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The need to understand the effect of policy decisions on environmental indicators is strong. The emergence of new technologies brought about by connected vehicle technologies, which are difficult to evaluate in field settings, means that policies must often be evaluated with software models. In these cases, however, the transportation model and the emissions model are often separate, and multiple different ways to connect these models are possible. Although the estimations provided by each model will vary, each method also differs in terms of the computational time. This research is motivated by the need to understand the consequences of choosing a particular method to link a traffic and emissions model. Within the literature, aggregated approaches that simply use average speeds and volumes are often selected for their convenience and lower data needs. A number of different scenarios were therefore constructed to compare the estimates of these aggregated approaches to other methods that use disaggregated data, such as the use of individual discrete trajectories, the use of a velocity binning scheme that characterises networks based on their velocity profile or the use of a clustering algorithm developed for this study. This research presents a clustering algorithm that can be used to reduce the computational loads of an emissions estimation process without loss of accuracy. The results of the analysis highlight the consequences of choosing each approach. Aggregated approaches produce unreliable estimates as they are backed by assumptions that may not be valid in every case. Using individual trajectories creates high computational loads and may not be feasible in all cases. The wealth of data available from a traffic microsimulation mean that using an aggregated approach neglects to utilise the full potential of the model; however, the hybrid approaches presented in this research (clustering and velocity binning) were found to make excellent use of this data while still minimizing computational demands.
This volume brings together works resulting from research carried out by members of the EURO Working Group on Transportation (EWGT) and presented during meetings and workshops organized by the Group under the patronage of the Association of European Operational Research Societies in 2012 and 2013. The main targets of the EWGT include providing a forum to share research information and experience, encouraging joint research and the development of both theoretical methods and applications, and promoting cooperation among the many institutions and organizations which are leaders at national level in the field of transportation and logistics. The primary fields of interest concern operational research methods, mathematical models and computation algorithms, to solve and sustain solutions to problems mainly faced by public administrations, city authorities, public transport companies, service providers and logistic operators. Related areas of interest are: land use and transportation planning, traffic control and simulation models, traffic network equilibrium models, public transport planning and management, applications of combinatorial optimization, vehicle routing and scheduling, intelligent transport systems, logistics and freight transport, environment problems, transport safety, and impact evaluation methods. In this volume, attention focuses on the following topics of interest: · Decision-making and decision support · Energy and Environmental Impacts · Urban network design · Optimization and simulation · Traffic Modelling, Control and Network Traffic Management · Transportation Planning · Mobility, Accessibility and Travel Behavior · Vehicle Routing
This comprehensive textbook/reference provides an in-depth overview of the key aspects of transportation analysis, with an emphasis on modeling real transportation systems and executing the models. Topics and features: presents comprehensive review questions at the end of each chapter, together with detailed case studies, useful links, references and suggestions for further reading; supplies a variety of teaching support materials at the book’s webpage on Springer.com, including a complete set of lecture slides; examines the classification of models used for multimodal transportation systems, and reviews the models and evaluation methods used in transportation planning; explains traffic assignment to road networks, and describes computer simulation integration platforms and their use in the transportation systems sector; provides an overview of transportation simulation tools, and discusses the critical issues in the design, development and use of the simulation models.
The search for sustainable transportation strategies hinges on the availability of transportation modeling frameworks that are sensitive enough to reflect the impact of proposed strategies and policies, and to evaluate new and emerging ideas and applications designed to make the system more sustainable. Motivated by this urgent need, this doctoral study aims at utilizing agent-based modeling and simulation (ABMS) principles to develop advanced transportation modeling frameworks that can support sustainable transportation planning and applications. Within this broader context, the study focuses on two major case studies. The first study involves developing an agent-based transportation model of a university campus capable of accurately modeling the parking search process. A unique feature of the model is that it includes a sequential game-theoretic neo-additive capacity model to model parking behavior under uncertainty. The model accounts for drivers' psychological characteristics (i.e. optimistic and pessimistic attitudes) regarding parking availability in their most desirable lot, traits that are shown to play a major role in determining drivers' parking choices. To demonstrate the model's validity and potential applications, it is used to model north campus transportation system of University at Buffalo (UB), The State University of New York and to quantify the environmental cost of the parking search process, a cost that turns out to be substantial. The second case study considered in this dissertation focuses on evaluating the likely environmental benefits of an Intelligent Transportation Systems (ITS) that involves providing dynamic route guidance to travelers based on their lowest emissions or fuel consumption route. To do this, an integrated microscopic traffic-emissions model is developed by interfacing the Transportation ANalysis and SIMulation System (TRANSIMS) with the Motor Vehicle Emission Simulator (MOVES) emissions model developed by the Environmental Protection Agency (EPA). The integrated model is then used to evaluate the benefits of "green" routing in the Greater Buffalo-Niagara metropolitan area. Results indicate that green routing could result in significant reductions in emissions, but that this naturally comes at the expense of an increased travel time. Assuming a traffic stream of only passenger cars, green routing is shown to result in an almost 13% reduction in Carbon Monoxide (CO) emissions, and a corresponding 8% increase in travel time for the case study.
