Using floating car data to analyse the effects of ITS measures and eco-driving

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

Assessment of innovative measures implemented in European bus systems using key performance indicators

This paper reports the results of the assessment of a range of measures implemented in bus systems in five European cities to improve the use of public transport by increasing its attractiveness and enhancing its image in urban areas. This research was conducted as part of the EBSF project (European Bus System of the Future) from 2008 to 2012. New buses (prototypes), new vehicle and infrastructure technologies, and operational best practices were introduced, all of which were combined in a system approach. The measures were assessed using multicriteria analysis to simultaneously evaluate a certain number of criteria that need to be aggregated. Each criterion is measured by one or more key performance indicators (KPI) calculated in two scenarios (reference scenario, with no measure implemented; and project scenario, with the implementation of some measures), in order to evaluate the difference in the KPI performance between the reference and project scenario. The results indicate that the measures produce a greater benefit in issues related to bus system productivity and customer satisfaction, with the greatest impact on aspects of perceptions of comfort, cleanliness and quality of service, information to passengers and environmental issues. The study also reveals that the implementation of several measures has greater social utility than very specific and isolated measures.

Multi-argument fuzzy measures on lattices of fuzzy sets

In this paper, we axiomatically introduce fuzzy multi-measures on bounded lattices. In particular, we make a distinction between four different types of fuzzy set multi-measures on a universe X, considering both the usual or inverse real number ordering of this lattice and increasing or decreasing monotonicity with respect to the number of arguments. We provide results from which we can derive families of measures that hold for the applicable conditions in each case.

Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: a review

Quantitative measures of human movement quality are important for discriminating healthy and pathological conditions and for expressing the outcomes and clinically important changes in subjects' functional state. However the most frequently used instruments for the upper extremity functional assessment are clinical scales, that previously have been standardized and validated, but have a high subjective component depending on the observer who scores the test. But they are not enough to assess motor strategies used during movements, and their use in combination with other more objective measures is necessary. The objective of the present review is to provide an overview on objective metrics found in literature with the aim of quantifying the upper extremity performance during functional tasks, regardless of the equipment or system used for registering kinematic data.

Considerations on the trade and finances of this Kingdom, and on the measures of Administration with respect to those great national objects since the conclusion of the peace [Texto impreso]

Autor tomado de la Britsh Library

Spatial Planning Measures for the Enhancement of Urban Resilience Against Flooding Risk

Dentro del campo de la ciudad como lugar se analiza el concepto de planificación territorial y planeamiento espacial. Flooding is one of the main risks associated to many urban settlements in Spain and, indeed, elsewhere. The location of cities has traditionally ignored this type of risk as other locational criteria prevailed (communications, crop yields, etc.). Defence engineering has been the customary way to offset the risk but, nowadays, the opportunity costs of engineering works in urban areas has highlighted the interest of “soft measures” based on prevention. Early warning systems plus development planning controls rank among the most favoured ones. This paper reflects the results of a recent EU-financed research project on alternative measures geared to the enhancement of urban resilience against flooding. A city study in Spain is used as example of those measures.

The environmental and economic effects of innovative measures in urban parcels delivery

The main scope of this research is to identify and evaluate solutions to redesign the parcels delivery logistic process to achieve higher level of quality, lower operational costs, energy consumptions and air pollution. The study is starting from the analysis of the delivery process managed by a leader company operating in Rome. Main delivery flows, personnel and fleet management costs, quality performances and environmental impacts are investigated. The results of this analysis are benchmarked with other European situations. On the basis of the feedback of this analysis, a set of operational measures, potentially able tackle the objectives, are identified and assessed by means of a simulative approach. The assessment is based on environmental and economic indicators allowing the comparison between new and reference scenarios from the viewpoints of the key players: operator, customer and Society. Moreover, the operational measures are combined into alternative packages by looking for the sets capable to maximize the benefits for the key players. The methodology, tested on Rome case study, is general and flexible enough to be extended to parcels delivery problem in different urban contexts, as well as to similar urban distribution problems (e.g. press, food, security, school)

Assessment methodology applied to demand measures to change urban mobility behavior

