Assessment of connected and autonomous vehicles impacts on traffic flow through microsimulation.
Autonomous and Connected Vehicles (CAVs) are an essential part of the future of intelligent roads around the world. They are an object of interest to the world traffic authorities and society. They have great potential for improving traffic flow, reducing the number of accidents, increasing energy e...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | Brasil |
| Institución: | Universidade de São Paulo (USP) |
| Repositorio: | Biblioteca Digital de Teses e Dissertações da USP |
| Idioma: | inglés |
| OAI Identifier: | oai:teses.usp.br:tde-09032021-090209 |
| Acceso en línea: | https://www.teses.usp.br/teses/disponiveis/3/3142/tde-09032021-090209/ |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous heterogeneous traffic Autonomous vehicles Comboios automatizados Connected and autonomous vehicles Microssimulação de tráfego Platooning Tráfego autônomo heterogêneo Traffic microsimulation Veículos autônomos |
| Sumario: | Autonomous and Connected Vehicles (CAVs) are an essential part of the future of intelligent roads around the world. They are an object of interest to the world traffic authorities and society. They have great potential for improving traffic flow, reducing the number of accidents, increasing energy efficiency, and reducing emission levels. Industry and academia have increased their efforts and investments to develop the various technologies that will integrate the CAV and assess its impact on the roads. The transition phases are more complicated due to the coexistence of autonomous and non-autonomous vehicles on the same path and need to be carefully evaluated. This dissertation\'s main objective is to develop a methodology to assess the impact of CAVs on traffic flow on urban and highway roads. The study also includes the transition phases that include mixed human-driven vehicle traffic (HDVs), autonomous vehicles (AVs),and autonomous and connected vehicles. The research evaluated how these technologies affect travel times in the presence of disturbances and the impact of automated trains\' functionfor all scenarios within urban or road environments. The study was carried out employing traffic microsimulation using the PTV VISSIM software, where the car-following models were developed and calibrated. The results showed that scenarios with 100% CAVs combined with optimal train size settings led to a reduction of up to 71% in travel times in urban applications and 43% in road applications than scenarios where humans drove 100% of vehicles. The study also shows a specific assessment platooning applied to cities and highways. In general, the platoons can place an essential role in minimizing travel time. Finally, studies have shown that the impacts measured on traffic performance can vary significantly, depending on the network\'s characteristics and the configuration of the capacity of the CAVs. The convergent point is that they have positive impacts. |
|---|