An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition,planning and cost

National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment.Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain.Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value.A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation.     

Engineering condition assessment of cycling infrastructure: Cyclists’ perceptions of satisfaction and comfort

The UK National Cycle Network comprises 23,660 km of cycling and walking paths of which a significant percentage is dedicated off-road infrastructure. This represents a significant civil engineering infrastructure asset that currently contributes to the provision of a sustainable transport mode option nationwide. Commuting and recreational cyclists have observed the often hazardous conditions on these paths. There are various simple measures that could be taken to improve the maintenance of such off-road paths. Reliance on walk-over surveys (direct visual inspection) and path users notifying the local authority may not be tackling maintenance in a resource efficient manner. The proposed inspection method includes the use of an instrumented bicycle to examine cycle path condition through user perception of satisfaction and quality. A questionnaire was conducted to identify the attributes of off-road cycling infrastructure people find most important in relation to their personal satisfaction. An exploratory factor analysis was undertaken on perception study data to elucidate the determination of the variables associated with perceived user satisfaction. The study has shown that people find maintenance issues to be of high importance, especially surface issues. From exploratory factor analysis of results, satisfaction has been found to load with comfort and safety. Field testing was then conducted using subjective user opinions and objective vibration data. These results were then used to assist the creation of dedicated user perception based surface condition rating-scales.     

Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS

It is generally accepted that compliance behavior is affected by many factors. The purpose of this study is to investigate the effects of diverse factors on drivers’ guidance compliance behaviors under road condition information shown on graphic variable message sign (VMS), and based on this to find out a better information release mode. The involved data were obtained from questionnaire survey, and ordinal regression was used to analyze the casual relation between guidance compliance behavior and its influencing factors. Based on an overall analysis of conditions in driver’s route choice, an accurate method was proposed to calculate the compliance rate. The model testing information indicated that ordinal regression model with complementary log–log being the link function was appropriate to quantify the relation between the compliance rate and the factors. The estimation results showed that age, driving years, average annual mileage, monthly income, driving style, occupation, the degree of trust in VMS, the familiarity with road network and the route choice style were significant determinants of guidance compliance behavior. This paper also compared two different guidance modes which were ordinary guidance mode (M1) and predicted guidance mode (M2) through simulation. The average speed fluctuations and average travel time supported that M2 had better effect in improving traffic flow and balancing traffic load and resource. Some detailed suggestions of releasing guidance information were proposed with the explanation by flow-density curve and variation of traffic flows. These findings are the foundation to design and improve guidance systems by assessing guidance effect and modifying guidance algorithm.     

EFECT – evaluation framework of environmental impacts and costs of transport initiatives

EFECT is a generalised methodological framework for evaluating the impacts resulting from transportation projects with a specific orientation to environmental impacts. The innovative aspect of the methodological framework is the combination of Multi-Criteria Analysis (MCA) with Cost-Benefit Analysis (CBA) methods to come up with an overall assessment of transport initiatives’ impacts over different geographical regions and time periods. Thus, it addresses both spatial and time impacts of transportation networks for all modes. The framework comprises four steps: structuring, weighting, rating, and exploring. Uncertainty is explicitly treated in the framework through fuzzy sets or, indirectly, through sensitivity testing. EFECT, using an additive function combining MCA and CBA methods, provides simplicity and intuitive understanding of results. This allows the use of either a core approach with a basic set of criteria and weights, or the application of a more detailed evaluation, when needed. The way EFECT is applied and the results produced are presented through a case-study example.     

Vulnerability and resilience of transport systems – A discussion of recent research

The transport system is critical to the welfare of modern societies. This article provides an overview of recent research on vulnerability and resilience of transport systems. Definitions of vulnerability and resilience are formulated and discussed together with related concepts. In the increasing and extensive literature of transport vulnerability studies, two distinct traditions are identified. One tradition with roots in graph theory studies the vulnerability of transport networks based on their topological properties. The other tradition also represents the demand and supply side of the transport systems to allow for a more complete assessment of the consequences of disruptions or disasters for the users and society. The merits and drawbacks of the approaches are discussed. The concept of resilience offers a broader socio-technical perspective on the transport system’s capacity to maintain or quickly recover its function after a disruption or a disaster. The transport resilience literature is less abundant, especially concerning the post-disaster phases of response and recovery. The research on transport system vulnerability and resilience is now a mature field with a developed methodology and a large amount of research findings with large potential practical usefulness. The authors argue that more cross-disciplinary collaborations between authorities, operators and researchers would be desirable to transform this knowledge into practical strategies to strengthen the resilience of the transport system.     

Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input–Output structural decomposition analysis

Decoupling road freight transport from economic growth has been acknowledged by the European Union as a key means to improving sustainability. It is therefore important to identify both the coupling and decoupling drivers of road freight transport demand in order to determine possible factors that may contribute to reduce road transport in the future without curbing economic development. This research proposes an Input–Output (IO) structural decomposition analysis (SDA) to explain road freight transport in terms of a set of key factors that have strongly influenced road freight demand in recent decades in European countries—such as economic growth, economic structure and the evolution of road transport intensity (including improvements in both supply and transport systems). This methodological approach allows us to quantify and compare their contribution in different European countries to either increase or decrease road freight transport demand. The empirical basis for this analysis is a dataset of nine European countries which have IO tables and road transport data available from 2000 to 2007, comprising data on domestic production, imports and exports as well as tonne-kms for 11 types of commodity classes. The results show that, as a whole, aggregate road transport demand has grown—driven mainly by economic activity—but this growth has been strongly curbed in some countries by changes in road freight transport intensity and moderately by the dematerialization of the economy. International transport has been also proven to be a key factor driving road freight transport volumes. Moreover, the increased penetration of foreign operators in national haulage markets appears to have reinforced the final decoupling levels observed in some cases.     

The cumulative effect of nuisances from road transportation in residential sectors on the Island of Montreal – Identification of the most exposed groups and areas

Air pollution and road traffic noise are considered to be the two most important nuisances that could negatively affect the quality of life. A prolonged exposure to high concentrations of these pollutants could conduct to various health problems. Studies in environmental equity have often considered these nuisances individually whenever it comes from the same source. The main objective of this paper is to determine if the 15 years of age, those aged 65 and over, visible minorities and low income individuals located in a portion of the Island of Montreal are overrepresented in city blocks characterized by having among the highest levels of transportation-related air pollutants (i.e., ambient concentrations of NO₂ and road traffic noise in decibels (dB(A)). The results show that low-income individuals and, to a lesser extent, visible minorities, are significantly overrepresented in city blocks characterized by the higher levels of NO₂ and road traffic noise in dB(A). Multinomial logistic regression analysis confirms these results, and also shows that young people under 15 years are under-represented in the most polluted areas. However, contrary to the previous bivariate results, people aged 65 and over are negatively and significantly associated with the likelihood of their living in a city block located in an advantaged area after controlling for the independent effects of the other explanatory variables. Moreover, visible minorities are significantly overrepresented in advantaged areas. Considering the observed results, some solutions are identified to reduce road traffic noise and air pollution in the city blocks localized near major traffic arteries.     

Impacts of combining partial and general equilibrium modelling in freight transport analyses – a forest sector case study from Norway

Abstract

The forest sector in Norway is very transport intensive, accounting for approximately 14% of total domestic freight transport traffic on Norwegian roads. This paper presents an analysis linking a general equilibrium freight transport modelling tool with a partial equilibrium model of the forest sector. The freight transport model predicts transport costs, modal split and transport patterns, and the results are treated as inputs to the forest sector model. The objective of the paper is to analyse the modelling effect of taking forest sector model effects back into the freight transport model and treated as new demand. Compared to a base scenario for the year 2020, we compare analyses with and without this new demand from the forest sector model back into the freight transport modelling tool.     

Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model

In this paper, we apply Bhat and Dubey’s (2014) new probit-kernel based Integrated Choice and Latent Variable (ICLV) model formulation to analyze children’s travel mode choice to school. The new approach offered significant advantages, as it allowed us to incorporate three latent variables with a large data sample and with 10 ordinal indicators of the latent variables, and still estimate the model without any convergence problems. The data used in the empirical analysis originates from a survey undertaken in Cyprus in 2012. The results underscore the importance of incorporating subjective attitudinal variables in school mode choice modeling. The results also emphasize the need to improve bus and walking safety, and communicate such improvements to the public, especially to girls and women and high income households. The model application also provides important information regarding the value of investing in bicycling and walking infrastructure.     

Transportation mode detection – an in-depth review of applicability and reliability

The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed by data insufficiency, ethics and privacy skepticism. The research problems whose study require hard-to-obtain data (e.g. transportation mode detection, service contextualisation, etc.) have now become more accessible to scientists because of the availability of data collecting outlets. One such problem is the detection of a user's transportation mode. Different fields have approached the problem of transportation mode detection with different aims: Location-Based Services (LBS) is a field that focuses on understanding the transportation mode in real-time, Transportation Science is a field that focuses on measuring the daily travel patterns of individuals or groups of individuals, and Human Geography is a field that focuses on enriching a trajectory by adding domain-specific semantics. While different fields providing solutions to the same problem could be viewed as a positive outcome, it is difficult to compare these solutions because the reported performance indicators depend on the type of approach and its aim (e.g. the real-time availability of LBS requires the performance to be computed on each classified location). The contributions of this paper are three fold. First, the paper reviews the critical aspects desired by each research field when providing solutions to the transportation mode detection problem. Second, it proposes three dimensions that separate three branches of science based on their main interest. Finally, it identifies important gaps in research and future directions, that is, proposing: widely accepted error measures meaningful for all disciplines, methods robust to new data sets and a benchmark data set for performance validation.     

