From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table

Effectiveness of best management practices to increase infiltration in urban and rural environments

Source-control best management practices (BMPs) have been designed and promoted as flexible alternatives for runoff mitigation in both urban and agriculturally developed landscapes and are likely to become more important given climatic predictions of more frequent and intense rain events. Strategies that incorporate vegetative elements and natural soil water infiltration to reduce runoff delivered to conventional sewer or tile drainage systems and increase groundwater recharge are compatible with other characteristics of urban and agricultural landscapes. However, the rate of adoption of BMPs has been slow as a result of uncertainties about maintenance, effectiveness when incorporated during retrofitting, and long-term benefits that have been under studied. In the first part of this study I examined the efficacy of three common stormwater BMPs in a variety of urban (residential, recreational and commercial) environments. Specifically, I examined bioretention cells, native landscaping (restored prairie), and vegetated riparian buffer practices. In the second component of this study, I examined the similarities and differences in performance for a single BMP, vegetated riparian buffers, when used in both urban and rural landscapes. For both studies, I examined performance capacity based on the spatial extent of each BMP (receiving area) to its subwatershed (contributing area). I also conducted rainfall simulation to measure infiltration, absorption capacity, runoff characteristics and collected soil samples to characterize pollutant accumulation. Among the urban BMPs in the first study, bioretention cells and wooded zones of the buffers had the lowest soil bulk densities, highest infiltration rates, and smaller runoff volumes than did their contributing areas. In the second study, I observed that urban buffers, although generally smaller, had larger practice to contributing area ratios, indicating that spatial constraints may not diminish buffer effectiveness in these landscapes. Rural and urban buffers demonstrated analogous performance for buffer areas compared to their respective contributing areas. In both landscape settings the buffer areas had the highest infiltration rates and the wooded buffer zones demonstrated significantly greater time-to-runoff compared to their contributing areas. In both studies, I determined that the effectiveness of BMPs observed could be enhanced if their surface area was enlarged, or if they were implemented as clustered practices. Further, my findings suggest that while implementation of these practices is likely to reduce runoff volumes and improve water quality, their performance could be improved using site-specific practice designs rather than following more generic technical recommendations

PREDICTING CLIMATE-INDUCED IMPACTS ON SEASONAL STREAM TEMPERATURES IN THE CROWN OF THE CONTINENT ECOSYSTEM

Changes in seasonal climate patterns are altering thermal distributions of freshwater ecosystems worldwide. The Crown of the Continent Ecosystem is one of the most biologically diverse ecosystems in North America, spanning northwestern Montana, USA, Alberta and British Columbia, Canada. The fluvial landscape consists of pristine freshwater habitats that provide strongholds for many aquatic species. My dissertation work provides the first broad scale analysis of seasonal climate effects on spatiotemporal patterns of stream temperature in the Crown of the Continent, and a multi-scalar analysis of potential impacts to bull trout (Salvelinius confluentus) populations, the most stenothermic cold-water fish in the northern Rocky Mountains. Seasonal stream temperature models were developed to predict monthly temperatures under current and future climate scenarios. Future climate simulations forecast increasing stream temperatures during spring, summer, and fall, with the largest absolute increases predicted for July, August, and September and the largest increases relative to historic temperatures predicted for April and November. Results portend a temporal shift in seasonal stream temperatures, including an earlier onset and extended duration of warm summer stream temperatures. Stream temperature warming was most pronounced in high-elevation montane and alpine streams, where glacial-fed streams were predicted to experience the largest magnitude (\u3e50%) of change due to the loss of alpine glaciers. Thermal riverscapes were used to assess spatiotemporal shifts in habitat distributions of bull trout. Models predicted thermal preferences for juvenile bull trout within tributary habitats during the summer months \u3c 12°C, while preferred temperatures for sub-adult and adult bull trout within river habitats were \u3c 15°C. Future stream temperature warming is likely to result in a contraction of thermally optimal habitats, suggesting a shift in the distributional range of bull trout further north in latitudes and higher in elevation. Thermal sensitivities during the summer months are likely to be highest in the southern periphery of their distributional range, while model simulations under extreme climate scenarios predict headwater tributaries within the Oldman, Flathead, and South Fork Flathead basins to provide cold-water refugia into the future. My dissertation work provides a decision support framework for predicting climate-induced stream temperature impacts on freshwater riverscapes and sensitive aquatic species to prioritize climate adaptation strategies in the Crown of the Continent

Mapping infiltration in an urbanizing mixed-land-use watershed with multi-temporal satellite imagery

