946 research outputs found

    Optimal Fleet Sizing of Personal Rapid Transit System

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    Part 5: Modelling and Optimization; International audience; In this paper, we address the problem of determining the optimal fleet size for Personal Rapid Transit system (PRT). In our problem, we consider electric battery and distance constraints which are found in real world application of the PRT system. To tackle this problem, we propose two valid mathematical formulations that are able to find optimal fleet size. Extensive computational experiments show that the edge based formulation performs impressively well, in terms of solution quality and computational time in comparison to the node based formulation. Document type: Part of book or chapter of boo

    Optimization of Electric-Vehicle Charging: scheduling and planning problems

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    The progressive shift from traditional vehicles to Electric Vehicles (EVs ) is considered one of the key measures to achieve the objective of a significant reduction in the emission of pollutants, especially in urban areas. EVs will be widely used in a not-so-futuristic vision, and new technologies will be present for charging stations, batteries, and vehicles. The number of EVs and Charging Stations (CSs) is increased in the last years, but, unfortunately, wide usage of EVs may cause technical problems to the electrical grid (i.e., instability due to intermittent distributed loads), inefficiencies in the charging process (i.e., lower power capacity and longer recharging times), long queues and bad use of CSs. Moreover, it is necessary to plan the CSs installation over the territory, the schedule of vehicles, and the optimal use of CSs. This thesis focuses on applying optimization methods and approaches to energy systems in which EVs are present, with specific reference to planning and scheduling decision problems. In particular, in smart grids, energy production, and storage systems are usually scheduled by an Energy Management System (EMS) to minimize costs, power losses, and CO2 emissions while satisfying energy demands. When CSs are connected to a smart grid, EVs served by CSs represent an additional load to the power system to be satisfied, and an additional storage system in the case of vehicle-to-grid (V2G) technology is enabled. However, the load generated by EVs is deferrable. It can be thought of as a process in which machines (CSs) serve customers/products (EVs) based on release time, due date, deadline, and energy request, as happens in manufacturing systems. In this thesis, first, attention is focused on defining a discrete-time optimization problem in which fossil fuel production plants, storage systems, and renewables are considered to satisfy the grid's electrical load. The discrete-time formalization can use forecasting for renewables and loads without data elaboration. On the other side, many decision variables are present, making the optimization problem hard to solve through commercial optimization tools. For this reason, an alternative method for the optimal schedule of EVs characterized by a discrete event formalization is presented. This new approach can diminish the number of variables by considering the time intervals as variables themselves. Of course, the solution's optimality is not guaranteed since some assumptions are necessary. Moreover, the last chapter proposes a novel approach for the optimal location and line assignment for electric bus charging stations. In particular, the model provides the siting and sizing of some CSs to maintain a minimum service frequency over public transportation lines

    Estimación del impacto ambiental y social de los nuevos servicios de movilidad

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    El transporte es fuente de numerosas externalidades negativas, como los accidentes de tráfico, la congestión en las zonas urbanas y la falta de calidad del aire. El transporte también es un sector que contribuye sustancialmente a la crisis climática con más del 16% de las emisiones globales de gases de efecto invernadero como resultado de las actividades de transporte. Muchos creen que la introducción de nuevos servicios de movilidad podría ayudar a reducir esas externalidades. Sin embargo, con cada introducción de un nuevo servicio de movilidad podemos observar factores que podrían contribuir negativamente a la sostenibilidad del sistema de transporte: una cadena de cambios de comportamiento causados por la introducción de posibilidades completamente nuevas. El objetivo de esta tesis es investigar cómo los nuevos servicios de movilidad, habilitados por la electrificación, la conectividad y la automatización, podrían impactar en las externalidades causadas por el transporte. En particular, el objetivo es desarrollar y validar un marco de modelado capaz de capturar la complejidad del sistema de transporte y aplicarlo para evaluar el impacto potencial de los vehículos automatizados.Transport is a source of numerous negative externalities, such as road accidents, congestion in urban areas and lacking air quality. Transport is also a sector substantially contributing to climate crisis with more than 16% of global greenhouse gas emissions being a result of transport activities. Many believe that the introduction of new mobility services could help reduce those externalities. However, with each introduction of a new mobility service we can observe factors that could negatively contribute to the sustainability of the transport system – a chain of behavioural changes caused by introduction of entirely new possibilities. The aim of this thesis is to investigate how the new mobility services, enabled by electrification, connectivity and automation, could impact the externalities caused by transport. In particular the objective is to develop and validate a modelling framework able to capture the complexity of the transport system and to apply it to assess the potential impact of automated vehicles.This work was realised with the collaboration of the European Commission Joint Research Centre under the Collaborative Doctoral Partnership Agreement N035297. Moreover, this research has been partially funded by the Spanish Ministry of Science and Innovation through the project: AUTONOMOUS – InnovAtive Urban and Transport planning tOols for the implementation of New mObility systeMs based On aUtonomouS driving”, 2020-2023, ERDF (EU) (PID2019-110355RB-I00)

    Assessing Potential Energy Savings in Household Travel: Methodological and Empirical Considerations of Vehicle Capability Constraints and Multi-day Activity Patterns.

