An Optimization Framework for Shared Mobility in Dynamic Transportation Networks PDF Download
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Author: Neda Masoud
Publisher:
ISBN: 9781369227307
Category :
Languages : en
Pages : 239
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Book Description
Recent advances in communication technology coupled with increasing environmental concerns, road congestion, and the high cost of vehicle ownership have directed more attention to the opportunity cost of empty seats traveling throughout the transportation networks every day. Peer-to-peer (P2P) ridesharing is a good way of using the existing passenger-movement capacity on the vehicles, thereby addressing the concerns about the increasing demand for transportation that is too costly to address via infrastructural expansion.This dissertation is dedicated to the optimization of the matching process between the participants in a ridesharing system. More specifically, focus of this dissertation is on multi-hop matching, in which riders have the possibility of transferring between vehicles. Different algorithms have been presented for various implementation strategies of ridesharing systems. Multiple case studies assess the important role ridesharing can play as a separate mode, or in conjunction with other modes of transportation, in multi-modal settings.
Author: Neda Masoud
Publisher:
ISBN: 9781369227307
Category :
Languages : en
Pages : 239
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Book Description
Recent advances in communication technology coupled with increasing environmental concerns, road congestion, and the high cost of vehicle ownership have directed more attention to the opportunity cost of empty seats traveling throughout the transportation networks every day. Peer-to-peer (P2P) ridesharing is a good way of using the existing passenger-movement capacity on the vehicles, thereby addressing the concerns about the increasing demand for transportation that is too costly to address via infrastructural expansion.This dissertation is dedicated to the optimization of the matching process between the participants in a ridesharing system. More specifically, focus of this dissertation is on multi-hop matching, in which riders have the possibility of transferring between vehicles. Different algorithms have been presented for various implementation strategies of ridesharing systems. Multiple case studies assess the important role ridesharing can play as a separate mode, or in conjunction with other modes of transportation, in multi-modal settings.
Author: Yue Guan (Ph. D.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 192
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Book Description
Mobility of people and goods has been critical to urban life ever since cities emerged thousands of years ago. With the ushering in Cyber-Physical Systems enabled by the development of smart mobile devices, telecommunication technologies, as well as affordable, accessible and powerful computing resources, new paradigms are revolutionizing urban mobility. Among these, Shared Mobility on Demand Service (SMoDS) has changed the landscape of urban transportation, providing alternatives with a customized combination of affordability, flexibility, and carbon footprint. Dynamic routing and dynamic pricing are two central pillars of an SMoDS solution, where the former offers customized routes according to the specific passenger request and real time traffic conditions, and the latter provides incentive signals that appropriately influence the passengers’ subscription of the service. Although emerging SMoDS solutions have seen remarkable successes, further improvements are in need. In this thesis, we present an integrated SMoDS design with dynamic routing and dynamic pricing that introduces two major improvements over the state of the art: (i) enhanced optimality in travel times through dynamic routing with added spatial flexibility, and (ii) explicit accommodation of behavioral modelling of empowered passengers so as to lead to an accurate dynamic pricing strategy. The first part of this thesis focuses on the development of the dynamic routing framework with a new concept of space window. To accommodate the complexity introduced by space window in the optimization of dynamic routes, we propose an algorithm based upon the Alternating Minimization (AltMin) paradigm, and demonstrate an order of magnitude improvement in computational efficiency compared to benchmarks provided by standard solvers. The second part of this thesis, related to dynamic pricing, is broken down into two modules, with the first related to behavioral modelling of empowered passengers based on Cumulative Prospect Theory (CPT). The CPT based behavioral model is able to capture the subjective and potentially irrational behaviors of passengers when deciding upon the SMoDS ride offer amidst uncertainties and risks associated with framing effects, loss aversion, diminishing sensitivity, and probability distortion. Key properties and the implications of the CPT based passenger behavioral model on dynamic pricing are discussed in detail. The second module of dynamic pricing determines the desired probability of acceptance from each passenger so as to optimize key performance indicators of the SMoDS such as the estimated waiting time. A Reinforcement Learning (RL) based approach combined with the problem formulation in the form of a Markov Decision Process (MDP) is used to estimate this desired probability of acceptance. The proposed RL algorithm deploys an integrated planning and learning architecture where the planning phase is carried out by a lookahead tree search, and the learning phase is achieved via value iteration using a neural network as the value function approximator. Two major challenges that arise in this context is the varying dimension of the underlying state and the arrival of information in a sequential manner where long-term dependency needs to be preserved. These are addressed through the incorporation of Long Short-Term Memory (LSTM), convolutional and fully-connected layers. Their judicious incorporation in the underlying neural network architecture allows the extraction of this information and successful estimation of the desired probability of acceptance that leads to the optimization of the SMoDS. A number of computational experiments are carried out using various datasets of large-scale problems and are shown to result in a superior capability of the proposed RL algorithm.
