A meso-simulation approach for the estimation of traffic flows in presence of automated vehicles

n/

Path Following and Motion Control for Articulated Frame Steering Mobile Working Machine Using ROS2

Autonomous vehicles (AVs) have been studied and researched at least since the middle of 19s century, and the interest in these vehicles has grown in the last decade. There are many vehicle types with different steering techniques. Each is designed and manufactured depending on the need to perform specific tasks (for example, transporting passengers, transporting goods, and doing heavy duties like cutting trees, digging earth, and harvesting crops). This thesis highlights the autonomous articulated frame steering (AFS) heavy-duty mobile working machines and aims to address the problems of autonomizing the AFS machine with basic autonomy requirements, which makes the machine move without the need for human direct and indirect control. The working environment (like mines, forests, and construction sites), where heavy-duty machines are used to perform some tasks, requires an expert machine operator to drive it and control its manipulator, which increases the operator’s workload. However, due to the working environment’s limited area, the machine mostly has repetitive tasks that include following the same paths; therefore, we proposed implementing a path-following control system that could be used to help the operator by reducing the work amount. The proposed path following is based on controlling the vehicle’s position and orientation to match the desired positions and orientation on a specified path where the position’s lateral error and orientation error are minimized to zero while the vehicle follows the given path. The implemented control system is divided into many subsystems; each is responsible for a specific task, and to communicate between them we used the Robot Operating System ROS2. In this thesis, we are focusing on two of these subsystems. The first subsystem, called path following that, generates linear and angular velocities needed to make the machine follow the path. The other subsystem, called motion control, is responsible for converting the linear and angular velocities to machine commands (gear, steering, gas) and controls the machine’s acceleration and steering angle. The implemented path-following control system required understanding the machine’s kinematics and modeling the steering system. The implemented system is tested first using an AFS robot in a simulation environment, then tested on a real AFS heavy-duty machine owned by Tampere university. Moreover, the tests repeated for another path following based on the modified pure pursuit technique provided by ROS2 navigation for compression and evaluation purposes

Análise dos impactos de veículos autônomos em uma rodovia brasileira com simulação de tráfego

Esta dissertação versa sobre a análise dos impactos de veículos autônomos (autonomous vehicles, AVs) em tráfego misto rodoviário no Brasil. Veículos autônomos prometem mudar a maneira como o fluxo de tráfego se comporta, em termos de melhoraria da eficiência da corrente de tráfego, aumento da capacidade da via e redução de acidentes de trânsito. Por ser uma tecnologia nova no mercado, há muitas incertezas associadas ao comportamento e desempenho desses veículos nas vias. O contexto rodoviário brasileiro apresenta condições de tráfego não homogêneas e os motoristas comportam-se de maneira mais agressiva em relação a outros locais do mundo. Dessa forma, este trabalho busca avaliar os impactos de veículos autônomos, em tráfego misto, em uma rodovia brasileira de múltiplas faixas, usando simulação de tráfego. Também pretende: (i) analisar os impactos da inserção de veículos autônomos na frota convencional quanto ao desempenho operacional dos cenários estudados; (ii) avaliar a mudança no número de eventos que seriam considerados conflitos para veículos convencionais, que a inserção de veículos autônomos poderá gerar, com base em uma medida de desempenho de segurança substituta; e (iii) estimar a percentagem de penetração de veículos autônomos que é capaz de trazer benefícios significativos ao fluxo de tráfego da rodovia estudada. O estudo envolveu um projeto de experimentos para a definição dos cenários com diferentes taxas de penetração de veículos autônomos na frota, volumes de tráfego na rodovia e comportamentos do sistema autônomo.Os parâmetros comportamentais dos AVs foram baseados no projeto CoEXist. O VISSIM foi utilizado para avaliar tempo e atraso de viagem, velocidade, taxa de ocupação e número de mudanças de faixa na BR-290/RS. Realizou-se uma análise de variância (ANOVA) para compreender os impactos dos veículos autônomos no desempenho operacional da rodovia. Por fim, foi realizada uma análise do número de eventos que seriam considerados conflitos para a frota convencional no SSAM (Surrogate Safety Assessment Model).Os resultados para uma frota composta por 100% AVs indicaram uma redução de 96,1% no atraso de viagem, um aumento de até 83,7% na velocidade e 132,7% no número de mudanças de faixa e uma redução de até 92% do número de eventos que seriam considerados conflitos totais e por colisão traseira. Quanto ao desempenho da corrente de tráfego da rodovia, foram observadas melhorias a partir da introdução de 60% de AVs na frota convencional, provocando uma diminuição dos períodos de congestionamento e um aumento da eficiência do fluxo de tráfego.This work is about the analysis of the impacts of autonomous vehicles (AVs) in mixed road traffic in Brazil. Autonomous vehicles promise to change the way traffic flow behave in terms of improving traffic stream efficiency, increasing capacity and reducing traffic accidents. By being a new technology in the industry, there are many uncertainties associated with their behavior and performance on the roads. In Brazil, the traffic conditions are not homogeneous and the drivers are more agressive compared to other countries. Therefore, this work aims to evaluate the impacts of autonomous vehicles in mixed traffic on a Brazilian multilane highway, by using microsimulation. Other objectives are to (i) analyze the impacts of the inclusion of autonomous vehicles in the fleet for system performance measures; (ii) evaluate the changes in the number of events that would be considered conflicts for legacy fleet that autonomous vehicles could generate, based on a surrogate safety performance measure; and (iii) estimate the penetration rate of autonomous vehicles that can bring significant benefits to highway traffic flow. The study involved a design of experiments to create scenarios with different penetration rates of autonomous vehicles in the fleet, traffic flow and automated system behavior. The behavioral parameters of the autonomous vehicles were based on the CoEXist project. The VISSIM was used to evaluate travel time, delay, speed, occupancy and lane change on the BR-290/RS. An analysis of variance (ANOVA) was performed to understand the impacts of autonomous vehicles on highway performance. Finally, an analysis of the number of events that would be considered conflicts for legacy fleet in SSAM (Surrogate Safety Assessment Model) was made. The results for 100% AVs indicated a 96,1% reduction in delay, 83,7% increase in speed and 132,7% lane change and a 92% reduction in the number of events that would be considered conflicts and conflicts of rear end for legacy fleet. Regarding the performance of the traffic stream, improvements were observed from a penetration rate equal to 60% of AVs in the fleet, causing a reduction of congestion periods and na increase in traffic flow efficiency