Simulation Approaches in Transportation Analysis: Recent Advances and Challenges presents the latest developments in transport simulation, including dynamic network simulation and micro-simulation of people’s movement in an urban area. It offers a collection of the major simulation models that are now in use throughout the world; it illustrates each model in detail, examines potential problems, and points to directions for future development. The reader will be able to understand the functioning, applicability, and usefulness of advanced transport simulation models. The material in this book will be of wide use to graduate students and practitioners as well as researchers in the transportation engineering and planning fields.
The increasing power of computer technologies, the evolution of software en- neering and the advent of the intelligent transport systems has prompted traf c simulation to become one of the most used approaches for traf c analysis in s- port of the design and evaluation of traf c systems. The ability of traf c simulation to emulate the time variability of traf c phenomena makes it a unique tool for capturing the complexity of traf c systems. In recent years, traf c simulation – and namely microscopic traf c simulation – has moved from the academic to the professional world. A wide variety of traf- c simulation software is currently available on the market and it is utilized by thousands of users, consultants, researchers and public agencies. Microscopic traf c simulation based on the emulation of traf c ows from the dynamics of individual vehicles is becoming one the most attractive approaches. However, traf c simulation still lacks a uni ed treatment. Dozens of papers on theory and applications are published in scienti c journals every year. A search of simulation-related papers and workshops through the proceedings of the last annual TRB meetings would support this assertion, as would a review of the minutes from speci cally dedicated meetings such as the International Symposiums on Traf c Simulation (Yokohama, 2002; Lausanne, 2006; Brisbane, 2008) or the International Workshops on Traf c Modeling and Simulation (Tucson, 2001; Barcelona, 2003; Sedona, 2005; Graz 2008). Yet, the only comprehensive treatment of the subject to be found so far is in the user’s manuals of various software products.
Transportation emissions constitute a significant portion of overall emissions inventories, and contribute to air quality health concerns. Reductions in transportation emissions can be achieved through efficient design of infrastructure, effective policy and regulation, and informed planning decisions. However, current transportation emissions models cannot accomplish all of these goals efficiently, and as a result such reduction opportunities are missed. This work presents a transportation micro-simulation tool that resolves emissions at the link level and efficiently models the effects of traffic congestion, traffic shifting, and mode shifting. This tool can be used for iterative design studies using conventional computing hardware. The model is described in detail, and a confidence assessment tests the model credibility. Several application studies illustrate the usefulness of the approach, and a comparison to an interaction-based micro-simulation demonstrates the efficiency and limitations of the approach.
TRB Special Report 288, Metropolitan Travel Forecasting: Current Practice and Future Direction, examines metropolitan travel forecasting models that provide public officials with information to inform decisions on major transportation system investments and policies. The report explores what improvements may be needed to the models and how federal, state, and local agencies can achieve them. According to the committee that produced the report, travel forecasting models in current use are not adequate for many of today's necessary planning and regulatory uses.
Simulation Approaches in Transportation Analysis: Recent Advances and Challenges presents the latest developments in transport simulation, including dynamic network simulation and micro-simulation of people’s movement in an urban area. It offers a collection of the major simulation models that are now in use throughout the world; it illustrates each model in detail, examines potential problems, and points to directions for future development. The reader will be able to understand the functioning, applicability, and usefulness of advanced transport simulation models. The material in this book will be of wide use to graduate students and practitioners as well as researchers in the transportation engineering and planning fields.