Planning autonomous vehicles in the absence of speed lanes using an elastic strip

Planning of autonomous vehicles in the absence of speed lanes is a less-researched problem. However, it is an important step toward extending the possibility of autonomous vehicles to countries where speed lanes are not followed. The advantages of having nonlane-oriented traffic include larger traffic bandwidth and more overtaking, which are features that are highlighted when vehicles vary in terms of speed and size. In the most general case, the road would be filled with a complex grid of static obstacles and vehicles of varying speeds. The optimal travel plan consists of a set of maneuvers that enables a vehicle to avoid obstacles and to overtake vehicles in an optimal manner and, in turn, enable other vehicles to overtake. The desired characteristics of this planning scenario include near completeness and near optimality in real time with an unstructured environment, with vehicles essentially displaying a high degree of cooperation and enabling every possible(safe) overtaking procedure to be completed as soon as possible. Challenges addressed in this paper include a (fast) method for initial path generation using an elastic strip, (re-)defining the notion of completeness specific to the problem, and inducing the notion of cooperation in the elastic strip. Using this approach, vehicular behaviors of overtaking, cooperation, vehicle following,obstacle avoidance, etc., are demonstrated.

Computing journey start times with recurrent traffic conditions

n this study, the authors discuss the effective usage of technology to solve the problem of deciding on journey start times for recurrent traffic conditions. The developed algorithm guides the vehicles to travel on more reliable routes that are not easily prone to congestion or travel delays, ensures that the start time is as late as possible to avoid the traveller waiting too long at their destination and attempts to minimise the travel time. Experiments show that in order to be more certain of reaching their destination on time, a traveller has to leave early and correspondingly arrive early, resulting in a large waiting time. The application developed here asks the user to set this certainty factor as per the task in hand, and computes the best start time and route.

Joint importance of multistate systems

Importance measures in reliability engineering are used to identify weak areas of a system and signify the roles of components in either causing or contributing to proper functioning of the system. Traditional importance measures for multistate systems mainly concern reliability importance of an individual component and seldom consider the utility performance of the systems. This paper extends the joint importance concepts of two components from the binary system case to the multistate system case. A joint structural importance and a joint reliability importance are defined on the basis of the performance utility of the system. The joint structural importance measures the relationship of two components when the reliabilities of components are not available. The joint reliability importance is inferred when the reliabilities of the components are given. The properties of the importance measures are also investigated. A case study for an offshore electrical power generation system is given.

Application of neural network to hybrid systems with binary inputs

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

An integrated dynamic whole life costing analysis for air distribution systems

Air distribution systems are one of the major electrical energy consumers in air-conditioned commercial buildings which maintain comfortable indoor thermal environment and air quality by supplying specified amounts of treated air into different zones. The sizes of air distribution lines affect energy efficiency of the distribution systems. Equal friction and static regain are two well-known approaches for sizing the air distribution lines. Concerns to life cycle cost of the air distribution systems, T and IPS methods have been developed. Hitherto, all these methods are based on static design conditions. Therefore, dynamic performance of the system has not been yet addressed; whereas, the air distribution systems are mostly performed in dynamic rather than static conditions. Besides, none of the existing methods consider any aspects of thermal comfort and environmental impacts. This study attempts to investigate the existing methods for sizing of the air distribution systems and proposes a dynamic approach for size optimisation of the air distribution lines by taking into account optimisation criteria such as economic aspects, environmental impacts and technical performance. These criteria have been respectively addressed through whole life costing analysis, life cycle assessment and deviation from set-point temperature of different zones. Integration of these criteria into the TRNSYS software produces a novel dynamic optimisation approach for duct sizing. Due to the integration of different criteria into a well- known performance evaluation software, this approach could be easily adopted by designers in busy nature of design. Comparison of this integrated approach with the existing methods reveals that under the defined criteria, system performance is improved up to 15% compared to the existing methods. This approach is interpreted as a significant step forward reaching to the net zero emission building in future.

Integrating augmented reality with home systems

Augmented Reality systems overlay computer generated information onto a user's natural senses. Where this additional information is visual, the information is overlaid on the user's natural visual field of view through a head mounted (or “head-up”) display device. Integrated Home Systems provides a network that links every electrical device in the home which provides to a user both control and data transparency across the network.

Photovoltaic and solar-assisted ground-source heat pump systems

This review investigates the performance of photovoltaic and solar-assisted ground-source heat pumps in which solar heat is transferred to the ground to improve the coefficient of performance. A number of studies indicate that, for systems with adequately sized ground heat exchangers, the effect on system efficiency is small: about 1% improvement if the heat source is photovoltaic, a 1–2% decline if the source is solar thermal. With possible exceptions for systems in which the ground heat exchanger is undersized, or natural recharge from ground water is insufficient, solar thermal energy is better used for domestic hot water than to recharge ground heat. This appears particularly true outside the heating season, as although much of the heat extracted from the ground can be replaced, it seems to have little effect on the coefficient of performance. Any savings in electrical consumption that do result from an improved coefficient can easily be outweighed by an inefficient control system for the circulation pumps.

A dynamical systems framework for intermittent data assimilation

We consider the problem of discrete time filtering (intermittent data assimilation) for differential equation models and discuss methods for its numerical approximation. The focus is on methods based on ensemble/particle techniques and on the ensemble Kalman filter technique in particular. We summarize as well as extend recent work on continuous ensemble Kalman filter formulations, which provide a concise dynamical systems formulation of the combined dynamics-assimilation problem. Possible extensions to fully nonlinear ensemble/particle based filters are also outlined using the framework of optimal transportation theory.

Categorization and construction of rule based systems

Expert systems have been increasingly popular for commercial importance. A rule based system is a special type of an expert system, which consists of a set of ‘if-then‘ rules and can be applied as a decision support system in many areas such as healthcare, transportation and security. Rule based systems can be constructed based on both expert knowledge and data. This paper aims to introduce the theory of rule based systems especially on categorization and construction of such systems from a conceptual point of view. This paper also introduces rule based systems for classification tasks in detail.

Intersections of Jane Jacobs’ conditions for diversity and low-carbon urban systems: a look at four global cities

Countless cities are rapidly developing across the globe, pressing the need for clear urban planning and design recommendations geared towards sustainability. This article examines the intersections of Jane Jacobs’ four conditions for diversity with low-carbon and low-energy use urban systems in four cities around the world: Lyon (France), Chicago (United-States), Kolkata (India), and Singapore (Singapore). After reviewing Jacobs’ four conditions for diversity, we introduce the four cities and describe their historical development context. We then present a framework to study the cities along three dimensions: population and density, infrastructure development/use, and climate and landscape. These cities differ in many respects and their analysis is instructive for many other cities around the globe. Jacobs’ conditions are present in all of them, manifested in different ways and to varying degrees. Overall we find that the adoption of Jacobs' conditions seems to align well with concepts of low-carbon urban systems, with their focus on walkability, transit-oriented design, and more efficient land use (i.e., smaller unit sizes). Transportation sector emissions seems to demonstrate a stronger influence from the presence of Jacobs' conditions, while the link was less pronounced in the building sector. Kolkata, a low-income, developing world city, seems to possess many of Jacobs' conditions, while exhibiting low per capita emissions - maintaining both of these during its economic expansion will take careful consideration. Greenhouse gas mitigation, however, is inherently an in situ problem and the first task must therefore be to gain local knowledge of an area before developing strategies to lower its carbon footprint.

Exploring smart grid possibilities: a complex systems modelling approach

Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders.