Summary of the project
Access to reliable and predictive information in real time allows users to make better mobility choices. To this end, Qucit is developing predictive engines that allow users to know in advance the availability of self-service bicycle systems (station by station). This encourages intermodality by providing reliable information to users when they plan their itinerary on the ViaNavigo tool of Ile-de-France Mobilités.
Summary of the project
Qucit also provides Keolis Bordeaux with the Qucit Bike API for the VCUB (self-service bicycle system in the Bordeaux metropolis). This predictive brick is integrated into La Bonne Station application and makes this mode of transport more reliable and attractive to users!
Summary of the project
Qucit also provides Keolis Dijon with the Qucit Bike API for the Vélodi (self-service bicycle system in the Dijon metropolitan area). This makes it possible to promote this mode of transport and make it attractive to users!
Summary of the project
The first in France: Instant System and Qucit have collaborated to integrate Qucit's artificial intelligence models into Modalis. BikePredict anticipates the availability of bicycles and places at each station in Bordeaux, La Rochelle and Pau. ParkPredict anticipates the time required to find a parking space and the level of traffic on existing car parks in Bordeaux. The predictive system converts journeys into more reliable and makes Modalis well-known in terms of intelligent route planners in France!
How is the prediction algorithm integrated into the calculator?
In order to encourage the use of public, soft and intermodal modes of transport, Instant System & Qucit rely on authentic information. It allows users to choose in advance the means of mobility that suits them best.