In order to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. Transport modelling literature has been increasingly aware that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users’ social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced; but links between international and Spanish perspectives are rarely dealt with. The overall objective of the thesis is to develop a stepped methodology that integrate diverse perspectives to evaluate the willingness to change patterns of urban mobility in Madrid, based on four steps: (1st) analysis of causal relationships between both objective and subjective personal variables, and travel behavior to capture pro-car and pro-public transport intentions; (2nd) exploring the potential influence of individual trip characteristics and social influence variables on transport mode choice; (3rd) identifying built environment dimensions on travel behavior; and (4th) exploring the potential influence on transport mode choice of extrinsic characteristics of individual trip using panel data, land use variables using spatial characteristics and social influence variables. The data used for this thesis have been collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) carried out in Madrid. Although the steps above are mainly methodological, the application to the area of Madrid allows deriving important results that can be directly used to forecast travel demand and to evaluate the benefits of specific policies that might be implemented in the area. The results demonstrated, respectively: (1st) transport policy actions are more likely to be effective when pro-car intention has been disrupted first; (2nd) the consideration of “helped” and “voluntary” users as tested here could have a positive and negative impact, respectively, on the use of public transport; (3rd) the importance of density, design, diversity and accessibility underlying dimensions responsible for land use variables; and (4th) there are clearly different types of combinations of social interactions, land use and time frame on travel behavior studies. Finally, with the objective to study the impact of demand measures to change urban mobility behavior, those previous results have been considered in a unique way, a hybrid discrete choice model has been used on a 5th step. Then it can be concluded that urban mobility behavior is not only ruled by the maximum utility criterion, but also by a strong psychological-environment concept, developed without the mediation of cognitive processes during choice, i.e., many people using public transport on their way to work do not do it for utilitarian reasons, but because no other choice is available. Regarding built environment dimensions, the more diversity place of residence, the more difficult the use of public transport or walking.

Assessing the passengers’ perception of implemented advanced management measures in bus service

The aim of this investigation is to evaluate the passenger?s perception of some attributes related to quality of bus services, and how this perception changes with the implementation of different measures. Surveys to passengers riding different bus lines were conducted in two scenarios: before the implementation of the measures and after the measures were implemented. The results of the passenger surveys were statistically analysed; then, an ordered logit model was used to analyse the differences between surveys thanks to the implemented measures. Finally, a factor analysis was done to identify the underlying unobserved factors (latent variables) that the respondents perceived

Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain) through the WRF-SMOKE-CMAQ modelling system

The achievement of the limit values established in the European legislation pose an important handicap for large urban areas with intense road traffic, such as Madrid (Spain). Despite permanent measures included in air quality plans it is important to assess additional measures that may be temporally applied under unfavourable conditions. This paper reports on the simulation of different traffic restriction strategies in Madrid for high-pollution episodes.

Veto values in Group Decision Making within MAUT: aggregating complete rankings derived from dominance intensity measures

We consider a groupdecision-making problem within multi-attribute utility theory, in which the relative importance of decisionmakers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, where as adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to derive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for the irrelative importance.

Sustainability assessment of energy saving measures: A multi-criteria approach for residential buildings retrofitting—A case study of the Spanish housing stock

The building sector is well known to be one of the key energy consumers worldwide. The renovation of existing buildings provides excellent opportunities for an effective reduction of energy consumption and greenhouse gas emissions but it is essential to identify the optimal strategies. In this paper a multi-criteria methodology is proposed for the comparative analysis of retrofitting solutions. Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) are combined by expressing environmental impacts in monetary values. A Pareto optimization is used to select the preferred strategies. The methodology is exemplified by a case study: the renovation of a representative housing block from the 1960s located in Madrid. Eight scenarios have been proposed, from the Business as Usual scenario (BAU), through Spanish Building Regulation requirements (for new buildings) up to the Passive House standard. Results show how current renovation strategies that are being applied in Madrid are far from being optimal solutions. The required additional investment, which is needed to obtain an overall performance improvement of the envelope compared with the common practice to date, is relatively low (8%) considering the obtained life cycle environmental and financial savings (43% and 45%, respectively).

Measures of residue density in protein structures

A hierarchy of residue density assessments and packing properties in protein structures are contrasted, including a regular density, a variety of charge densities, a hydrophobic density, a polar density, and an aromatic density. These densities are investigated by alternative distance measures and also at the interface of multiunit structures. Amino acids are divided into nine structural categories according to three secondary structure states and three solvent accessibility levels. To take account of amino acid abundance differences across protein structures, we normalize the observed density by the expected density defining a density index. Solvent accessibility levels exert the predominant influence in determinations of the regular residue density. Explicitly, the regular density values vary approximately linearly with respect to solvent accessibility levels, the linearity parameters depending on the amino acid. The charge index reveals pronounced inequalities between lysine and arginine in their interactions with acidic residues. The aromatic density calculations in all structural categories parallel the regular density calculations, indicating that the aromatic residues are distributed as a random sample of all residues. Moreover, aromatic residues are found to be over-represented in the neighborhood of all amino acids. This result might be attributed to nucleation sites and protein stability being substantially associated with aromatic residues.

Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

7 pages, 4 figures Acknowledgement We are grateful to M. Riedl and G. Ansmann for fruitful discussions and critical comments on earlier versions of the manuscript. This work was supported by the Volkswagen Foundation (Grant Nos. 88461, 88462, 88463, 85390, 85391 and 85392).

Sources of selection bias in evaluating social programs: An interpretation of conventional measures and evidence on the effectiveness of matching as a program evaluation method

This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.