Digital soil mapping (DSM) is a field of soil science that aims to improve traditional soil maps by producing higher resolution predictive maps of soil properties using spatial environmental data. DSM has historically relied primarily on static environmental covariates—such as slope gradient, slope aspect, and other topographic variables derived from digital terrain models—for predicting static soil properties, like soil texture. Advancements in satellite imagery and statistical modeling improve the accuracy of digital soil maps by incorporating multi-temporal data that can capture landscape-scale change over relatively short periods of time. Adding these dynamic environmental covariates may be especially useful for spatial prediction of dynamic soil properties, like infiltration rate, that are strongly affected by phenomenon that satellite imagery can detect, like land use that changes rapidly due to human activity. Infiltration strongly impacts soil health and hydrologic characteristics in a watershed. Understanding infiltration for sustainable land management is vital for making best management decisions in urbanizing environments like the West Run Watershed in Morgantown, West Virginia. We hypothesized that infiltration could be predicted at a higher accuracy and a finer spatiotemporal scale using digital soil mapping techniques than is currently provided by the current official soil data and maps produced by the National Cooperative Soil Survey. Spatial predictions of infiltration rate were produced for the West Run watershed using both static and dynamic environmental covariates as inputs into multiple linear regression (MLR) and random forest (RF) models, each of which were made using 10-fold cross validation. Training and independent validation sampling locations were selected using a conditioned Latin hypercube sampling scheme and observed saturated hydraulic conductivity of the soil surface was collected using automated dual-head infiltrometers. The MLR and RF models had R 2 of 0.302 and 0.201, respectively. Validation sampling was stratified by the predicted infiltration values of the MLR model. Validation R 2 values for the MLR and RF models were 0.080 and 0.103. The results from this study will benefit the development of a dynamic soil survey and will improve hydrologic models in this and potentially other mixed-land-use watersheds

On Statistical QoS Provisioning for Smart Grid

Current power system is in the transition from traditional power grid to Smart Grid. A key advantage of Smart Grid is its integration of advanced communication technologies, which can provide real-time system-wide two-way information links. Since the communication system and power system are deeply coupled within the Smart Grid system, it makes Quality of Service (QoS) performance analysis much more complex than that in either system alone. In order to address this challenge, the effective rate theory is studied and extended in this thesis, where a new H transform based framework is proposed. Various scenarios are investigated using the new proposed effective rate framework, including both independent and correlated fading channels. With the effective rate as a connection between the communication system and the power system, an analysis of the power grid observability under communication constraints is performed. Case studies show that the effective rate provides a cross layer analytical framework within the communication system, while its statistical characterisation of the communication delay has the potential to be applied as a general coupling point between the communication system and the power system, especially when real-time applications are considered. Besides the theoretical QoS performance analysis within Smart Grid, a new Software Defined Smart Grid testbed is proposed in this thesis. This testbed provides a versatile evaluation and development environment for Smart Grid QoS performance studies. It exploits the Real Time Digital Simulator (RTDS) to emulate different power grid configurations and the Software Defined Radio (SDR) environment to implement the communication system. A data acquisition and actuator module is developed, which provides an emulation of various Intelligent Electronic Devices (IEDs). The implemented prototype demonstrates that the proposed testbed has the potential to evaluate real time Smart Grid applications such as real time voltage stability control

Minnesota Water Resources Conference

1 online resource (PDF)University of Minnesota. College of Continuing Educatio

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Water-Wise Cities and Sustainable Water Systems

Building water-wise cities is a pressing need nowadays in both developed and developing countries. This is mainly due to the limitation of the available water resources and aging infrastructure to meet the needs of adapting to social and environmental changes and for urban liveability. This is the first book to provide comprehensive insights into theoretical, systematic, and engineering aspects of water-wise cities with a broad coverage of global issues. The book aims to (1) provide a theoretical framework of water-wise cities and associated sustainable water systems including key concepts and principles, (2) provide a brand-new thinking on the design and management of sustainable urban water systems of various scales towards a paradigm shift under the resource and environmental constraints, and (3) provide a technological perspective with successful case studies of technology selection, integration, and optimization on the “fit-for-purpose” basis

Towards a National 3D Mapping Product for Great Britain

Knowing where something happens and where people are located can be critically important to understand issues ranging from climate change to road accidents, crime, schooling, transport and much more. To analyse these spatial problems, two-dimensional representations of the world, such as paper or digital maps, have traditionally been used. Geographic information systems (GIS) are the tools that enable capture, modelling, storage, retrieval, sharing, manipulation, analysis, and presentation of geographically referenced data. Three-dimensional geographic information (3D GI) is data that can represent real-world features as objects in 3D space. 3D GI offers additional functionality not possible in 2D, including analysing and querying volume, visibility, surface and sub-surface, and shadowing. This thesis contributes to the understanding of user requirements and other data related considerations in the production of 3D geographic information at a national level. The study promotes Ordnance Survey’s efforts in developing a 3D geographic product through: (1) identifying potential applications; (2) analysing existing 3D city modelling approaches; (3) eliciting and formalising user requirements; (4) developing metrics to describe the usefulness of 3D data and; (5) evaluating the commerciality of 3D GI. A review of current applications of 3D showed that visualisation dominated as the main use, allowing for better communication, and supporting decision-making processes. Reflecting this, an examination of existing 3D city models showed that, despite the varying modelling approaches, there was a general focus towards accurate and realistic geometric representation of the urban environment. Web-based questionnaires and semi-structured interviews revealed that while some applications (e.g. subsurface, photovoltaics, air and noise quality) lead the field with a high adoption of 3D, others were laggards due to organisational inertia (e.g. insurance, facilities management). Individuals expressed positive views on the use of 3D, but still struggled to justify the value and business case. Simple building geometry coupled with non-building thematic classes was perceived to be most useful by users. Several metrics were developed to quantify and compare the characteristics of thirty-three 3D datasets. Results showed that geometry-based metrics such as minimum feature length or Euler characteristic can be used to provide additional information as part of fitness-for-purpose evaluations. The metrics can also contribute to quality control during data production. An investigation into the commercial opportunities explored the economic value of 3D, the market size of 3D data in Great Britain, as well as proposed a number of opportunities within the wider business context of Ordnance Survey