Abstract

In transportation planning, design of intersections is required some concrete decisions. It is mostly related to capacity, safety and economy. In many applications, capacity is considered as the main factor for design purpose and type of intersection is determined regarding the capacity. But it is known that safety and economy are as important as the capacity. In order to handle this problem, a multi-criteria decision making approach (AHP) is used. Four intersection types are used. Fuel consumption, emission rates, delay, cost of intersection type and safety parameters are taken into account in the decision process. These intersection types are tested by SIDRA Intersection software using the parameters listed above. The data obtained by SIDRA software is used in the AHP model. Weights of the factors used in the AHP model are varied considering the views of capacity and economy. And results and applicability of the model are discussed. © 2016, IGI Global. All rights reserved. Document type: Part of book or chapter of book

Abstract

the level of traffic congestion rises and the complexity of traffic networks increases, the development of effective transportation strategies becomes the most challenging task for every transport authority. Meanwhile, advancements in computer technology and especially the technique of computer simulation offer a new effective way for testing plausible solutions prior to their implementation. Based on a microscopic traffic simulation model this paper presents an evaluation of the effectiveness of alternative traffic solution interventions on a main arterial in Nicosia, Cyprus. In particular, computer experiments are carried out to test various plausible scenario solutions. The scenarios under evaluation, involve the use of dedicated bus lanes, high occupancy vehicle lanes and road enhancement interventions. The simulation results show that an attractive scenario such as the use of dedicated bus lanes, if not designed properly, could bring disastrous results not only to the private car transport mode but also to the bus transport mode as coupling effects cause buses to get stuck with the rest of the traffic. By going through a computer experimentation process and scenario analysis a viable solution is derived, where restricted lanes for buses and high occupancy vehicles are introduced in combination with road geometry redesign and traffic re-direction at key points. 96 177 187 "p"Sponsors: WIT Transactions on The Built Environment Conference code: 71376

Abstract

The analysis of road transport costs and efficiency relies strongly on the availability of spatial data which in some regions are difficult or expensive to obtain. Open geographical databases seem therefore a promising alternative for these regions. OpenStreetMap©, due to permanent development and improvement by a large number of collaborators, is able to provide reliable data at no cost; as a result, the development and application of specific geographic information tools in most locations becomes possible. In this work we developed routines for forest logistics based on data from OpenStreetMap©, specifically to evaluate fuel consumption and costs as well as CO2 emissions in wood transport in the Northeastern region of Portugal, where the road network is strongly affected by topography that has impact on forest logistics and the viability of alternatives of wood mobilization. We applied our methodology in a real case study of transport of forest biomass to a pellet plant, deriving surface estimates of fuel consumption, fuel costs, CO2 emissions, and accessibility performance to be used as criteria for deciding on support systems for forest management and planning in the Northeastern region. This application demonstrates the importance of available geographic information data and tools in forest mobilization.

Abstract

Purpose – The purpose of this paper is to develop an easy and robust tool to develop a decision support system (DSS) for the inspection staff of oil pipelines. The aim is to predict “the class” of each spillage, with respect to some relevant variables such as, mechanical failure or system malfunction. The management will then be able to define which pipelines to monitor and to choose the most suitable monitoring policies, based on the decision tree analysis outcome. Design/methodology/approach – A non-parametric technique based on rule induction is proposed for the identification of the expected spill cause category of cross-country oil pipelines. In particular, the classification and regression trees approach is used to automatically generate inspection or maintenance decision rules. The analysis that is described is based on an extended database concerning information about spill cause category in cross-country oil pipelines in Western Europe. Findings – The proposed technique represents an interesting added value tool for the management. The proposed methodology extrapolates rules for determining the expected spill cause category of cross-country pipelines, depending on the boundary conditions. Practical implications – The methodology here presented will assist maintenance managers of oil pipeline to better plan maintenance activity. In particular, the procedure makes it possible to determine which parts of a pipeline have to be submitted to a monitoring action or particular protection, with the aim of improving the efficiency and reducing the risk of spillages. Originality/value – Effective planning, coordination, and scheduling of the maintenance function can be, and for many years was, accomplished without computer support. The proposed procedure may be included in an information systems tool (sound Computerized Maintenance Information Management System (CMMIS)), for more efficient and effective maintenance/inspection scheduling activitie

Abstract

Decision Support System (DSS) has been developed to evaluate the technical and economical feasibility of CO2 storage in the subsurface. The DSS performs a detailed, stochastic analysis of the technical and economical aspects of a CCS project, which consists of any number of CO2 sources and sinks plus the connecting pipeline network. The DSS uses the database of CO2 emission points and storage locations in Europe that has been compiled in the EU Geocapacity project. The system is a combination of an internet application, which visualises the database and allows the user to select sources and sinks and create a pipeline network, and an application to be run on a local computer, which performs a stochastic analysis of the costs of a CO2 capture, transport and storage system. The DSS provides not only an estimate of the total CCS cost, but also an analysis of the elements in the CCS chain (capture, compression, transport and storage), enabling a feasibility analysis on several levels. © 2009 Elsevier Ltd. All rights reserved.

Abstract

The batteries of electric vehicles can be used as Virtual Power Plants to balance out frequency deviations in the electricity grid. Carsharing fleet owners have the options to charge an electric vehicle's battery, discharge an electric vehicle's battery, or keep an electric vehicle idle for potential rentals. Charging and discharging can be used to provide reliable operating reserves. We develop an analytical model that manages carsharing fleets. On the one hand, the energy in the batteries of an electric vehicle can be made available to the grid as operating reserves. On the other hand, the electric vehicle can be made available for rental, where the location within the city matters: drivers want a car to be close to their place of departure or arrival. The model can also be used by Transportation Network Companies such as Uber to preposition their vehicles conveniently in a city or optimize zonal pricing. To validate our model we develop a Discrete Event Simulation platform. We calibrate this simulation with locational information (GPS), rental, and charging transactions of 1,500 electric vehicles from the carsharing services Car2Go (Daimler) and DriveNow (BMW) over several years. We investigate the influence of the charging infrastructure density, battery technology, and rental demand for vehicles on the payoff for the carsharing operator and make an international comparison between the USA, Germany, the Netherlands, and Denmark. We show that Virtual Power Plants of electric vehicles create sustainable revenue streams for electric vehicle carsharing companies without compromising their rental business.

Abstract

WOS: 000261774600007 Purpose - The purpose of this paper is to develop a knowledge-based decision support tool used for assisting en-route air traffic controllers by generating resolutions for dual aircraft conflicts after being integrated into a model-based conflict detection and conflict resolution system. Design/methodology/approach - Air traffic controller knowledge, which was obtained from the literature research, about solving aircraft conflicts is represented in a decision tree. Then it is written in Visual Basic programming language. With reference to several rules form the expert air traffic controller knowledge and some factors which affect controller conflict resolution process, the tool generates advisories consisting of eight kinds of separation strategies. Findings - The paper finds that it is expected to increase the safety of air traffic system by supporting air traffic controller in conflict resolution process. Controller workload can be reduced by fast, reliable and acceptable resolution advisories of the tool. Research limitations/implications - The accuracy of decision tree is limited with the adequacy and quality of knowledge obtained from references, several assumptions and interpretation. Because of the unavailability of a model-based conflict detection and resolution tool, the tool could not be evaluated in simulations. Originality/value - After being integrated into a model-based decision support tool, it can reduce the deficiencies of the model-based tool such as low degree of resolution acceptance by controllers and low-resolution speed by providing expert air traffic controller knowledge to the tool.