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The multiplicity of stakeholders in urban contexts can greatly increase the complexity of transportation systems. Since all stakeholders depend, to varying degrees, on the same data to get the information for their mobility, this work considers that an integrated information system, focused on their different needs, will significantly improve the efficiency of transportation systems. A stakeholder-focused system makes the provided information more relevant, while an integrated system fosters the sharing of the data that generates this information. To build such a system, a conceptual framework focused on stakeholders and their decision processes was developed. This new framework takes advantage of existing ones, such as the Zachman framework, the Enterprise Architecture Design, and the Multilevel Service Design. The proposed multidisciplinary approach, putting together information systems (IS) and service design concepts, has considerable potential in ensuring that the right information reaches each stakeholder at the right time.

In their quest for sustainability, cities design and deploy smart mobility solutions aiming to improve the efficiency and management of transportation systems and to provide better services to citizens. Those solutions are often based on Information and Communication Technologies (ICT) and on digital services, but their maintenance and management are a greater challenge than their implementation. Problems can be difficult to identify since they can be exogenous or endogenous to the service provider. Usually, in their effort to maintain good service levels, companies implement complex and expensive information systems that use sensors to monitor infrastructure and hardware but ignore other sources of valuable information. In a digitalized world, customers easily report problems that are a cause of lower quality of service and worse user experience. However, for several reasons, service providers do not always pay due attention to these complaints. As communication channels are already open, we claim that customer participation through these reports can be used to significantly enhance the delivery and quality of mobility services. In this work we propose a methodology that takes advantage of customers’ participation in the maintenance and management of smart city solutions. With this methodology, we aim to redesign the process of customer interaction with service providers in order to improve the overall efficiency and the service experience. Our research is based on a case study from a public transport service in the metropolitan area of Porto, in Portugal.

A set of processes, including the collection of heterogeneous data and in-depth knowledge on multiple dimensions, are required to enhance multimodal public transport services and address traveller needs in an effective and efficient way. The main purpose of this paper is to use reliability data to drive the planning and operationalisation of a multimodal metropolitan-wide network of public transport, covering the needs of authorities, transport providers and travellers. This will be achieved by a methodology using data from current public transport lines and design process to find the best combination of hubs, stops and connections, fully controlled by the transport authority and with the assistance of transport providers. The expect result is a more "predictable" network that maximises schedule reliability, while providing better information for travellers.

This article is about making decisions concerning the management of sustainability, decisions that may influence the use or protection of natural resources or address difficult societal choices. Managers have more and more to tackle a diversity of problems in a rigorous and transparent way. One of the distinctive features of these decisions is that managers must give attention to both the values of people affected and factual information concerning the potential consequences of actions. This imposes the adoption of new methods for structuring spaces, strategy alternatives, and organizational planning. The support from operational research analysts becomes increasingly important, as we are dealing with people mostly without strong quantitative or model-building backgrounds. With the presence of different perspectives and mental models, behavior elements are at the core of the problem and unintentional biases in model use may occur. Our intention is to help promote the transference of knowledge to and within companies so that they may assure resilience. We found in general morphological analysis a great help for that. We want to make available a meta-model based on Operational Research for fields involving public resources and multiple interests to aid current and future managers of companies. We conclude the article with two case studies to illustrate our approach.

Designing mobility policies and solutions in modern congested cities is a considerable challenge, as we have to respond simultaneously to the needs of multiple actors and activities. Multimodal networks have a great potential to provide higher levels of service, and to improve system efficiency and sustainability. A smart integration of modes, along with well-designed interfaces and multi-platform information systems, can address a diverse and dynamic demand from varied types of travelers (residents, visitors) and trip purposes (loading/unloading, services access). In cargo transport, vehicle dimensions, pollutant emissions or time/zone windows have also to be taken into account. To help the design of these nets, and to promote the involvement of different stakeholders (citizens, authorities, business owners, transport operators, service providers), we have created a conceptual framework based on multicriteria models and service design approaches, and a Decision Support System to implement this framework.

