Advanced Optimization Method for Improving the Urban Traffic Management

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU118853" target="_blank" >RIV/00216305:26220/16:PU118853 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7561507" target="_blank" >https://ieeexplore.ieee.org/document/7561507</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/FRUCT-ISPIT.2016.7561507" target="_blank" >10.1109/FRUCT-ISPIT.2016.7561507</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Advanced Optimization Method for Improving the Urban Traffic Management

Popis výsledku v původním jazyce

The Smart City as a concept of future cities anticipates the smart and efficient traffic management. Current situation of traffic management did not offer a sufficient solution and it is not wise to use the current technology to improve the traffic situation on the city roads. This paper deals with advanced methods for optimization, the genetic algorithms, for using in urban traffic management. Implementation of genetic algorithm and also implementation of classical static solution were provided. We try to prove the advantages of modern optimization methods, which could bring more fluent traffic to the cities and solve the current challenges as i.e. high emissions, big delay, higher probability of accidents. The paper provides comparison measurements of static and dynamic solution in discrete time, discussion of the possible implementation in praxis and evaluation of the advantages and disadvantages for both methods.

Název v anglickém jazyce

Advanced Optimization Method for Improving the Urban Traffic Management

Popis výsledku anglicky

The Smart City as a concept of future cities anticipates the smart and efficient traffic management. Current situation of traffic management did not offer a sufficient solution and it is not wise to use the current technology to improve the traffic situation on the city roads. This paper deals with advanced methods for optimization, the genetic algorithms, for using in urban traffic management. Implementation of genetic algorithm and also implementation of classical static solution were provided. We try to prove the advantages of modern optimization methods, which could bring more fluent traffic to the cities and solve the current challenges as i.e. high emissions, big delay, higher probability of accidents. The paper provides comparison measurements of static and dynamic solution in discrete time, discussion of the possible implementation in praxis and evaluation of the advantages and disadvantages for both methods.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1401" target="_blank" >LO1401: Interdisciplinární výzkum bezdrátových technologií</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 18th FRUCT & ISPIT Conference, 18-22 April 2016, Technopark of ITMO University, Saint-Petersburg, Russia. FRUCT Oy, Finland.

ISBN

978-952-68397-3-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

48-53

Název nakladatele

Neuveden

Místo vydání

St. Petersburg

Místo konání akce

St. Petersburg

Datum konání akce

18. 4. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000389208900008