---
license: cc-by-nc-4.0
task_categories:
- tabular-classification
- tabular-regression
language:
- en
tags:
- fleet-management
- telematics
- trucking
- dispatch
- predictive-maintenance
- synthetic-data
- delivery
- vehicles
- mindweave
- maintenance
- fuel
- test-data
- logistics
- transportation
- fleet
pretty_name: Vehicle Fleet Management Dataset (Free Sample)
size_categories:
- 1K<n<10K
configs:
- config_name: depots
  data_files: data/depots.csv
  default: true
- config_name: drivers
  data_files: data/drivers.csv
- config_name: maintenance
  data_files: data/maintenance.csv
- config_name: trips
  data_files: data/trips.csv
- config_name: vehicles
  data_files: data/vehicles.csv
---

# Vehicle Fleet Management Dataset (Free Sample)

> **This is a free sample** with 2,126 rows. The full dataset has **12,624 rows** across 5 tables.

Fleet operations data for a simulated delivery company with 60 vehicles across
3 depots. 15,000 trip records, maintenance logs, fuel purchases, and driver
assignments over 18 months.

Features mileage-based maintenance schedules, fuel efficiency tracking by
vehicle type, seasonal route patterns, and two anomalies — a fuel price
spike and a vehicle recall affecting 8 trucks.

Ideal for: fleet management software, logistics optimization, predictive
maintenance ML, fuel cost analysis, and transportation dashboards.


## Sample tables

| Table | Sample Rows |
|-------|------------|
| depots | 3 |
| drivers | 15 |
| maintenance | 50 |
| trips | 2,000 |
| vehicles | 58 |
| **Total** | **2,126** |

## Full dataset

The complete dataset includes all tables with full row counts:

| Table | Full Rows |
|-------|----------|
| depots | 3 |
| drivers | 15 |
| maintenance | 523 |
| trips | 12,025 |
| vehicles | 58 |
| **Total** | **12,624** |

**Formats included:** CSV, Parquet, SQLite

**[Get the full dataset on Gumroad](https://mindweavetech.gumroad.com)**

## About

Generated by [Mindweave Technologies](https://mindweave.tech) -- realistic synthetic datasets for developers, QA teams, and data engineers.

Every dataset features:
- Enforced foreign key relationships across all tables
- Realistic statistical distributions (not uniform random)
- Temporal patterns (seasonal, time-of-day, day-of-week)
- Injected anomalies for ML training and anomaly detection
- Deterministic generation (same seed = same output)

Browse all datasets: [https://mindweavetech.gumroad.com](https://mindweavetech.gumroad.com)