Modelling bicycle use intention: the role of perceptions

Users’ perceptions are identified as key elements to understand bicycle use, whose election cannot be explained with usual mobility variables and socio-economic characteristics. A hybrid model is proposed to model the intention of bicycle use; it combines a structural equations model that captures intentions and a choice model. The framework is applied to a case of a university campus in Madrid that is studying a new internal bike system. Results show that four latent variables (convenience, pro-bike, physical determinants and external restrictions) help explaining intention to use bike, representing a number of factors that are linked to individual perceptions.     

Influence of the weather on mode choice in corridors with time-varying congestion: a mixed data study

Studies that link human behaviour to the influence of weather have historically been conducted in such fields as tourism, marketing and leisure. In most studies that jointly examine weather and the mode of transport, only open-air transportation has been considered (for example, bicycle, motorcycle or walking). This focus, together with the habitual use of data collected with automatic devices and a lack of studies that analyse this issue using stated preference data, are the main reasons motivating this paper. This paper aims to analyse the influence of weather and the density of traffic on the choice of transport mode. A case study is conducted in an access/egress corridor located in the city of Barcelona (Spain). Two data sources were used: revealed preference and stated preference data. Modelling techniques using mixed data enabled the stronger features from both data sources to be captured. Finally, we discuss how the selection of different alternative specific constants in models estimated using mixed data could generate unrealistic forecasting results if environmental changes are expected in the actual market.     

Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates

Transportation - Hybrid discrete choice (HDC) modeling requires indicators to allow for the identification of latent variables. An indicator usually expresses the level of agreement of a respondent...     

CANDY statement of methods

This paper presents a detailed overview of CANDY, a catenary–pantograph dynamic interaction software. Authors describe the main key points of the formulation, focusing on its time-integration scheme, the pantograph and contact models as well as the solution of the initial equilibrium problem. Nonetheless one of the most important features of CANDY is its moving finite element mesh, which enables accurate results without excessive computational cost. The validation of the model against the European Standard EN 50318 and some conclusions and comments about the results of the benchmark are also included.     

Computing 4D near-optimal trajectories for dynamic air traffic flow management with column generation and branch-and-price

Abstract

The current air traffic system faces recurrent saturation problems. Numerous studies are dedicated to this issue, including the present research on a new dynamic regulation filter holding frequent trajectory optimisations in a real-time sliding horizon loop process. We consider a trajectory optimisation problem arising in this context, where a feasible four-dimensional (4D) trajectory is to be built and assigned to each regulated flight to suppress sector overloads while minimising the cost of the chosen policy. We model this problem with a mixed integer linear programme and solve it with a branch-and-price approach. The pricing sub-problem looks for feasible trajectories in a dynamic three-dimensional (3D) network and is solved with a specific algorithm based on shortest path labelling algorithms and on dynamic programming. Each algorithm is tested on real-world data corresponding to a complete traffic day in the European air traffic system; experimental results, including computing times measurement, validate the solution process.     

Integrating short turning and deadheading in the optimization of transit services

Urban transit demand exhibits peaks in time and space, which can be efficiently served by means of different fleets, increasing frequencies in those groups of stops with larger passenger inflow. In this paper we develop a model that combines short turning and deadheading in an integrated strategy for a single transit line, where the optimization variables are both of a continuous and discrete nature: frequencies within and outside the high demand zone, vehicle capacities, and those stations where the strategy begins and ends. We show that closed solutions can be obtained for frequencies in some cases, which resembles the classical “square root rule”. Unlike the existing literature that compares different strategies with a given normal operation (no strategy - single frequency), we use an optimized base case, in order to assess the potential benefits of the integrated strategy on a fair basis. We found that the integrated strategy can be justified in many cases with mixed load patterns, where unbalances within and between directions are observed. In general, the short turning strategy may yield large benefits in terms of total cost reductions, while low benefits are associated with deadheading, due to the extra cost of running empty vehicles in some sections.     

Public regulation and passengers importance in port infrastructure costs

Because ports are conceived and designed mainly to be the transfer point of various types of freight, passengers tend to be forgotten in the analysis of port costs. In this paper first we investigate the importance of passengers in port infrastructure costs by means of a multi-output cost function estimated from 20 annual observations (1986-2005) for 26 Spanish Port Authorities. Results show that, although a passenger weights on average less than one tenth of a ton, he or she represents as much as two tons of solid bulk and about three tons of containerized general cargo in terms of marginal costs. Secondly, we compare the marginal costs of different cargoes with their price caps established by law. Results suggest that some type of second best pricing is induced by present regulation.     

Understanding individual travel decisions: results from a commuters survey in Geneva

In this paper, we present the results of an extended traveler behavior survey conducted in Geneva (Switzerland) in March 1994. In this survey, commuters were asked about the impact of various factors, related to individual or household characteristics and situational, contextual and environmental constraints on their basic travel decisions. In particular, the issues of mode, route and departure time choice were investigated, together with the diversion from normal patterns in response to adverse weather conditions. Some cross cultural comparisons are discussed with respect to the results of a similar survey conducted in Brussels (Belgium) in 1992 (Khattak & de Palma 1995, 1997).     

Multioutput analysis of cargo handling firms: An application to a Spanish port

Cargo handling in ports is a multioutput activity, as freight can arrive in many forms such as containers, bulk, rolling stock, or non-containerised general cargo. In this paper, the operation of cargo handling firms in a Spanish port is analysed through the estimation of a multioutput cost model that uses monthly data on three representative firms located at the Las Palmas port. This permits the calculation of product specific marginal costs, economies of scale (general and by firm) and economies of scope, which help identifying optimal pricing policies and the potential cost advantages of increasing production.     

Generating twins to build weekly time use data from multiple single day OD surveys

Origin-Destination surveys, which are regularly conducted in many cities (to calibrate transport models), contain indirect information on individual time use that can be recovered through the declared trip purpose. Although this data source is very rich, it has two limitations for the calibration of time use models: the level of disaggregation regarding time use is constrained by the definition of trip purposes, and the information gathered on different time periods is usually obtained from different individuals. In this paper we propose a new method to overcome the second limitation, transforming the original daily observations into individual-weeks. For every working day observation we build Saturday and Sunday “twins” as a convex combination of observed weekend individuals such that the distance between the attributes of the working day individual and the synthetic twin is minimized. We applied this procedure to the Santiago OD survey, and generated a database of weekly observations particularly rich for model calibration and segmentation.