AN ADAPTABLE MATHEMATICAL MODEL FOR INTEGRATED NAVIGATION SYSTEMS

The project has been directed towards improving the accuracy and safety of marine navigation and ship handling, whilst contributing to reduced manning and improved fuel costs. Thus, the aim of the work was to investigate, design and develop an adaptable mathematical model that could be used in an integrated navigation system (INS) and an automatic collision avoidance system (ACAS) for use in marine vehicles. A general overview of automatic navigation is undertaken and consideration is given to the use of microprocessors on the bridge. Many of these systems now require the use of mathematical models to predict the vessels' manoeuvring characteristics: The different types and forms of models have been investigated and the derivation of their hydrodynamic coefficients is discussed in detail. The model required for an ACAS should be both accurate and adaptable, hence, extensive simulations were undertaken to evaluate the suitability of each model type. The modular model was found to have the most adaptable structure. All the modular components of this model were considered in detail to improve its adaptability, the number of non-linear terms in the hull module being reduced. A novel application, using the circulation theory to model the propeller forces and moments, allows the model to be more flexible compared to using traditional B-series four-quadrant propeller design charts. A new formula has been derived for predicting the sway and yaw components due to the propeller paddle wheel effect which gives a good degree of accuracy when comparing simulated and actual ship data, resulting in a mean positional error of less than 7%. As a consequence of this work, it is now possible for an ACAS to incorporate a ship mathematical model which produces realistic manoeuvring characteristics. Thus, the study will help to contribute to safety at sea.Kelvin Hughes Lt

Will automated vehicles negatively impact traffic flow?

With low-level vehicle automation already available, there is a necessity to estimate its effects on traffic flow, especially if these could be negative. A long gradual transition will occur from manual driving to automated driving, in which many yet unknown traffic flow dynamics will be present. These effects have the potential to increasingly aid or cripple current road networks. In this contribution, we investigate these effects using an empirically calibrated and validated simulation experiment, backed up with findings from literature. We found that low-level automated vehicles in mixed traffic will initially have a small negative effect on traffic flow and road capacities. The experiment further showed that any improvement in traffic flow will only be seen at penetration rates above 70%. Also, the capacity drop appeared to be slightly higher with the presence of low-level automated vehicles. The experiment further investigated the effect of bottleneck severity and truck shares on traffic flow. Improvements to current traffic models are recommended and should include a greater detail and understanding of driver-vehicle interaction, both in conventional and in mixed traffic flow. Further research into behavioural shifts in driving is also recommended due to limited data and knowledge of these dynamics. Document type: Articl

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

An institutional deployment framework for intelligent transportation systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.Includes bibliographical references (p. 163-177).Increasing traffic congestion around the world is limiting urban mobility and contributing to unsustainable environmental, economic, and social conditions. The concept of intelligent transportation systems (ITS), which is defined as the application of computing and electronics technologies to transportation, offers potential for alleviating the negative effects of traffic congestion. These negative effects include impacts on road efficiency, the environment, safety, and cost. Institutional obstacles, however, limit ITS deployment. This thesis presents a portfolio of ITS technologies that are relevant in combating congestion. Technologies studied include Advanced Traffic Management Systems (ATMS), Advanced Traveler Information Systems (ATIS), Advanced Public Transportation Systems (APTS), Advanced Vehicle Control Systems (AVCS), and many others. Each technology is analyzed on the basis of benefits and costs, real world examples, barriers to implementation, and social implications. From this portfolio, an institutional deployment framework for ITS is developed based on the barriers to implementation shared by many of these technologies. This framework addresses political, economic, organizational, financial, legal, and information issues. After developing this framework, it is applied to ITS institutions in the cities of Singapore and Kuala Lumpur, Malaysia. Three conclusions can be drawn from this comparison. First, ITS can make significant impacts on congestion, efficiency, safety, and the environment. At the same time, one must consider the social implications and costs of deployment. Second, deploying ITS in urban areas is a complex challenge, requiring the consideration of a wide range of factors. Finally, implementation of ITS must be specific to a particular region; the imitation of other cities without localized planning may result in unsuccessful deployments.by Sandi Shih Lin.S.M

Modeling the relationship between air quality and intelligent transportation system (ITS) with artificial neural networks.

