Technical characteristics and efficiency of urban bus companies: The case of Spain

The aim of the present study is twofold. First, to provide new information concerning the technical characteristics of urban bus companies on the basis of a sample of medium and large-size cities in Spain. Second, to analyze the degree of efficiency of those companies and to quantify the reasons for this efficiency. The results should be useful in evaluating possible changes in public policies relating to urban transport, specifically changes in the way the market is organized and in pricing.The analysis is carried out by estimating a cost function. The sample is made up of a panel data set consisting of observations of nine Spanish companies that operated during the period 1983–1995. The specified functional form is translogarithmic. The output unit of measure adopted is bus*kms run. The cost function includes the network length for each company, thus permitting evidence concerning economies of density and economies of scale.The use of panel data allows us to estimate the cost function, taking into account that each company is affected by the specific characteristics of each individual city, the different features of the network in question and by different levels of efficiency. The economies of scale have been calculated, taking into account that the features of the network and of the city – represented by their specific individual effect – will vary with the company's level of output.Finally, an analysis is made of the relative productive efficiency of the companies, as well as of the variables likely to influence that efficiency.     

Using Bus Rapid Transit to Mitigate Emissions of CO2 from Transport

Abstract

This article investigates the role of bus rapid transit as a tool for mitigation of transport‐related carbon dioxide (CO₂) emissions. We analyse a Quality Bus Corridor (QBC) implemented in Dublin, Ireland, in 1999 and estimate CO₂ emissions associated with differing levels of bus priority for the period 1998–2003 and for the Kyoto commitment period (2008–12). Associated monetary values are established using CO₂ prices from the European Union Emissions Trading Scheme. We find that, in the absence of a QBC, peak‐time emissions for our sample population would have been 50% higher than in the factual scenario. For the Kyoto commitment period, we find the median value of the policy implementation to be in the region of [euro]650 000.     

Modelling major traffic incident impacts and estimation of their associated costs

Network area-wide impacts due to major traffic incidents can be assessed using a microsimulation approach. A VISSIM microsimulation model for a motorway network has been developed and is used to quantify impacts of a major incident in terms of associated costs. The modelled results reveal that a 65% capacity reduction results in 36% more incident-induced delay when compared with the application of a 50% capacity reduction assumption for a two-hour incident clearance duration that blocked one lane of a two-lane motorway. Additionally, an incident which caused a full blockage incurred 40 times more associated impact costs when compared with a major incident which caused a one lane blockage. A 23% cost saving can be achieved by clearing one lane of a fully blocked two-hour major traffic incident after 90 minutes, while a 37% cost saving can be achieved by clearing all blockages after 90 minutes.     

Analysis of vehicle ownership evolution in Montreal,Canada using pseudo panel analysis

This paper employs a pseudo-panel approach to study vehicle ownership evolution in Montreal region, Canada using cross-sectional origin–destination survey datasets of 1998, 2003 and 2008. Econometric modeling approaches that simultaneously accommodate the influence of observed and unobserved attributes on the vehicle ownership decision framework are implemented. Specifically, we estimate generalized versions of the ordered response model—including the generalized, scaled- and mixed-generalized ordered logit models. Socio-demographic variables that impact household’s decision to own multiple cars include number of full and part-time working adults, license holders, middle aged adults, retirees, male householders, and presence of children. Increased number of bus stops, longer bus and metro lengths within the household residential location buffer area decrease vehicle fleet size of households. The observed results also varied across years as manifested by the significance of the interaction terms of some of the variables with the time elapsed since 1998 variable. Moreover, variation due to unobserved factors are captured for part-time working adults, number of bus stops, and length of metro lines. In terms of the effect of location of households, we found that some neighborhoods exhibited distinct car ownership temporal dynamics over the years.     

Modelling demand in restricted parking zones

Multiple linear regression (MLR) and geographically weighted regression (GWR) models are used for estimating parking demand in areas with paid short stay parking systems. These models have been applied to the city of Santander (Cantabria, Spain) to check their goodness of fit and their predictive ability. The results show the main advantages and disadvantages of using GWR models. The technique proved to be useful in this case study because it offered a better fit and made better predictions in a scenario showing a certain degree of spatial heterogeneity unexplained by any of the variables introduced into the global model. However, the GWR model also presented situations of local correlation although this was considered moderate given the results provided by the variance inflation factors and the local condition indexes.     

Sight distance analysis of highways using GIS tools

Analyzing the distance visible to a driver on the highway is important for traffic safety, especially in maneuvers such as emergency stops, when passing another vehicle or when vehicles cross at intersections. This analysis is necessary not only in the design phase of highways, but also when they are in service. For its use in this last phase, a procedure supported by a Geographic Information System (GIS) has been implemented that determines the highway distances visible to the driver. The use of a GIS allows the sight distance analysis to be integrated with other analyses related to traffic safety, such as crash and design consistency analyses. In this way, more complete analyses could be made and costs shared. Additionally, with the procedure proposed it is possible to use data regarding the trajectory of a vehicle obtained on a highway with a Global Positioning System (GPS) device. This application is very useful when highway design data are not available. The procedure developed and its application in a case study are presented in this article.     

The effect of neighbourhood characteristics,accessibility, home–work location,and demographics on commuting distances

The goal of this paper is to better understand home-to-work travel distances throughout the Montréal Metropolitan region. A simultaneous equation modelling analysis is carried out to jointly explain commuter trip length and home–work location as a function of neighbourhood typologies, commuter socio-demographics and measures of job and worker accessibility. First, a factor and cluster analysis of urban form is performed over the entire region on a fine-scale grid pattern. The outcome of this analysis is the classification of typologies at both home and job locations. Different measures of accessibility and commuter socio-demographics are then incorporated into the analysis. Varied data sources including a detailed Montréal Origin–Destination Survey on over 30,000 home-to-work automobile trips are analyzed. Among other results, commuters that live and work in a different sub-region almost double the average trip distance and although socio-economic factors have a statistically significant correlation with commuter distance, these factors have a marginal effect. Interestingly, our results highlight the importance of urban form and job accessibility. Deciding on whether to live and work in the same sub-region was modelled as an endogenous binary random utility model; unobserved heterogeneities seem to be simultaneously influencing both the home–work location choice and trip-to-work distances. Our results underscore the importance of home–work location with respect to urban form and job accessibility. Hence, policies that support more dense and mixed land-use in suburban areas would not be enough to reduce commuter distances. These actions should be accompanied by other policy initiatives to discourage long car trips.