Author: Junfeng Jiao
Publisher: Elsevier
ISBN: 0128230886
Category : Political Science
Languages : en
Pages : 166
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Book Description
Shared Mobility offers a current view on one of the most significant economic activities in recent years. While most studies investigate shared mobility services and transportation piecemeal by city, mode, or company, this book focuses on transportation network companies themselves, highlighting shared bikes and E-scooters. Sections cover how they perform at the local or regional level in an effort to help governments better plan and regulate these emerging services. Shared Mobility explores the opportunities and challenges in these new systems and provides a thorough and succinct reference text for researchers, graduate students, and professionals in the fields of transportation planning, transportation engineering, and urban planning. Examines data collected from the author’s extensive multi-year lab study on shared mobility and transportation Offers a detailed quantitative analysis of shared mobility activities and their impacts on people and cities Explores the interactions between shared mobility modes and policy outcomes
Author: Joseph Chow
Publisher: Elsevier
ISBN: 0128136146
Category : Social Science
Languages : en
Pages : 492
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Book Description
Informed Urban Transport Systems examines how information gathered from new technologies can be used for optimal planning and operation in urban settings. Transportation researchers, and those from related disciplines, such as artificial intelligence, energy, applied mathematics, electrical engineering and environmental science will benefit from the book’s deep dive into the transportation domain, allowing for smarter technological solutions for modern transportation problems. The book helps create solutions with fewer financial, social, political and environmental costs for the populations they serve. Readers will learn from, and be able to interpret, the information and data collected from modern mobile and sensor technologies and understand how to use system optimization strategies using this information. The book concludes with an evaluation of the social and system impacts of modern transportation systems. Takes a fresh look at transportation systems analysis and design, with an emphasis on urban systems and information/data use Serves as a focal point for those in artificial intelligence and environmental science seeking to solve modern transportation problems Examines current analytical innovations that focus on capturing, predicting, visualizing and controlling mobility patterns Provides an overview of the transportation systems benefitting from modern technologies, such as public transport, freight services and shared mobility service models, such as bike sharing, peer-to-peer ride sharing and shared taxis
Author: Gereon Meyer
Publisher: Springer
ISBN: 3319516027
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
This book explores the opportunities and challenges of the sharing economy and innovative transportation technologies with regard to urban mobility. Written by government experts, social scientists, technologists and city planners from North America, Europe and Australia, the papers in this book address the impacts of demographic, societal and economic trends and the fundamental changes arising from the increasing automation and connectivity of vehicles, smart communication technologies, multimodal transit services, and urban design. The book is based on the Disrupting Mobility Summit held in Cambridge, MA (USA) in November 2015, organized by the City Science Initiative at MIT Media Lab, the Transportation Sustainability Research Center at the University of California at Berkeley, the LSE Cities at the London School of Economics and Politics and the Innovation Center for Mobility and Societal Change in Berlin.
Author: Matthias Finger
Publisher: Springer
ISBN: 3319965263
Category : Science
Languages : en
Pages : 256
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Book Description
This book presents essential new governance structures to embrace and regulate smart mobility modes. Drawing on a range of case studies, it paves the way for new approaches to governing future transportation systems. Over the past decades, Information and Communication Technologies have enabled the development of new mobility solutions that have completely redefined traditional and well-established urban transportation systems. Urban transportation systems are evolving dramatically, from the development of shared mobility modes, to the advent of electric mobility, and from the automated mobility trend to the rapid spread of integrated transportation schemes. Given the disruptive nature of those new mobility solutions, new governance structures are needed. Through a series of case studies from around the world, this book highlights governance and regulatory processes having supported, or sometimes prevented, the development and implementation of smart mobility solutions (shared, automated, electric, integrated). The combination of chapters offers a comprehensive overview of the different research endeavours focusing on the governance of smart transportation systems and will help pave the way for this important subject, which is crucial for the future of cities.
