(e-)bike sharing systems
The missing transport for cities' public network
Did you know that 54% of the world population lives urban areas? And the number is increasing by 2 habitants per second. That's why part of the future of our cities now relies on their capacity of going from Grey to Green. A huge challenge for every a city is its public transportation network, having a big impact in the quality of life of all the habitants. Each mode of transport has advantages that make it attractive and disadvantages that have to be managed so that the city is a desirable place for its citizens. Bicycles are an urban transportation mode and 1.250 million bicycles are currently used as a public transport in 57 countries and more than 1.000 cities around the world*.
SiBike - Green Light for Cyclists
The number of bike users is increasing every day. This means pressure on safety, and emerging bicycle traffic issues.
That’s why Siemens developed Sitraffic SiBike: the ‘green wave’ for cyclists. With the help of a smartphone application, cyclists are given priority at traffic lights. The cyclist’s smartphone determines its position via GPS and checks whether the bike has passed a specific trigger point at a predetermined speed. When the bike passes this point, the app sends a green-light request to traffic lights, helping those on bicycles to reach their destination faster.
Contagem debicicletas - Conheça os números
Siemens offers cities a clever solution for bicycle movements’ counting on cycle lanes (per direction). The bicycle counter poles count the passing cyclists and indicate the numbers via lane-side screens. The poles have a sensitizing and motivating effect because they show - almost literally - that cyclists also count. The data can be used for improvements to infrastructure and road engineering, giving insightful and real-time information for decision making and urban planning.
Artificial Intelligence to support decisions
The Data Analytics and Application Center (DAAC) support all customers analyzing data streams and identifying patterns and trends. Algorithm simulation to improve efficiency of any process and optimization of bicycle availability at docking stations are just one of the examples of real world applications powered by data analysis, improving the quality o the bike sharing service provided.
*Roland Berger (2016), Bike Sharing 4.0 - Study
