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Algoritmo de software para predicción del tráfico y guía de rutas en tiempo real

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOSG20150903001
Publicado:
14/09/2015
Caducidad:
13/09/2016
Resumen:
Una universidad de Singapur ha desarrollado una tecnología para predecir las condiciones futuras del tráfico en redes de carreteras a gran escala y en tiempo real que ofrece una guía de rutas predictiva a los usuarios. La tecnología permite reducir la duración del viaje, el consumo de combustible y molestias al conductor, mejorando la productividad. Los usuarios también pueden intercambiar información sobre el tráfico con otras personas mediante aplicaciones de redes sociales. Se buscan socios con el fin de establecer acuerdos de licencia, investigación o cooperación técnica.

Details

Tittle:
Real-time traffic prediction -Y- route guidance software algorithm
Summary:
The technology offered by a Singapore university can predict future traffic conditions of large scale road networks in real-time and provides predictive route guidance to users. In this way, the technology promises to reduce the driver´s travel time, fuel consumption and discomfort, and improve the overall productivity.

The type of partnerships that the university is seeking can be in the form of licensing, research cooperation or technical cooperation.
Description:
The Singapore university offers a diverse range of courses but also has specialisation in technology research. The real-time traffic prediction and route guidance technology was developed by the university as a result of its research in this area.

Traffic congestion introduces delay, impacts the driver comfort and satisfaction, increases pollution and noise at congestion sites and significantly reduces the productivity of the city.

Traffic states of the large-scale networks can be predicted in real-time by deploying the compressed prediction method (a patent pending proprietary method). Compressed prediction is a fast and scalable algorithm that enables real-time traffic prediction across multiple time horizons for large road networks. Route Guidance is implemented on top of the traffic prediction, giving optimal route based on future traffic conditions.

The deliverable solution for individual users is in the form of smartphone application giving users real-time traffic information in Geographic Information System (GIS) context. Users will also be able to share traffic information with others using social networking apps. Crowdsourcing is also used to further improve the predictions accuracy route reliability.

The university is open to any of the following types of partnerships:
- Licensing of the technology
- Cooperation to further undertaken research and development as a joint effort with the partner
- Technical cooperation

The nature of business of the partner can be a commercial or government cooperation who can implement this technology to address challenges in road traffic management.
Advantages and Innovations:
It has been shown that efficient routing brings about a reduction in travel time (up to 14%), fuel consumption (up to 7.8%) and variability of travel times (up to 50%). Hence real-time network estimation and multi-horizon predictions are necessary for efficient utilization of network infrastructure.

This technology helps individual car owners, commuters, taxi companies and delivery vans to avoid traffic congestion by informing them and providing them alternate routes to optimise their commuting times. It also enables public sector companies to manage roads and infrastructure better.

Commonly deployed prediction methods in the market such as support vector regression and neural networks achieve good performance by explicitly predicting the traffic variables like speed and volume at each road segment in the network. However, these common methods are inadequate when it comes to real-time prediction of large traffic network. The advantage and innovation of this solution is its use of a novel patent pending compressed prediction method to provide real-time prediction of large traffic networks and at the same time greatly reducing the computational load.
Stage of Development:
Available for demonstration
IPs:
Patent(s) applied for but not yet granted

Partner sought

Type and Role of Partner Sought:
The proposed partner could be a commercial or government cooperation that can adopt this technology to address challenges in road traffic management.

The university is open to the following types of partnerships:

- Licensing of the technology
- Research cooperation agreement to jointly carry out R-Y-D with the Singapore university
- Technical cooperation agreement

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English

Keywords

Technology Keywords:
08002001 Métodos de análisis y detección
02008005 Road Transport
02010003 Sistemas y transporte