Oslo City Bike
Oslo City Bike (OCB) is UIP’s flagship. Since the launch of the new system in 2016, OCB has logged over 10 million trips; an average of eight rides per bike per day, making it one of the most efficient bike sharing systems in the world. The Oslo system has 3 000 bicycles distributed at 250 stations within Ring 3, with a total of 6 000 locks.
In 2018, OCB handled 102 471 unique users who took a record number of 2 818 007 trips. In 2019, the use decreased somewhat, but still landed on 2 244 556 trips.
In 2020 OCB was a safe and efficient alternative for those having to get around town, but not wanting to use public transportation during a pandemic. With the support of the Oslo municipality we put spiked tires on 1 000 bikes so that we could keep the system open during the winter months as well.
On team with the city
All the way, we have worked closely, and have had a very good collaboration, with the Urban Environment Agency in Oslo municipality. Having a station in the neighborhood makes the area more attractive to residents, employees and visitors, and we are experiencing great demand from residents and businesses who want stations nearby.
Flexible and simple
The system is app-based, and you can easily retrieve the bike with the push of a button. UIP’s model makes it easy to get started, find a bike and start a ride. The entire system is built around and linked to the user’s telephone number. We use telephone numbers to verify the customer, contact them when necessary, as well as to make sure that it is easy and safe to become a city cyclist. Screens at the stations also enable user to get a bike without a smartphone.
City cyclists can also report errors on bicycles via the app. Errors and discrepancies are collected in reports in our admin interface where we can log, sort and prioritize repairs.
We have integrated data analysis and prediction models in the product to optimize operations. This way we can rebalance the system in the most efficient way possible. In addition, we can proactively allocate resources when a station experiences heavy traffic.