Nairobi Motorcycle Transit Comparison Dataset: Fuel vs. Electric Vehicle Performance Tracking (2023)

This dataset contains GPS tracking data and performance metrics for motorcycle taxis (boda bodas) in Nairobi, Kenya, comparing traditional internal combustion engine (ICE) motorcycles with electric motorcycles. The study was conducted in two phases:

Baseline Phase: 118 ICE motorcycles tracked over 14 days (2023-11-13 to 2023-11-26)

Transition Phase: 108 ICE motorcycles (control) and 9 electric motorcycles (treatment) tracked over 12 days (2023-12-10 to 2023-12-21)

The dataset is organised into two main categories:

Trip Data: Individual trip-level records containing timing, distance, duration, location, and speed metrics

Daily Data: Daily aggregated summaries containing usage metrics, economic data, and energy consumption

This dataset enables comparative analysis of electric vs. ICE motorcycle performance, economic modelling of transportation costs, environmental impact assessment, urban mobility pattern analysis, and energy efficiency studies in emerging markets.

Institutions:

EED Advisory

Clean Air Taskforce

Stellenbosch University

Steps to reproduce:

Raw Data Collection

GPS tracking devices installed on motorcycles, collecting location data at 10-second intervals

Rider-reported information on revenue, maintenance costs, and fuel/electricity usage

Processing Steps

GPS data cleaning: Filtered invalid coordinates, removed duplicates, interpolated missing points

Trip identification: Defined by >1 minute stationary periods or ignition cycles

Trip metrics calculation: Distance, duration, idle time, average/max speeds

Daily data aggregation: Summed by user_id and date with self-reported economic data

Validation: Cross-checked with rider logs and known routes

Anonymisation: Removed start and end coordinates for first and last trips of each day to protect rider privacy and home locations

Technical Information

Geographic coverage: Nairobi, Kenya

Time period: November-December 2023

Time zone: UTC+3 (East Africa Time)

Currency: Kenyan Shillings (KES)

Data format: CSV files

Software used: Python 3.8 (pandas, numpy, geopy)

Notes: Some location data points are intentionally missing to protect rider privacy. Self-reported economic and energy consumption data has some missing values where riders did not report.

Categories

Motorcycle, Transportation in Africa, Electric Vehicles