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”) 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!


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