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.

Sources and Data

Traffic data https://extranet.liikennevirasto.fi/webgis-sovellukset/webgis/template.html?config=liikenne

Population in Lieksa per square kilometer http://www.stat.fi/tup/rajapintapalvelut/vaestoruutuaineisto_1km.html

Population in Northern Karelia by age 2015 http://www.stat.fi/tup/kunnat/kuntatiedot/422.html

Google Maps APIs https://developers.google.com/maps/

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