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    The lack of multi-day data for household travel and vehicle capability requirements is an impediment to evaluations of energy savings strategies, since 1) travel requirements vary from day-to-day, and 2) energy-saving transportation options often have reduced capability. This work demonstrates a survey methodology and modeling system for evaluating the energy-savings potential of household travel, considering multi-day travel requirements and capability constraints imposed by the available transportation resources. A stochastic scheduling model is introduced – the multi-day Household Activity Schedule Estimator (mPHASE) – which generates synthetic daily schedules based on “fuzzy” descriptions of activity characteristics using a finite-element representation of activity flexibility, coordination among household members, and scheduling conflict resolution. Results of a thirty-household pilot study are presented in which responses to an interactive computer assisted personal interview were used as inputs to the mPHASE model in order to illustrate the feasibility of generating complex, realistic multi-day household schedules. Study vehicles were equipped with digital cameras and GPS data acquisition equipment to validate the model results. The synthetically generated schedules captured an average of 60 percent of household travel distance, and exhibited many of the characteristics of complex household travel, including day-to-day travel variation, and schedule coordination among household members. Future advances in the methodology may improve the model results, such as encouraging more detailed and accurate responses by providing a selection of generated schedules during the interview. Finally, the Constraints-based Transportation Resource Assignment Model (CTRAM) is introduced. Using an enumerative optimization approach, CTRAM determines the energy-minimizing vehicle-to-trip assignment decisions, considering trip schedules, occupancy, and vehicle capability. Designed to accept either actual or synthetic schedules, results of an application of the optimization model to the 2001 and 2009 National Household Travel Survey data show that U.S. households can reduce energy use by 10 percent, on average, by modifying the assignment of existing vehicles to trips. Households in 2009 show a higher tendency to assign vehicles optimally than in 2001, and multi-vehicle households with diverse fleets have greater savings potential, indicating that fleet modification strategies may be effective, particularly under higher energy price conditions.Ph.D.Natural Resources and EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91567/1/kevinb_1.pd

    A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions

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    Why should you read another book about transport and land use? This book differs in that we won’t focus on empirical arguments – we present political arguments. We argue the political aspects of transport policy shouldn’t be assumed away or treated as a nuisance. Political choices are the core reasons our cities look and function the way they do. There is no original sin that we can undo that will lead to utopian visions of urban life. The book begins by introducing and expanding on the idea of Accessibility. Then we proceed through several major parts: Infrastructure Preservation, Network Expansion, Cities, and Institutions. Infrastructure preservation concerns the relatively short-run issues of how to maintain and operate the existing surface transport system (roads and transit). Network expansion in contrast is a long-run problem, how to enlarge the network, or rather, why enlarging the network is now so difficult. Cities examines how we organize, regulate, and expand our cities to address the failures of transport policy, and falls into the time-frame of the very long-run, as property rights and land uses are often stickier than the concrete of the network is durable. In the part on Institutions we consider things that might at first blush appear to be short-run and malleable, are in fact very long-run. Institutions seem to outlast the infrastructure they manage. Many of the transport and land use problems we want to solve already have technical solutions. What these problems don’t have, and what we hope to contribute, are political solutions. We expect the audience for this book to be practitioners, planners, engineers, advocates, urbanists, students of transport, and fellow academics

    Future Transportation

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    Greenhouse gas (GHG) emissions associated with transportation activities account for approximately 20 percent of all carbon dioxide (co2) emissions globally, making the transportation sector a major contributor to the current global warming. This book focuses on the latest advances in technologies aiming at the sustainable future transportation of people and goods. A reduction in burning fossil fuel and technological transitions are the main approaches toward sustainable future transportation. Particular attention is given to automobile technological transitions, bike sharing systems, supply chain digitalization, and transport performance monitoring and optimization, among others

    From Structures to Services. The Path toBetter Infrastructure in Latin America and the Caribbean