Decision-making processes are essential in the design and operation of transportation systems. Multiple actors interact through these systems and their decisions may significantly influence each other actions, both at a strategic level and an operational and real time level. However, those decisions are often based on the same or similar data. Planners are interested in knowing congestion points to manage traffic, transport operators want to prevent delays, and travelers try to choose the best route for their trips. In this context, multimodal networks have a great potential to provide higher levels of service, and to improve system efficiency and city sustainability. Managing a multimodal network with multiple stakeholders can be achieved through integration and collaboration, and a smart incorporation of modes, along with well-designed interfaces and multi-platform information systems. In such a context, a diverse and dynamic demand from varied types of travelers (residents, visitors) and trip purposes (loading/unloading, services access) needs to be addressed. In cargo transport, vehicle dimensions, pollutant emissions or time/zone windows have also to be taken into account. To help decision-making processes in such multi-stakeholder contexts, we have created a conceptual framework for an integrated information system based on Enterprise Architecture Frameworks and Service Design approaches. Since this information system will be capable of integrating different data sources and provide different information for different stakeholders, the framework can hopefully be used in quite different contexts. In this work, we use it to address urban mobility issues.

Public transport networks were, in the past, mainly designed to maximize the efficiency of commuting trips. However, with such perspective there are considerable risks to marginalize some specific population groups (e.g. disabled, elderly, children, pregnant, people in poverty). For enhancing social inclusion and improving the accessibility of more vulnerable citizens, such networks are often redesigned and adjusted. Nevertheless, even with such adjustments, it is sometimes difficult to provide efficient services that fully address the real needs and capabilities of travelers, partially because of the failure in following the fast technological and demanding changes of modern societies. Taking in mind these challenges, we have developed a conceptual model to support knowledge sharing and decision-making in urban mobility, and to improve the way travel information is addressed. The multi-user integrated platform proposed in this work is supported by the idea that information from different channels must be centralized, organized, managed and properly distributed. This idea is grounded in two main principles: (i) past and real-time information from a wide range of sources is combined for knowledge extraction, and such knowledge is going to be used not only to allow travelers to better plan their trips, but also to help transport providers to develop services adapted to the needs and preferences of their customers; and (ii) information is provided in a personalized way taking into account socio-economical differences between groups of travelers.

This paper presents a General Morphological Analysis (GMA) meta-model aiming to help decision-makers wishing to integrate sustainability concerns into the company strategy. This is made by joining Operational Research (OR) analysts, decision-makers and stakeholders as participants in the problem structuring and formulation process. This is particularly relevant in societal issues, where public transport companies are particularly important. Indeed, public transport companies play a quite visible role in the dimensions of corporate social responsibility, namely because of four reasons: (i) they provide daily services crucial to mass customers’ mobility; (ii) their investments are usually of high value and rather sensitive to technological development; (iii) they play a crucial role in the energy sector and (iv) are strongly dependent upon macro-policies.

Societies are facing complex challenges, which may impede a harmonious transition to future patterns in various fields. The strategic response must reconfigure society in such a way that the provision of critical resources and the resilience of the socio-technical systems are assured in the long-term. The implementation of a new dominant technology and paradigm in the transport context is a complex process. This complexity is multidimensional and requires seamless integration of a great number of features, which entail trade-offs in the decision-making process. In this paper, General Morphological Analysis (GMA) is used as a theoretical framework to help to achieve a schematic perspective of the transition management of transport to a new powertrain technology. This is presented as an illustration of a broader representation of all the possible solutions of a large-scale problem as it is the case of any multi-level process of governance leading to the pursuit of new paradigms. The original contribution of the paper lies on the fact that there is no application of GMA to address sustainable challenges in the transport sector using simultaneously the same framework at different levels of a system, in a multi-level perspective. The analysis of sustainable decisions requires the consideration of institutions (its political dimension) at different scales, in an interactive and integrated way.