Cost escalations in the front-end of projects – empirical evidence from Norwegian road projects

This paper investigates an issue largely ignored in the transport literature on cost overruns, namely, cost increases in the early project phase, long before the decision to build is made. This is the phase of project planning that is referred to as the front-end phase in the literature. The rationale of the study is that unless cost estimates during the front-end phase are relatively accurate, the wrong projects may be selected for further development. We first argue for why it is important to address cost escalation during the front-end phase of project planning. We then use Norwegian data to demonstrate the magnitude of cost escalations during the front-end phase of projects and in comparison to the implementation phase. We find that even in a sample of projects with relatively small cost overruns as in the case of Norway, there are substantial cost increases before the formal decision to build was made. This raises the issue of whether decisions and priorities taken at the early stages of project development are based on false information and whether this may lead to the wrong project concepts being selected.     

Intelligent transportation system and traffic safety – drivers perception and acceptance of electronic speed checkers

Intelligent Transportation System (ITS) can play an important role in reducing risks and increasing traffic safety. Discussion as to whether a technological approach or a behavioral approach is the right way to achieve a safer traffic environment forms a point of departure for this paper. On the one hand, there are the technicians who emphasize technology as the way towards safer traffic. Behaviorists, on the other hand, view the drivers’ behavior as fundamental and argue that education and incentive-oriented policies are essential in order to influence the driver and therefore increase traffic safety. Independent of the approach advocated a successful outcome of either a technological improvement, or an information campaign, has to be based on a high level of acceptance among potential users. In order to increase traffic safety, it is therefore essential to recognize driver motivation and attitudes. In this paper we focus on drivers’ attitudes towards risk, traffic safety and safety measures. A study of drivers’ attitudes and acceptance of an electronic device for speed checking (which the drivers tested for nine months) indicated a high acceptance level. The drivers perceived that they had both become more aware of traffic regulations and behaved in accordance with safety regulations.     

The call of the road: factors predicting students’ car travelling intentions and behaviour

The most common daily trip for employed persons and students is the commute to and from work and/or place of study. Though there are clear environmental, health and safety benefits from using public transport instead of private vehicles for these trips, a high proportion of commuters still choose private vehicles to get to work or study. This study reports an investigation of psychological factors influencing students’ travel choices from the perspective of the Theory of Planned Behaviour (TPB). Students from three different university campuses (n = 186) completed a cross-sectional survey on their car commuting behaviour. Particular focus was given to whether car commuting habits could add to understanding of commuting behaviour over and above behavioural intentions. Results indicated that, as expected, behavioural intention to travel by car was the strongest TPB predictor of car commuting behaviour. Further, general car commuting habits explained additional variance over and above TPB constructs, though the contribution was modest. No relationship between habit and intentions was found. Overall results suggest that, although student car commuting behaviour is habitual in nature, it is predominantly guided by reasoned action. Implications of these findings are that in order to alter the use of private vehicles, the factors influencing commuters’ intentions to travel by car must be addressed. Specifically, interventions should target the perceived high levels of both the acceptability of commuting by car and the perceived control over travel undertaken by private vehicle.     

Does the aviation Emission Trading System influence the financial evaluation of new airplanes? An assessment of present values and purchase options

In this paper we assess the impact of the CO₂ costs for short- and long-haul aircraft based on present values and on purchase options. We evaluate purchase options with a framework developed for real option analysis to estimate the value of flexibility under uncertain kerosene and CO₂ prices. We find an average influence of CO₂ costs on present values of €1.1 million for the short haul plane and €4.1 million for the long-haul plane over the typical lifetime of an airplane. For purchase options, we find a CO₂ influence of €0.43 million for the long-haul plane and a moderate impact for the short-haul plane. The results underline the importance of CO₂ and kerosene costs for long-haul aircraft.     

