This project was co-financed with state support of the CR Technological Agency as part of Programu aplikovaného výzkumu a experimentálního vývoje ALFA
www.tacr.cz
Research useful for society.

Project detail

Verification of the implementation of continuous traffic load map using modern classification and prediction methods

Duration: 01.01.2012 — 31.12.2014

Funding resources

Technologická agentura ČR - Program aplikovaného výzkumu a experimentálního vývoje ALFA

- whole funder (2012-01-01 - 2014-12-31)

On the project

Cílem projektu je vytvořit parametrizovatelnou softwarovou aplikaci, která umožní na komunikacích v městských aglomeracích stanovit parametry dopravního proudu v místech neosazených detektory dopravy.

Description in English
The aim of the project is to create a parameterizable software application that determines the parameters of traffic flow in areas that are not equipped with traffic detectors on the roads in urban areas.

Keywords
zátěžová mapa; softwarová aplikace; model; dopravní proud; predikce;umělá inteligence

Key words in English
traffic load map; software application; model; traffic flow; prediction; artfical intelligence

Mark

TA02030915

Default language

Czech

People responsible

Koplík Karel, Ing. - fellow researcher
Fučík Otto, doc. Dr. Ing. - principal person responsible

Units

Department of Computer Systems
- responsible department (2011-11-08 - 2014-12-31)
Faculty of Information Technology
- co-beneficiary (2011-11-08 - 2014-12-31)

Results

KADLČEK, F.; FUČÍK, O. Fast and Energy Efficient AdaBoost Classifier. FPGAWorld'13. Copenhagen and Stockholm: Association for Computing Machinery, 2013. p. 1-5. ISBN: 978-1-4503-2496-0.
Detail

PETRLÍK, J.; FUČÍK, O.; SEKANINA, L. Multiobjective Selection of Input Sensors for Travel Times Forecasting Using Support Vector Regression. In 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems Proceedings. Piscataway: Institute of Electrical and Electronics Engineers, 2014. p. 14-21. ISBN: 978-1-4799-4498-9.
Detail

PETRLÍK, J.; FUČÍK, O.; SEKANINA, L. Multiobjective Selection of Input Sensors for SVR Applied to Road Traffic Prediction. In Parallel Problem Solving from Nature - PPSN XIII. Lecture Notes in Computer Science. Heidelberg: Springer Verlag, 2014. p. 802-811. ISBN: 978-3-319-10761-5.
Detail

Responsibility: Fučík Otto, doc. Dr. Ing.