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SOM SIGNED

Statistical modeling for Optimization Mobility

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "SOM" data sheet

The following table provides information about the project.

Coordinator
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE 

Organization address
address: DOMAINE DE VOLUCEAU ROCQUENCOURT
city: LE CHESNAY CEDEX
postcode: 78153
website: www.inria.fr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 149˙109 €
 EC max contribution 149˙109 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-PoC
 Funding Scheme ERC-POC
 Starting year 2016
 Duration (year-month-day) from 2016-10-01   to  2018-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) coordinator 149˙109.00

Map

 Project objective

This project will commercialize software and internet services for improving mobility-related online services such a ride sharing, navigation systems and crowdsourcing. In particular, we will commercialize an app for mobile devices which makes predictions on the future travel intentions of the user based on the rich data available on the device through the use of highly efficient predictive modeling techniques. Based on these predictions, the mobile device can communicate in the background on ride sharing, crowdsourcing and congestion avoidance. Three key competitive advantages are (1) the privacy one gets in contrast with most cloud-based platforms where all data is centrally collected, (2) the saving of computational costs by distributing computations to devices having much more detailed information than what one can centrally collect, and (3) the fact that most services work with current traffic information, while we work with future travel intentions, allowing for planning better ahead. The commercialization of this technology will be realized by improving the existing network of potential industrial partners and end-users, demonstrating the technology for key services, exploring alternative commercialization strategies, and preparing a team to carry on the exploitation. When successful, this project will have lead to significant economic and societal benefits in improving the efficiency of crowdsourcing and ride sharing, increasing the popularity of ride sharing and reducing congestions.

 Publications

year authors and title journal last update
List of publications.
2017 Jan Ramon
Exploiting traffic data
published pages: , ISSN: , DOI:
INRIA Meetup 2019-06-13
2017 Jan Ramon
Invited talk: Learning from partly observable time- dependent graphs
published pages: , ISSN: , DOI:
ECML/PKDD 2017 workshop on large scale time dependent graphs 2019-06-13

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The information about "SOM" are provided by the European Opendata Portal: CORDIS opendata.

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