Using DEA models to jointly estimate service quality perception and profitability – Evidence from international airports

With increasing competition between airports and a growing share of non-aeronautical revenues, particularly at large international hubs, perceived quality and consumer satisfaction have not only become a key focus of management but potentially the most important tool to achieve or maintain a competitive advantage. However, in the long run stakeholders aim for profit maximisation and it has been shown for other parts of the aviation supply chain that quality does significantly impact on profitability. In this paper we aim to investigate whether perceived airport quality has an impact on airport profit margins. We further apply two-stage Data Envelopment Analysis (DEA) models to estimate a single efficiency measure that combines the potentially conflicting indicators of perceived service quality and profitability for the airport context. We also identify determinants of the jointly estimated single quality/profitability measure.     

All work and no play? The role of instrumental and affective factors in work and leisure journeys by different travel modes

This paper examines the relative importance that people attach to various instrumental and affective journey attributes when travelling either for work or for a leisure day trip and presents how journeys by various travel modes score on these attributes. Although not a comparative paper, data are presented for two studies which used some identical measurements: one on commuter journeys and one on leisure journeys. The results show that for work journeys, respondents tend to attach more importance to instrumental aspects, and especially to convenience than to affective factors. For leisure journeys, however, respondents appear to attach almost equal importance to instrumental and affective aspects, particularly flexibility, convenience, relaxation, a sense of freedom and ‘no stress’. Each study also examines (i) how regular users’ evaluate their own mode and (ii) how car users perceive the performance of alternative modes compared to their importance ratings. This ‘gap’ analysis reveals on which modes and for which attributes the greatest deficiencies in performance lie. The data for both the work and leisure studies shows that for car users, alternative transport modes are inferior on the salient attributes such as convenience and flexibility even though car users rate modes such as walking and cycling as performing well, if not better, on less important attributes such as the environment, health and even excitement. Nevertheless, for those who cycle and walk regularly, satisfaction with their own travel mode as measured by the gap between importance and performance on salient attributes is better than for those who mostly use the car. Conclusions are made as to how greater attention to affective factors may improve our understanding of mode choice.     

Effects of new bus and rail rapid transit systems – an international review

Cities worldwide are implementing modern transit systems to improve mobility in the increasingly congested metropolitan areas. Despite much research on the effects of such systems, a comparison of effects across transit modes and countries has not been studied comprehensively. This paper fills this gap in the literature by reviewing and comparing the effects obtained by 86 transit systems around the world, including Bus Rapid Transit (BRT), Light Rail Transit (LRT), metro and heavy rail transit systems. The analysis is twofold by analysing (i) the direct operational effects related to travel time, ridership and modal shifts, and (ii) the indirect strategic effects in terms of effects on property values and urban development. The review confirms the existing literature suggesting that BRT can attract many passengers if travel time reductions are significantly high. This leads to attractive areas surrounding the transit line with increasing property values. Such effects are traditionally associated with attractive rail-based public transport systems. However, a statistical comparison of 41 systems did not show significant deviations between effects on property values resulting from BRT, LRT and metro systems, respectively. Hence, this paper indicates that large strategic effects can be obtained by implementing BRT systems at a much lower cost.     

Comparative effects of eco-driving initiatives aimed at urban bus drivers – Results from a field trial

A field trial is used to investigate effects of two programmes aimed at encouraging bus drivers to develop and maintain ecological driving behaviour. Drivers on one bus line were divided into three groups, one received feedback from an in-vehicle system, the second received the same feedback coupled with personal training sessions, and the third acting as a control. A 6.8% fuel saving and large decreases in instances of harsh deceleration and speeding were found, but with no difference in the effect of the two eco-driving strategies. The drivers reported perceived gains in theoretical knowledge of eco-driving, but found it more difficult to put that knowledge into practice. Several contextual factors were found to limit drivers’ to eco-driving, most noticeably shaped by their work tasks, but also the commitment of the company where they were employed.     

Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts

This paper proposes a generalized model to estimate the peak hour origin–destination (OD) traffic demand variation from day-to-day hourly traffic counts throughout the whole year. Different from the conventional OD estimation methods, the proposed modeling approach aims to estimate not only the mean but also the variation (in terms of covariance matrix) of the OD demands during the same peak hour periods due to day-to-day fluctuation over the whole year. For this purpose, this paper fully considers the first- and second-order statistical properties of the day-to-day hourly traffic count data so as to capture the stochastic characteristics of the OD demands. The proposed model is formulated as a bi-level optimization problem. In the upper-level problem, a weighted least squares method is used to estimate the mean and covariance matrix of the OD demands. In the lower-level problem, a reliability-based traffic assignment model is adopted to take account of travelers’ risk-taking path choice behaviors under OD demand variation. A heuristic iterative estimation-assignment algorithm is proposed for solving the bi-level optimization problem. Numerical examples are presented to illustrate the applications of the proposed model for assessment of network performance over the whole year.