Author: Haoran Zhang
Publisher: Elsevier
ISBN: 0323901700
Category : Transportation
Languages : en
Pages : 308
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Book Description
Big Data and Mobility as a Service explores MaaS platforms that can be adaptable to the ever-evolving mobility environment. It looks at multi-mode urban crowd data to assess urban mobility characteristics, their shared transportation potential, and their performance conditions and constraints. The book analyzes the roles of multimodality, travel behavior, urban mobility dynamics and participation. Combined with insights on using big data to analyze market and policy decisions, this book is an essential tool for urban transportation management researchers and practitioners. Summarizes current fundamental MaaS technologies Shows how to utilize anonymous big data for transportation analysis and problem-solving Illustrates, with data-enabled shared transportation service examples from different countries, the similarities and differences within a global urban mobility framework
Author: Fatima Afifah
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Smart mobility, enabled by advanced sensing, communication, vehicle, and emerging mobility technologies, has transformed transportation systems. Real-time information shared by public and private entities plays a pivotal role in smart mobility, which facilitates informed decision-making, including effective mode choice, dynamic vehicle control, optimized travel routing, and strategic vehicle relocation. While more information is believed to benefit individual decision makers, it is crucial to acknowledge that the effects of information on transportation network performance are contingent; more information may not always benefit the safety and mobility of the whole system. The goal of this dissertation is to investigate the effects of information shared by public and private transportation entities on system-level performance. The challenges are primarily due to the lack of a unified modeling framework to endogenously reflect the decentralized multi-agent interaction involved in the interconnected transportation networks and the resulting computational complexities arising from non-convexity and high dimensionality. To address these challenges, this dissertation proposes novel modeling frameworks and computational solutions for three cutting-edge smart mobility applications. First, to examine the impact of en-route information on a transportation network, we propose a novel two-stage stochastic traffic equilibrium model to characterize the equilibrium traffic patterns considering adaptive routing behavior when locational en-route traffic information is provided through infrastructure-to-vehicles (I2V) communications. This model is formulated as a convex stochastic optimization problem so that efficient stochastic programming algorithms can be directly leveraged to achieve scalability. Second, to achieve optimal control over real-time variable speed limits information sharing and evaluate its impact on the network, we propose a twin-delayed deep deterministic policy gradient model, which converges more reliably than state-of-the-art deep reinforcement learning models. We investigate the transferability of the control algorithm and conduct comparative analyses of different traffic control strategies and spatial distributions of variable speed limit control (VSLC) deployment. Third, to assess the impacts of information provided by private ride-sourcing companies on transportation network congestion, we propose a Stackelberg framework for spatial pricing of ride-sourcing services considering traffic congestion and convex reformulation strategies under mild conditions. We perform numerical experiments on transportation networks of varying scales and with diverse transportation network company (TNC) objectives, aiming to derive policy insights regarding the implications of spatial pricing information on transportation systems.
Author: Patrick Vogel
Publisher: Springer
ISBN: 3319277359
Category : Technology & Engineering
Languages : en
Pages : 172
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Book Description
This monograph presents a tactical planning approach for service network design in metropolitan areas. Designing the service network requires the suitable aggregation of demand data as well as the anticipation of operational relocation decisions. To this end, an integrated approach of data analysis and mathematical optimization is introduced. The book also includes a case study based on real-world data to demonstrate the benefit of the proposed service network design approach. The target audience comprises primarily research experts in the field of traffic engineering, but the book may also be beneficial for graduate students.
Author: Tolga Bektaş
Publisher: Springer
ISBN: 3319684965
Category : Computers
Languages : en
Pages : 597
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Book Description
This book constitutes the refereed proceedings of the 8th InternationalConference on Computational Logistics, ICCL 2017, held in Southampton,UK, in October 2017.The 38 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: vehicle routing and scheduling; maritime logistics;synchromodal transportation; and transportation, logistics and supply chain planning.