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    To close its infrastructure gap, Latin America and the Caribbean needs more than investment in new structures. It needs to become more efficient at investing in infrastructure and regulating a new range of services that have the potential to disrupt the energy, transport, and water sectors. The technological revolution makes a future with quality services possible, but not inevitable. This book offers policy options for countries to improve the access, quality, and affordability of services today, to ensure that they will be sustainable in the future, and to harness emerging technological advances for the benefit of all. This report aims to provoke discussion and further research on those many important issues and mark a path that helps the region move from structures to services and improve infrastructure for all

    Energy, sustainability and communities : assessing the potential for community energy planning in British Columbia

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    Analysis of the demand for energy services has traditionally focused on efficiency improvements to buildings and equipment. Yet, energy consumption patterns are also influenced by urban infrastructure characteristics which are largely under the control of municipal government.Community energy planning (CEP) is an integrative process that aims to jointly address energy,sustainability and community planning objectives. It is currently in its infancy as a planningprocess. To move from the realm of concept to that of practice , it is necessary to answer three questions: what is CEP? ; why should we do it?; and how do we do it?This study develops the concept of CEP into four policy packages designed to influence urban land use planning, transportation management, site and building design, and the use of alternative energy supplies . The " why" ofCEP must be answered at two levels: at the community level in order to motivate local action; and at a more aggregate level in order to motivate major policy shifts. In this study, the benefits to communities are demonstrated through a series of four casestudies which compare two alternative scenarios of development over a fifteen year time frame.Demonstrating the benefits at a more aggregate level is difficult , given the diversity of communities . By focusing on a single component of CEP, namely urban land use planning, it was possible to develop a heuristic for illustrating the benefits of CEP at the provincial level. The "how" of CEP is also examined at two levels: a conceptual level , to identify major legal, technical, economic and social issues ; and a practical level, to develop, through a case study, an understanding of some real-world problems and solutions . As CEP requires the involvement of municipal government in an area-not traditionally considered municipal jurisdiction, the specificlegal authority for municipal action with respect to CEP is examined.The results of the study analyses suggest that communities can achieve energy and cost savings of 15 to 30% and energy-related emission reductions of 30 to 45%. Investments in the energy sector tend to produce two to three times more jobs in the local economy in a CEP approach versus a business-as-usual approach. At an aggregate level, land use planning reform alone is estimated to produce carbon dioxide emission reductions of 17% at cost savings of 20%. Savings per tonne ofabatement are in excess of $600 . These results are relatively insensitive to substantial changes in the underlying assumptions, suggesting that uncertainty is not a significant factor in interpreting the results . The study suggests that the greatest benefits will be realized by bringing very low density urban areas up to more moderate densities through selective redevelopment.The implications of these results for municipalities and regions , the province , and the energy utilities are presented, along with suggestions for further study

    Data-driven Methodologies and Applications in Urban Mobility

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    The world is urbanizing at an unprecedented rate where urbanization goes from 39% in 1980 to 58% in 2019 (World Bank, 2019). This poses more and more transportation demand and pressure on the already at or over-capacity old transport infrastructure, especially in urban areas. Along the same timeline, more data generated as a byproduct of daily activity are being collected via the advancement of the internet of things, and computers are getting more and more powerful. These are shown by the statistics such as 90% of the world’s data is generated within the last two years and IBM’s computer is now processing at the speed of 120,000 GPS points per second. Thus, this dissertation discusses the challenges and opportunities arising from the growing demand for urban mobility, particularly in cities with outdated infrastructure, and how to capitalize on the unprecedented growth in data in solving these problems by ways of data-driven transportation-specific methodologies. The dissertation identifies three primary challenges and/or opportunities, which are (1) optimally locating dynamic wireless charging to promote the adoption of electric vehicles, (2) predicting dynamic traffic state using an enormously large dataset of taxi trips, and (3) improving the ride-hailing system with carpooling, smart dispatching, and preemptive repositioning. The dissertation presents potential solutions/methodologies that have become available only recently thanks to the extraordinary growth of data and computers with explosive power, and these methodologies are (1) bi-level optimization planning frameworks for locating dynamic wireless charging facilities, (2) Traffic Graph Convolutional Network for dynamic urban traffic state estimation, and (3) Graph Matching and Reinforcement Learning for the operation and management of mixed autonomous electric taxi fleets. These methodologies are then carefully calibrated, methodically scrutinized under various performance metrics and procedures, and validated with previous research and ground truth data, which is gathered directly from the real world. In order to bridge the gap between scientific discoveries and practical applications, the three methodologies are applied to the case study of (1) Montgomery County, MD, (2) the City of New York, and (3) the City of Chicago and from which, real-world implementation are suggested. This dissertation’s contribution via the provided methodologies, along with the continual increase in data, have the potential to significantly benefit urban mobility and work toward a sustainable transportation system
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