided by the vehicle's battery for propulsion, braking, and offload work. The python code for the kinetic model can be found in the attached GitHub link https://github.com/ChullEPG/Bumpy-Ride. Future research can use this data to develop standard driving cycles for paratransit vehicles, and to improve the validity of micro-traffic simulators that are used to simulate per-second paratransit vehicle drive cycles between minutely waypoints.


Steps to reproduce

RAW DATA: Data collection is done by taking mini-bus taxis trips while equipped with a handheld GPS recording device. GPS Device: The GPS device was designed and built at the University of Stellenbosch. It was based on an Arduino platform, with Arduino Nanos being used. In total, 6 devices were assembled and used for data collection. Each device is equipped with a dedicated alkaline battery pack, supplying 12V directly to the Arduino. All components are enclosed in a reused food container. An Adafruit Ultimate GPS Breakout was used to log GPS locations. This breakout includes an antenna. Serial communication is used with this module. All of the data is stored to an onboard SD card, through a High Speed SD/Micro SD Card Reader by Robotdyn. This is done through a SPI interface. Low correlation in the logged altitude by the GPS model was found, thus altitude data was added with the use an online altitude tool, gpsvisualizer.com, and using the GPS location as input. The user interface is kept very simple, with only 2 inputs and 2 outputs. For input, a power and recording switch is located on the front of the device. Two red LEDs to indicate GPS signal fix and active recording is located inside the device, which can be seen through the transparent lid. The LED located on the Arduino serves as an indication that the device is successfully powered on. Software: All data is stored in comma separated variable (CSV) files. Each recorded trip is saved in a separate file. The stored data includes: Date [dd/mm/yyyy] Time [hh:mm:ss] Latitude [degrees] Longitude [degrees] Altitude [m] Speed [km/h] Heading (degrees from True North) Signal quality Number of connected satellites Sampling is set to be done on the next full second of the Arduino’s internal clock. However, it can take up to 0.6s for the GPS module to retrieve a clean NMEA sentence to be processed. Depending on the time delay due to the GPS waiting for a clean sentence, every few samples could be logged at a time difference of 2s. PROCESSED DATA: The data was processed using code that corresponds to the kinetic model in "The bumpy ride to electrification: High fidelity energy consumption estimates for paratransit vehicles in South Africa". The code can be found at the Github link here and below: https://github.com/ChullEPG/Bumpy-Ride. In addition to the raw data, the processed data includes Slope angle [rad] Displacement [m] Propultion Work [J] Braking Work [J] Offload Work [J] Energy Consumption [kWh]


University of Oxford, Stellenbosch University


Global Positioning Systems, Vehicle, Energy in Developing World, Energy Consumption, Road Transportation, Developing Countries