A decision support approach for condition-based maintenance of rails based on big data analysis

In this paper, a decision support approach is proposed for condition-based maintenance of rails relying on expert-based systems. The methodology takes into account both the actual conditions of the rails (using axle box acceleration measurements and rail video images) and the prior knowledge of the railway track. The approach provides an integrated estimation of the rail health conditions to support the maintenance decisions for a given time period. An expert-based system is defined to analyse interdependency between the prior knowledge of the track (defined by influential factors) and the surface defect measurements over the rail. When the rail health conditions is computed, the different track segments are prioritized, in order to facilitate grinding planning of those segments of rail that are prone to critical conditions. In this paper, real-life rail conditions measurements from the track Amersfoort-Weert in the Dutch railway network are used to show the benefits of the proposed methodology. The results support infrastructure managers to analyse the problems in their rail infrastructure and to efficiently perform a condition-based maintenance decision making.     

客运营销辅助决策支持系统的研究

分析客运营销辅助决策支持系统所包含的主要系统功能:客运市场调查与分析预测、运营策划、分析与评价,并在此基础上归纳总结系统所需的关键预测技术和方法,以便客运营销辅助决策支持系统的研究和创新.     

Using intelligent agents for Transportation Regulation Support System design

This paper presents an agent-based approach used to design a Transportation Regulation Support System (TRSS), that reports the network activity in real-time and thus assists the bus network regulators. The objective is to combine the functionalities of the existing information system with the functionalities of a decision support system in order to propose a generic model of a traffic regulation support system. Unlike the other approaches that only deal with a specific task, the original feature of our generic model is that it proposes a global approach to the regulation function under normal conditions (network monitoring, dynamic timetable management) and under disrupted conditions (disturbance assessment and action planning of feasible solutions). Following the introduction, the second section presents the notions of the domain and highlights the main regulation problems. The third section details and motivates our choice of the components of the generic model. Based on our generic model, in the fourth section, we present a TRSS prototype called SATIR (Système Automatique de Traitement des Incidents en Réseau – Automatic System for Network Incident Processing) that we have developed. SATIR has been tested on the Brussels transportation network (STIB). The results are presented in the fifth section. Lastly, we show how using the multi-agent paradigm opens perspectives regarding the development of new functionalities to improve the management of a bus network.     

Economic effects of air transport market liberalization in Africa

Although the aviation industry is increasingly becoming important for Africa’s economic development and integration, the ability of airlines to access foreign markets remains hindered by restrictive regulatory policies. Attempts have been made to fully liberalize the intra-African air transport market. Except for general assertions about the merits/demerits of liberalization, our empirical understanding of the welfare effects of such polices in Africa remains rudimentary. This study empirically measures the economic effects of air transport liberalization, mainly on two supply side variables: fare and service quality, measured as departure frequency. The empirical models evaluate how air fares and departure frequency respond to measures of openness in air services agreements, while controlling for other determinants. The results show up to 40% increase in departure frequency in routes that experienced some type of liberalization compared to those governed by restrictive bilateral air service agreements. Furthermore, there is a relatively larger increase in departure frequency in routes which experienced partial liberalization compared to fully liberalized ones. This can be explained by the diminishing marginal effect of progressive liberalization on departure frequency. While the effect of liberalization is substantial in improving service quality, there is no evidence of its fare reducing effect.     

Contrasts between utility maximisation and regret minimisation in the presence of opt out alternatives

An increasing number of studies of choice behaviour are looking at Random Regret Minimisation (RRM) as an alternative to the well established Random Utility Maximisation (RUM) framework. Empirical evidence tends to show small differences in performance between the two approaches, with the implied preference between the models being dataset specific. In the present paper, we discuss how in the context of choice tasks involving an opt out alternative, the differences are potentially more clear cut. Specifically, we hypothesise that when opt out alternatives are framed as a rejection of all the available alternatives, this is likely to have a detrimental impact on the performance of RRM, while the performance of RUM suffers more than RRM when the opt out is framed as a respondent being indifferent between the alternatives on offer. We provide empirical support for these hypotheses through two case studies, using the two different types of opt out alternatives. Our findings suggest that analysts need to carefully evaluate their choice of model structure in the presence of opt out alternatives, while any a priori preference for a given model structure should be taken into account in survey framing.     

