Real Time Detection and Classification of Arrow Markings in Urban Streets

For highly automated driving in urban regions it is essential to know the precise position of the car. Furthermore it is important to understand the surrounding context in complex situations, e.g. multilane crossings and turn lanes. To understand those situations there is not only the task to detect the lane border, but to detect the painted information inside the lane. The paper is facing and evaluating two methods to classify this additional lane information. Therefore the images from five cameras mounted around the car are used. Four of them with fisheye lenses. The methods have in common, that the input images are transformed into a bird view projection. First introduced method is to extract contours from the transformed images and collect geometrical features and Fourier coefficients. The second introduced way, is to calculate histograms of oriented gradients and use it as input for the classification step. Both classification approaches are implemented and evaluated as multiclass and single class detectors for each arrow type. Furthermore, the classification results from a support vector machine and random forest were faced for this classification problem. The results from the multiclass detectors are evaluated and presented in form of confusion matrices. With the introduced approaches a high detection confidence could be achieved, proofed with validation datasets and in practical use.     

The <Emphasis Type="Italic">Santiago Panel</Emphasis>: measuring the effects of implementing Transantiago

Although panels offer significant advantages over cross sectional data especially in terms of evaluating the effects of significant policy changes, there are precious few examples of panels built around an important change to an urban transport system. For this reason we took the opportunity of the introduction of Transantiago, a radically new public transport system for Santiago de Chile in February 2007, to form a panel, the first wave of which was taken in December 2006. The final objective was to use this Santiago Panel to estimate mode choice models considering both inertia and policy effects. This document describes both the design and construction of the panel, and presents some results based on an analysis of its four waves; for example, we registered a high percentage of mode change (55.1%) attributable to the introduction of the new system. The panel can claim the highest response rate (or lowest attrition) reported in the literature (95% in the second wave, 92% in the third one, and 85% in the forth one). This hints at the possibility of developing sophisticated models to evaluate the effects of a system shock in the presence of inertia in decision making.     

Sustainability at Spanish ports specialized in liquid bulk: evolution in times of crisis (2010–2015)

In Spain, 28 Port Authorities of general interest moved more than 168 thousand tonnes of liquid bulk (34% of overall traffic) in 2015. Almost 82% of this amount corresponded to eight ports (G-8) that have a refinery within their facilities. This unique degree of specialization and concentration makes this set of ports an ideal sample to analyse the evolution of their sustainability levels, particularly during the crisis started in 2008 and onwards. A proprietary methodology based on Multidimensional Synthetic Indices has been used. The comparison of the findings obtained for 2010 and 2015 allows a diagnosis of the evolution of port sustainability measured through the economic, institutional, environmental and social dimensions to be established, as well as a study of the patterns of behaviour that each port has followed in this issue.     

Indirect estimation of interregional freight flows with a real-valued genetic algorithm

Transportation - This paper introduces a method for estimating the interregional transportation of certain commodities in those cases where the commodity flows are not readily available and only...     

Valuing reductions in environmental pollution in a residential location context

A stated preference ranking experiment is designed to estimate the willingness-to-pay (WTP) for reducing the amount of atmospheric pollution in a group-based residential location context. Important issues are the proper definition of the context and the variable metric for the environmental attribute. Sample members were asked to rank 10 options arising from variations in the attributes travel time to work and to study, rent of the house and an environmental attribute (the number of days of Alert, in terms of concentration of PM₁₀, at a dwelling’s location). Multinomial logit models based on a consistent microeconomic framework were estimated for various stratifications of the data (income, pollution sensitivity, and type of dwelling currently inhabited). From these subjective values of time and WTP were derived for reductions in the number of days of alert and hence the amount of pollutant concentration at a given location. The WTP came out at about 1% of the family income for reducing one contingence day per year; this is approximately 60% higher than an estimate reported for the city of Edmonton, Canada, but the average PM₁₀ concentration in Santiago is about six times higher.     

