Development of Swarm Traffic Algorithms : Road detection within an ellipse ; Utveckling av Svärmtrafikalgoritmer : Vägdetektion inom en ellips ; Development of Swarm Traffic Algorithms: Road detection within an ellipse; Development of heat traffic algorithms: Road detection within an ellipse
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| Název: | Development of Swarm Traffic Algorithms : Road detection within an ellipse ; Utveckling av Svärmtrafikalgoritmer : Vägdetektion inom en ellips ; Development of Swarm Traffic Algorithms: Road detection within an ellipse; Development of heat traffic algorithms: Road detection within an ellipse |
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| Autoři: | Dal Mas, Massimiliano |
| Informace o vydavateli: | KTH, Skolan för elektroteknik och datavetenskap (EECS) |
| Rok vydání: | 2021 |
| Témata: | OpenSCENARIO, autonomous driving scenario representation, simulation infrastructure, automated driving systems, self-driving car project, Computer and Information Sciences, Data- och informationsvetenskap, info, museo |
| Popis: | The latest trends in autonomous vehicles research gave rise to the needs for specific tools to validate and test such systems. The estimations state that to consider an autonomous vehicle statistically safe, it should drive for thousands of kilometres using traditional validation methods. This process would take a long time. Furthermore, an update in the software, would require to re-run those kilometres. Therefore, the testing must be performed exploiting virtual simulations that should realistically reflect the real world. One way to perfor msuch simulations is to let the vehicle model drive down a road map and control the surrounding traffic. To be effective, spawned traffic should not be generated too far from the target vehicle. The OpenSCENARIO standard offers a feature restricting such traffic within an ellipse centred in the central object (target vehicle). This thesis investigated what technique was more efficient and scalable to detect viable roads within the ellipse to spawn stochastic traffic on. The explored solutions are two: an analytical approach and an adaptation of the AABB tree algorithm. The research started with simple cases and incremented the scenario’s complexity during the development. Through this methodology, each technique’s positive aspects and limits have been highlighted, allowing a comparison to be made. ; De senaste trenderna i autonoma fordon har ökat behovet av specifika verktyg för att validera och testa sådana system. För att kunna betrakta ett autonomt fordon som statistiskt säkert, ska enligt uppskattningar autonoma fordon köra tusentals kilometer med traditionella valideringsmetoder. Denna process skulle ta mycket lång tid. Dessutom skulle en uppdatering i mjukvaran kräva att alla dessa tusentals kilometer att körs igen. Därför måste testningen utföras med hjälp av virtuella simuleringar som bör efterlikna den reella världen realistiskt. Ett sätt att genomföra dessa simuleringar är att låta en autonom fordonsmodell köra genom ett vägnät och kontrollera kringliggande . |
| Druh dokumentu: | thesis |
| Jazyk: | English |
| Relation: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306729 |
| Dostupnost: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306729 |
| Rights: | undefined |
| Přístupové číslo: | edsbas.528BD208 |
| Databáze: | BASE |
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