Intelligent transportation systems based on automated data collection frameworks are widely used by the major transit companies around the globe. This paper describes the current state of the art on improving both planning and control on public road transportation companies using automatic vehicle location (AVL) data. By surveying this topic, the expectation is to help develop a better understanding of the nature, approaches, challenges, and opportunities with regard to these problems. This paper starts by presenting a brief review on improving the network definition based on historical location-based data. Second, it presents a comprehensive review on AVL-based evaluation techniques of the schedule plan (SP) reliability, discussing the existing metrics. Then, the different dimensions on improving the SP reliability are presented in detail, as well as the works addressing such problem. Finally, the automatic control strategies are also revised, along with the research employed over the location-based data. A comprehensive discussion on the techniques employed is provided to encourage those who are starting research on this topic. It is important to highlight that there are still gaps in AVL-based literature, such as the following: 1) long-term travel time prediction; 2) finding optimal slack time; or 3) choosing the best control strategy to apply in each situation in the event of schedule instability. Hence, this paper includes introductory model formulations, reference surveys, formal definitions, and an overview of a promising area, which is of interest to any researcher, regardless of the level of expertise.

This paper intends to analyze the performance of an electric bus for three different routes in the city of Oporto. The objective is to study the correlation between the type of route a bus travels and the amount of energy it spends in performing it. Besides energy, the potential of the recovering part of it through regenerative braking will also be discussed. It is expected that long and demanding routes, e.g. those encompassing meandering paths, will make the bus use more energy. To accomplish these objectives, a simulation platform was built upon both a nanoscopic representation of the electrical bus and its microscopic interaction with the road traffic network while performing different journeys through specific routes. Simulation results are compared and discussed, as well as are directions for future work identified., This work is financed by FEDER Funds, through the Operational Programme for Competitiveness Factors COMPETE, and by Portuguese Funds through FCT (Fundacao para a Ciencia e Tecnologia), under Project 13844. FCT is also acknowledged by its financial support through PhD scholarship grants SFRH/BD/167202/2009 and SFRH/BD/51256/2010, the latter within the MIT-Portugal Program in Engineering Design and Advanced Manufacturing Leaders for Technical Industries focus area.

Private individual transportation is becoming cumbersome and expensive, as urban traffic turns more chaotic, fuel prices increase and the effects of pollutant emissions become evident. Public buses are an attractive approach to reducing the cars in use, as they mostly depend on preexistent infrastructure. Making these buses electric would mean even less tailpipe emissions and cheaper consumption costs, when compared to conventional vehicle fleets. However, fully electric bus fleets can prove disadvantageous. We can tackle this with a more conservative approach - using mixed bus fleets, comprised by both electric and conventional buses. This work intends on studying how to obtain a good balance of the different vehicle typologies in the fleet. To fulfill these goals, real data of a bus network in Porto, Portugal, is studied and an evolutionary algorithm devises mixed fleet arrangements, with a brief sensitivity analysis giving us an overview of how to improve our results. As a means of decision support, this work contributes not only with an approach to configure optimized mixed bus fleets, but also with general considerations for managing public transit with electric vehicle fleets.

Graphical abstractDisplay Omitted HighlightsWe proposed a data driven method to predict Bus Bunching (BB) in real-time.Firstly, the bus headways are predicted combining Offline and Online Regression.Then, a BB likelihood is computed for each stop based on such predictions.Finally, a corrective action is selected and deployed using these likelihoods.This methodology is validated using one-year data of 18 real-world bus routes. Recent advances in telecommunications created new opportunities for monitoring public transport operations in real-time. This paper presents an automatic control framework to mitigate the Bus Bunching phenomenon in real-time. The framework depicts a powerful combination of distinct Machine Learning principles and methods to extract valuable information from raw location-based data. State-of-the-art tools and methodologies such as Regression Analysis, Probabilistic Reasoning and Perceptron's learning with Stochastic Gradient Descent constitute building blocks of this predictive methodology. The prediction's output is then used to select and deploy a corrective action to automatically prevent Bus Bunching. The performance of the proposed method is evaluated using data collected from 18 bus routes in Porto, Portugal over a period of one year. Simulation results demonstrate that the proposed method can potentially reduce bunching by 68% and decrease average passenger waiting times by 4.5%, without prolonging in-vehicle times. The proposed system could be embedded in a decision support system to improve control room operations.

