Modelling Traffic Emissions Based on an Advanced Vehicle Detection
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F24%3APU152170" target="_blank" >RIV/00216305:26210/24:PU152170 - isvavai.cz</a>
Výsledek na webu
<a href="https://etul.publi.cz/book/5462-55-mezinarodni-vedecka-konference-zamerena-na-vyzkumne-a-vyukove-metody-v-oblasti-vozidel-a-jejich-pohonu" target="_blank" >https://etul.publi.cz/book/5462-55-mezinarodni-vedecka-konference-zamerena-na-vyzkumne-a-vyukove-metody-v-oblasti-vozidel-a-jejich-pohonu</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Modelling Traffic Emissions Based on an Advanced Vehicle Detection
Popis výsledku v původním jazyce
Air pollution from traffic emissions affects billions of people worldwide, yet measurements are very limited. Pollution concentrations in cities vary rapidly over short distances due to unevenly distributed emission sources, dilution and physicochemical transformations. Conventional monitoring methods lack the necessary resolution to characterise exposures and locate hotspots. Detailed, specific and up-todate data are crucial for in-depth analysis, modelling, management or planning. This paper explores and develops a widely applicable solution for real-time traffic pollutant estimation based on high-accuracy traffic dynamics data and microscopic multimodal emission models. A key aspect is the implementation of an advanced image processing method for vehicle detection and classification. Accurate vehicle trajectories together with terrain morphology are input to new micro-simulation models for the generation of exhaust and non-exhaust pollutants (CO2, NOX, PM).
Název v anglickém jazyce
Modelling Traffic Emissions Based on an Advanced Vehicle Detection
Popis výsledku anglicky
Air pollution from traffic emissions affects billions of people worldwide, yet measurements are very limited. Pollution concentrations in cities vary rapidly over short distances due to unevenly distributed emission sources, dilution and physicochemical transformations. Conventional monitoring methods lack the necessary resolution to characterise exposures and locate hotspots. Detailed, specific and up-todate data are crucial for in-depth analysis, modelling, management or planning. This paper explores and develops a widely applicable solution for real-time traffic pollutant estimation based on high-accuracy traffic dynamics data and microscopic multimodal emission models. A key aspect is the implementation of an advanced image processing method for vehicle detection and classification. Accurate vehicle trajectories together with terrain morphology are input to new micro-simulation models for the generation of exhaust and non-exhaust pollutants (CO2, NOX, PM).
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
20301 - Mechanical engineering
Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů