Rur.ai - MaaS to the Rural Masses

Heat map of Lieksa, Finland for calculating bus stem routes
Existing bus routes in Lieksa
App UI
App UI
App UI

JUNCTION 2017 Mobility Track: Rural Mobility challenge

We created a MaaS service for rural ares. The service optimizes transport by combining autonomous vehicles and autonomous buses.

This post is an early-stage demo version.

The service

Key Solution: Stem route theory Highest population density areas and busiest traffic routes are combined to a same map (Image 1) to calculate Stem Routes that will function with quick intervals as the backbone of this new transport arrangement. The main problem is to get on-demand people-flow from the housing areas to the stem route.

Ideal situation Autonomous vehicle’s algorithm would take into consideration the following parameters: the distance (via road) between different coordinates, preferred waiting time of different customers, capacity of the car, upcoming connecting busses, predict over-demand during rush hours and guide the car to optimal location to stay idle, based on machine learning that gathers its’ data from trials such as our solution.