Abstract

This study uses regression analysis to evaluate long-run traffic management system performance. Three important traffic management systems in the Twin Cities metro area - Ramp Metering, Variable Message Signs (VMS), and Freeway Service Patrol (the Highway Helper Program) were evaluated with multiple regression models to predict link speed and incident rate. We find that ramp meters increase freeway link speed and reduce incident rate. Freeway Service Patrols increase link speed when incidents are present. The results for variable message signs are ambiguous. Document type: Part of book or chapter of book

Abstract

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of average pollutant levels but also during high and low pollution episodes. To do so, we use a quantile regression approach for fixed effect panel data, which allows us analyzing different scenarios (beyond the average levels). We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect - or even a slightly increasing effect - on the two pollutants, depending on the pollution scenario. Document type: Article

Abstract

Short sea shipping (SSS) is the maritime transport of goods over relatively short distances, as opposed to the intercontinental cross-ocean deep sea shipping. The goal of the current paper is to identify SSS growth potential and the univariate regression analysis indicates that the following variables influence total SSS volume in European countries: land area, coastline, total number of SSS ports, number of small SSS ports, number of large SSS ports, number of inhabitants, Gross Domestic Product (GDP), GDP per head, road length and rail length. An additional multivariate regression analysis indicates that more than 78% of the variance in the total SSS volume per country can be explained by variations in the number of large SSS ports and the GDP per head. Finally, future prospects for SSS indicate that most countries show (theoretical) potential to further increase their SSS volume calling for tailor-made policies to utilize this potential. Document type: Article

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

Sites with varying geometric features were analyzed to develop the 85th percentile speed prediction models for car and sports utility vehicle (SUV) at 50 m prior to the point of curvature (PC), PC, midpoint of a curve (MC), point of tangent (PT) and 50 m beyond PT on four-lane median divided rural highways. The car and SUV speed data were combined in the analysis as they were found to be normally distributed and not significantly different. Independent parameters representing geometric features and speed at the preceding section were logically selected in stepwise regression analyses to develop the models. Speeds at various locations were found to be dependent on some combinations of curve length, curvature and speed in the immediately preceding section of the highway. Curve length had a significant effect on the speed at locations 50 m prior to PC, PC and MC. The effect of curvature on speed was observed only at MC. The curve geometry did not have a significant effect on speed from PT onwards. The speed at 50 m prior to PC and curvature is the most significant parameter that affects the speed at PC and MC, respectively. Before entering a horizontal curve, drivers possibly perceive the curve based on its length. Longer curve encourages drivers to maintain higher speed in the preceding tangent section. Further, drivers start experiencing the effect of curvature only after entering the curve and adjust speed accordingly. Practitioners can use these findings in designing consistent horizontal curve for vehicle speed harmony. Document type: Article

Abstract

n increasing number of municipalities are striving for energy autonomy. This study determines in which municipalities and at what additional cost energy autonomy is feasible for a case study of Germany. An existing municipal energy system optimization model is extended to include the personal transport, industrial and commercial sectors. A machine learning approach identifies a regression model among 19 methods, which is best suited for the transfer of individual optimization results to all municipalities. The resulting levelized cost of energy (LCOE) from the optimization of 15 case studies are transferred using a stepwise linear regression model. The regression model shows a mean absolute percentage error of 12.5%. The study demonstrates that energy autonomy is technically feasible in 6,314 (56%) municipalities. Thereby, the LCOEs increase in the autonomous case on average by 0.41 €/kWh compared to the minimum cost scenario. Apart from energy demand, base-load-capable bioenergy and deep geothermal energy appear to have the greatest influence on the LCOEs. This study represents a starting point for defining possible scenarios in studies of future national energy system or transmission grid expansion planning, which for the first time consider completely energy autonomous municipalities.

Abstract

The study presents an investigation into traffic based noise pollution in the city of Kirikkale, Turkey. For this purpose, traffic noise levels were measured at 15 intersections across the city during three peak times ‐ morning (08:00–09:00), noon (12:30–13:30) and evening (17:00–18:00) hours. The comparison of Leq values against the limit values of the Turkish Noise and Control Regulations for Settlement Zones showed that Leqvalues exceeded the limits at all stations. A linear regression analysis performed between the Leq and logarithm of total traffic volume (log Q) produced a coefficient of determination of 0.52. A multi regression analysis carried out between the Leq and four different vehicle types resulted in a correlation coefficient of 0.74. The correlation matrix indicated that the highest correlation was found for trucks/buses with r = 0.92. The spatial maps of traffic noise created by the Kriging method under ArcView GIS displayed that there seemed to be significant differences in the spatial variation of traffic noise across the city. In order to reduce traffic based noise levels within the city some useful suggestions were presented. First published online: 27 Oct 2010