Preference Heterogeneity and Willingness to Pay for Travel Time Savings

We examined different model specifications to detect the presence of preference heterogeneity in a mode choice context. The specification that worked best allows for both systematic and random variations in tastes, with parameters obtained at the individual level using Bayesian methods. Subjective values of travel time (SVT) and expected individual compensated variation were derived and aggregated to obtain measures of social welfare. Results suggest that the benefit measures, both at the individual and at the social level, are sensitive to preference heterogeneity assumptions. SVT and welfare changes derived from travel time reductions could be underestimated if the traditional assumption of taste homogeneity is made (we detected differences up to 30% in both types of measures). We also obtained an empirical value for the error made when evaluating changes in social welfare using an approximation of the expected individual compensated variation (expressed as a function of individual SVT) rather than its exact expression.     

On the semantic scale problem in stated preference rating experiments

Stated preference (SP) rating experiments are easy to design and conduct. Furthermore, they constitute a generalisation of SP choice experiments in terms of the information about preferences that can be achieved. However, its results are sensitive to the numerical values assigned by the analyst to the semantic scale used by individuals to express their preferences. We consider this problem in depth using a variety of statistical techniques, including ordinal probit and a novel optimal scale linear regression approach.     

Energy-harvesting potential of automobile suspension

This study is aimed quantify dissipated power in a damper of automobile suspension to predict energy harvesting potential of a passenger car more accurately. Field measurements of power dissipation in a regenerative damper are still rare. The novelty is in using the broad database of real road profiles, a 9 degrees-of-freedom full-car model with real parameters, and a tyre-enveloping contact model. Results were presented as a function of road surface type, velocity and road roughness characterised by International Roughness Index. Results were calculated for 1600 test sections of a total length about 253.5?km. Root mean square of a dissipated power was calculated from 19 to 46?W for all four suspension dampers and velocity 60?km/h and from 24 to 58?W for velocity 90?km/h. Results were compared for a full-car model with a tyre-enveloping road contact, full-car and quarter-car models with a tyre–road point contact. Mean difference among three models in calculated power was a few per cent.     

Analysis of the evolvement of contact wire wear irregularity in railway catenary based on historical data

This paper studies the evolvement of the wear irregularity of contact wire using wire thickness data measured yearly from a section of railway catenary. The power spectral density and time–frequency representation based on the wavelet transform are employed for data analysis, with an emphasis on local wear irregularities that are crucial for contact wire condition assessment. To investigate the cause of wear irregularity evolvement and the mutual influence with the pantograph–catenary dynamic interaction, simulations considering the influence of wear irregularity are carried out based on the finite element method. Analyses of the actual wear irregularities and the dynamic contact force under singular and complex wear irregularities are performed. Although the wear irregularity has limited impact on the pantograph–catenary interaction, it can induce the vibration of pantograph and contact wire that will lead to a notable increase of contact force standard deviation. The evolvement of wear irregularity is closely associated with the span length and dropper distribution of catenary structure and the running direction of pantograph. In addition, it is found feasible to detect the wear irregularity based on contact force, on condition that the sampling frequency is high enough to reflect the indicative frequencies.     

Forecasting vs. observed outturn: Studying choice in faster inter-island connections

Passenger demand and, in particular, mode choice between the islands of Gran Canaria and Tenerife has experienced important changes in the last decade. In 2005 the jetfoil, which had been the dominant mode for many years, was replaced by a slower but cheaper fast ferry service. This induced important changes in the market shares of all competing modes (airplane, slow ferry and another fast ferry with a shorter in-sea time, but needing a bus connection in land). We estimated several discrete choice models, with data collected two years before, with the aim to test their forecasting performance in relation with observed behaviour. Interestingly, we found that an easy to interpret multinomial logit model allowing for systematic taste variations performed best in forecasting. We also discuss some model assumptions related to forecasting that allow replicating the effects of introducing a new mode more accurately. We finally show how the model can be used to examine the social benefits of a related infrastructure improvement project in the island of Gran Canaria.