A behavioural comparison of route choice on metro networks: Time,transfers, crowding,topology and socio-demographics

Understanding travellers’ behaviour is key element in transportation planning. This article presents a route choice model for metro networks that considers different time components as well as variables related to the transferring experience, train crowding, network topology and socio-demographic characteristics. The route choice model is applied to the London Underground and Santiago Metro networks, to make a comparison of the decision making process of the users on both cities. As all the variables are statistically significant, it is possible to affirm that public transport users take into account a wide variety of elements when choosing routes. While in London the travellers prefer to spend time walking, in Santiago is preferable to spend time waiting. Santiago Metro users are more willing to travel in crowded trains than London Underground users. Both user groups have a similar dispreference to transfers after controlling for the time spent on transfer, but different attitudes to ascending and descending transfers. Topological factors presented on a distorted Metro map are more important than actual topology to passengers’ route choice decisions.     

Impact of service network topology on air transportation efficiency

Each stakeholder in the air transportation system has a different perspective on the performance efficiency metrics, making analysis of system-wide design options very difficult. This paper uses topological structures of service networks to examine trade-offs between efficiency metrics established around the passenger, airline, and air navigation service provider perspectives. The findings indicate that the scale-free type topologies are preferred under most of the metrics. However, with enough density, random topologies become more appealing with its high robustness feature and performance comparable to scale-free.     

Design and evaluation of railway corridors based on spatial ecological and geological criteria

Transport infrastructure is closely linked to several sustainability issues of main policy relevance, and significant impacts on biodiversity as well as resource use and construction costs relate to the corridor design and location in the landscape. The aim of this study was to develop methods for railway corridor planning, in which corridor design and location would be based on important ecological and geological sustainability criteria. The method, an MCA framework including both spatial and non-spatial MCA, was demonstrated on a railway planning proposition in an urbanising area north of Stockholm, Sweden. Alternative spatial alignments for 6 railway corridors were derived based on criteria representing biodiversity, resource efficiency and costs, developed from ecological and geological knowledge, data and models. The method identified a study area specific positive synergy between ecological and geological sustainability criteria. The evaluation part of the methodology could furthermore identify uncertainties in the input data and assumptions and conflicts between ecological criteria. In order to arrive at a well-informed decision support system, the criteria as well as the decision rules employed could be further elaborated. Other relevant sustainability issues would also need to be integrated, such as cultural landscapes, recreation, and other ecosystem services. Still, arriving at a corridor design informed by the ecological and geological conditions in the planned area, as demonstrated by this study, could improve the sustainability performance of transport infrastructure planning.     

Time-dependent green vehicle routing problem with stochastic vehicle speeds: An approximate dynamic programming algorithm

This paper addresses a Time Dependent Capacitated Vehicle Routing Problem with stochastic vehicle speeds and environmental concerns. The problem has been formulated as a Markovian Decision Process. As distinct from the traditional attempts on the problem, while estimating the amount of fuel consumption and emissions, the model takes time-dependency and stochasticity of the vehicle speeds into account. The Time Dependent Capacitated Vehicle Routing Problem is known to be NP-Hard for even deterministic settings. Incorporating uncertainty to the problem increases complexity, which renders classical optimization methods infeasible. Therefore, we propose an Approximate Dynamic Programming based heuristic as a decision aid tool for the problem. The proposed Markovian Decision Model and Approximate Dynamic Programming based heuristic are flexible in terms that more environmentally friendly solutions can be obtained by changing the objective function from cost minimization to emissions minimization. The added values of the proposed decision support tools have been shown through computational analyses on several instances. The computational analyses show that incorporating vehicle speed stochasticity into decision support models has potential to improve the performance of resulting routes in terms of travel duration, emissions and travel cost. In addition, the proposed heuristic provides promising results within relatively short computation times.     

A multi criteria decision analysis technique for including environmental impacts in sustainable infrastructure management business practices

This paper presents a decision analysis technique to allow highway agencies to assess the tradeoffs between costs, condition and energy consumption. It is shown how the entire feasible solution space can be evaluated between multiple stakeholders with differing values to assess the desirability of the outcomes resulting from infrastructure management decisions. Furthermore, an example network-level analysis is presented using data from the Virginia Department of Transportation. The example analysis clearly shows a tradeoff between the most cost effective outcomes (i.e., minimizing the cost divided by the condition) and the outcomes where the energy consumption is minimized, and how decision analysis should account for this tradeoff. The results of the method presented in this paper show that various pavement management alternatives can be represented in terms of desirability, and that this desirability can assist the decision maker with making decisions about performance goals and targets.