Environmental or air quality impacts of Intelligent Transportation Systems (ITS) are very difficult to measure. Some researchers have attempted to quantify the effects of individual ITS application on emissions; yet, the effects of ITS as a whole on ambient air quality have not been investigated. The objective of this research was to model the relationship between ITS and ambient air quality. The multiple Artificial Neural Networks (ANN) training with the data yielded a model for predicting the air quality. In addition, the ANN made the measurement of the effect of ITS on air quality possible. Data pertaining to sixty US cities (urbanized area) were used for this research. Input variables used were related to transportation and local characteristics, and ITS applications. Output variables were the annual average concentrations of CO, Ozone, and N02 in ambient air. The K-fold cross validation technique was used to train the ANN. The results of ANN model were compared with that of a Multiple Regression (MR) model showing the supremacy of ANN over MR. The ANN model results show that the Mean Absolute Errors (MAEs) in prediction vary from 5 to 20 %. This variance is justified since the factors related with industries, which contribute significantly to air pollution, have not been taken into consideration in this study. There were some unusual findings: in contrast to the common assumptions, N02 concentration increases with ITS intensity, and Ground Level Ozone concentration, in ambient air, seemed to be more transportation-dependent as compared with that of CO and N02• A recommendation for further research on this topic is to include more input variables, especially those which are relatcd with industries, to improve the accuracy of prediction. Scientific experimentations have also been recommended to corroborate the unusual findings

The design of an intelligent decision support tool for submarine commanders

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 155-158).A recent search of headlines shows a high number of maritime collisions and accidents. The USS Hartford, a nuclear submarine, recently surfaced into an oil tanker just after the running aground of the USS Port Royal in Hawaii. Internationally, a French and British submarine collided in the Atlantic Ocean. The high frequency of these maritime accidents points to the need for a better decision support in ship and submarine navigation. Towards this end, this thesis proposes a mobile decision support tool to aid maritime commanders in maintaining situational awareness and aiding in navigation and collision avoidance. The Mobile Situational Awareness Tool (MSAT), specifically designed for submarine commanders but extensible to all maritime settings, provides mobile information for health and status monitoring and on-the-fly path planning capabilities. The functional and informational requirements for MSAT were identified through an in-depth analysis of submarine operations, specifically through a cognitive task analysis. The MSAT design incorporates a path planning algorithm that accounts for depth, land, visibility, and other contacts to propose the most efficient path from start to finish, especially useful for navigation in littoral regions. The MSAT also provides health and status monitoring capabilities, tracking many of the important systems across a submarine to provide information to the commander, as well as maintain high situational awareness. Human subject experiments showed that when compared to paper charts, the navigation tool in the MSAT performs significantly better with regards to both path length and the time it takes to plan a new path.(cont.) For health and status monitoring, a survey of current task times revealed potential savings by the MSAT by decreasing both the average and variability of task time. By reducing the number of physical movements needed by commanders through the use of a mobile tool, time is saved that can be used for task reallocation, or promote a change in task flow. There are many potential benefits for both the Navy and the commercial maritime community that the MSAT can provide. However, before the MSAT can become operational, there are some system implementation issues that must first be addressed. These range from an analysis of the hardware and software required, to the changes in training that might come from the addition of a new tool. Future work is needed in this area to help move forward so that the benefits can be realized across the maritime community.by Geoffrey P. Carrigan.S.M

2000 Transportation Scholars Conference: Compendium of Papers, 2000

Compendium of papers presented at the Transportation Scholars Conference in 2000