AI technology for online ridesharing

A smart ridesharing platform at a city-wide scale that allows the organization of short-distance trips with users' own private cars (without the participation of professional drivers), and could result in social, economic and environmental benefits for cities that deploy it.

Market need: The possibility of serving multiple passengers on a single trip at a city-wide scale is a very complex computational problem. Nowadays, ridesharing solutions cannot cope with the scale requirements of a city. This AI technology deals with this problem, focusing on scaling up ridesharing.

Proposed solution: The technology automatically assembles shared trips in real-time, being capable of coping with a large volume of travel requests and cars. The allocation of vehicles to passengers is done with the double objective of minimizing the distance to be travelled, then reducing costs, and of reducing the vehicle fleet.
The proposed system allows people to organize one-time trips on short notice with their private cars, and with no involvement of professional drivers.

Competitive advantages

A ridesharing application at large-scale that process in few seconds hundreds of travel requests from a large population of users.
Reduction of gas emissions, noise pollution and traffic congestion. Reduction of travel costs.
It can be integrated as a dashboard for the creation and evaluation of different ride-sharing scenarios.