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In this study, we investigated autonomous vessel obstacle avoidance using advanced techniques within the Guidance, Navigation, and Control (GNC) framework. We propose a Mixed Integer Linear Programming (MILP) based Guidance system for robust path planning avoiding static and dynamic obstacles. For Navigation, we suggest a multi-modal neural network for perception, demonstrating the identification of obstacle type, position, and orientation using imaging sensors. Additionally, the paper compares an error-based PID control strategy and a Model Predictive Control (MPC) scheme as well. This evaluation aids in better evaluating their performance and determining their applicability within the GNC scheme. We detail the implementation of these systems, present simulation results, and offer a performance evaluation using an experimental dataset. Our findings, analysed through qualitative discussion and quantitative performance indicators, contribute to advancements in autonomous navigation and the control strategies to achieve it., Transport Engineering and Logistics

The framework of an autonomous vessel is typically composed of three distinct and independent blocks known as the Guidance, Navigation and Control (GNC) system. This paper presents a combination of advanced complementary techniques in the different GNC subsystems to improve upon the current common practices/state of the art in obstacle avoidance. The novel Guidance system is based on Mixed Integer Linear Programming (MILP). This optimisation technique allows quick, robust path planning with the possibility for a variety of constraints. The feasibility of this method will be investigated with the goal of providing optimal path planning in the presence of static and dynamic obstacles during autonomous sailing operations. Within the Navigation System, a multi-modal neural network architecture is proposed for the perception branch to provide high-level situational awareness for collision avoidance purposes. The computer vision approach allows for the vessel type, position and orientation all to be extracted for encounters with both dynamic and static obstacles using only imaging sensors. Two Control methods are studied in the paper, an error-based PID control strategy as well as an MPC control scheme. These two techniques will be compared to evaluate the performance and reviewing the suitability for use within the specific GNC scheme and the generic application environment. This paper details the specific implementation of each system within the overall framework, presents simulation results of the path planner and control strategy, with a performance evaluation of the navigation system using an experimental dataset. The results obtained are analysed through qualitative discussion as well as quantitative performance indicators and key conclusions are consequently drawn., Transport Engineering and Logistics

INTRODUCTION: African, Caribbean and Black (ACB) communities are disproportionately infected by HIV in Ontario, Canada. They constitute only 5% of the population of Ontario yet account for 25% of new diagnoses of HIV. The aim of this study is to understand underlying factors that augment the HIV risk in ACB communities and to inform policy and practice in Ontario. METHODS AND ANALYSIS: We will conduct a cross-sectional study of first-generation and second-generation ACB adults aged 15-64 in Toronto (n=1000) and Ottawa (n=500) and collect data on sociodemographic information, sexual behaviours, substance use, blood donation, access and use of health services and HIV-related care. We will use dried blood spot testing to determine the incidence and prevalence of HIV infection among ACB people, and link participant data to administrative databases to investigate health service access and use. Factors associated with key outcomes (HIV infection, testing behaviours, knowledge about HIV transmission and acquisition, HIV vulnerability, access and use of health services) will be evaluated using generalised linear mixed models, adjusted for relevant covariates. ETHICS AND DISSEMINATION: This study has been reviewed and approved by the following Research Ethics Boards: Toronto Public Health, Ottawa Public Health, Laurentian University; the University of Ottawa and the University of Toronto. Our findings will be disseminated as community reports, fact sheets, digital stories, oral and poster presentations, peer-reviewed manuscripts and social media