# Rebalancing operations

Adapt dynamically your rebalancing for more riderships

The issue of rebalancing is **critical** to manage a micro-mobility system. **A system is never perfectly balanced by itself.**

Some areas are primarily departure areas and others are arrival areas.

Many external factors can impact the use of the system and **require dynamic changes in the rebalancing strategies** (e.g., holidays, weather).

Over time, **user behaviors can change**, making it necessary to continually re-evaluate these strategies

## A more effective rebalancing strategy for an optimized and sustainable shared mobility system

### Increase vehicle use rate through high quality service

### Reduce your operating costs by optimizing each trip to pick up/drop off a shared vehicle

## Automate your fleet dispatching and rebalancing for better service

- **Modeling of vehicle rentals** and returns by station or by zone
- **Calculation of the optimal number** of shared vehicles to relocate per station or per zone for a maximum number of rentals
- **Automatic optimization of each tour** to match **the rebalancing strategy** (availability of bikes, reduction of kilometers traveled by vans, productivity of the operators etc.)

## State-of-the-art technology

Our predictive models calculate user **rentals and returns of scooters/bikes**, as well as unmet demand up to 24 hours in advance. They are based on **multiple data sources** processed in real-time by **contextual machine learning algorithms**:

- Real-time station occupancy (number of vehicles and free spaces)
- Dynamics of each station over the last few hours
- Calendar data (time of day, day of week, day of year, holidays, school holidays)

## Testimonies

> « The Qucit Bike solution keeps rebalancing drivers in zones to maximize productivity of bike pickups and drop offs, making the operation much more efficient. As a result of our partnership, we’ve seen very strong Y-o-Y improvements in availability shortages (full & empty stations). We also have the ability to get granular details on team member output which allows us to improve our approach to employee coaching & training. Overall, optimized rebalancing performance has driven a 27% Y-o-Y increase in trips and a 76% growth in membership for Bike Share Toronto. »  
> — Monica Wejman, General Manager, Bike Share Toronto at Shift Transit

## Cycling cities — going beyond bike share

Surprisingly enough, the history of bike-sharing began roughly 50 years ago.

The first bike-share system was introduced in **Amsterdam**, in 1965. The program called [“Witte Fietsen” (“White Bikes”)](https://www.theguardian.com/cities/2016/apr/26/story-cities-amsterdam-bike-share-scheme) put white-coated bicycles in the streets available without any payment and control. Many of them were damaged or stolen and this brought the endeavor to a close.

Only the beginning of the new century saw an increase in the bike-sharing systems from **13** in **2004** to **1608** in **2018**. Lately, the progress has been significant: from **2.3** million in **2016** the number of bicycles in bike-sharing systems skyrocketed to **18.2** million in **2018**

Today, there are even bike-share schemes above the arctic circle!

[Read more](/content/en/news/cycling-cities-going-beyond-bike-share/index.html)