In this paper we briefly present our feelings about urban logistic and its role in urban mobility. In some way, we can say that this is a position paper based on an extensive review of all known related published material. We support the development of new approaches for the management of passenger and freight transport together as a single logistics system; based on the access to more and more sophisticated flows of data and better communication means, we envisage the dissemination of sufficient information for the correct decision of every citizens between several mobility options in real time (especially with the support of mobile technology); and we sustain that new tools are needed to help the design of innovative business models and policies, and the change of habits and behaviors. We visualize urban logistics as a multi-stakeholder, multi-criteria and multimodal mobility dynamic system.

Education, like many institutions in contemporary society, faces significant challenges to the completion of its mission. This is especially true of higher education, which is often expected to be and seen as a facilitator of social and cultural advancement. Gamification is a relatively new concept intending to use elements from video games in non-game applications. Education is therefore an area with high potential for application of this concept since it seeks to promote peoples motivation and engagement. The research in progress aims at creating a model for applying gamification in a course of Human Resources Management for Engineers, where testing and validating the results of that application can be possible. This paper presents the state of the art of gamification in higher education, as well as some guidelines and main features of a gamification framework to be applied in the course of a Masters in Engineering.

This paper is about long-term travel time prediction in public transportation. However, it can be useful for a wider area of applications. It follows a heterogeneous ensemble approach with dynamic selection. A vast set of experiments with a pool of 128 tuples of algorithms and parameter sets (a&ps) has been conducted for each of the six studied routes. Three different algorithms, namely, random forest, projection pursuit regression and support vector machines, were used. Then, ensembles of different sizes were obtained after a pruning step. The best approach to combine the outputs is also addressed. Finally, the best ensemble approach for each of the six routes is compared with the best individual a&ps. The results confirm that heterogeneous ensembles are adequate for long-term travel time prediction. Namely, they achieve both higher accuracy and robustness along time than state-of-the-art learners.

This volume brings together works resulting from research carried out by members of the EURO Working Group on Transportation (EWGT) and presented during meetings and workshops organized by the Group under the patronage of the Association of European Operational Research Societies in 2012 and 2013. The main targets of the EWGT include providing a forum to share research information and experience, encouraging joint research and the development of both theoretical methods and applications, and promoting cooperation among the many institutions and organizations which are leaders at national level in the field of transportation and logistics. The primary fields of interest concern operational research methods, mathematical models and computation algorithms, to solve and sustain solutions to problems mainly faced by public administrations, city authorities, public transport companies, service providers and logistic operators. Related areas of interest are: land use and transportation planning, traffic control and simulation models, traffic network equilibrium models, public transport planning and management, applications of combinatorial optimization, vehicle routing and scheduling, intelligent transport systems, logistics and freight transport, environment problems, transport safety, and impact evaluation methods. In this volume, attention focuses on the following topics of interest: Decision-making and decision support Energy and Environmental Impacts Urban network design Optimization and simulation Traffic Modelling, Control and Network Traffic Management Transportation Planning Mobility, Accessibility and Travel Behavior Vehicle Routing

Operational planning at public transport companies is a complex process that usually comprises several phases. In the planning phase, schedules are constructed considering that buses arrive and depart as scheduled. Obviously, several disruptions frequently occur, but their impact on the operating conditions is not easy to estimate. This difficulty arises mostly due to the impossibility of testing different solutions under the same conditions. Indeed, typically, the available data are a result of the current plan, while new proposed solutions have not produced real data yet.

In some formulations of the vehicle replacement problem, in particular those leading to repair limit type models, the alternative policies are evaluated and compared over a fixed planning horizon. Although it has been widely recognised that the optimal policies derived under these formulations depend critically on the length of the horizon, no method has been presented so far to set appropriately this parameter. In this paper, the authors describe a method which overcomes this shortcoming. Once the best policy has been derived from a given finite horizon with length H, such a policy is repeated indefinitely over time and an equivalent annual rent is computed. The parametrisation of H leads to the definition of an annual rent function with a sequence of nearly equidistant local minima. It is suggested that in practice the second local minimum of this function leads to an adequate choice of the parameter H. The method can be applied both to stochastic and deterministic cost modelling situations. The method was tested using both real data from large samples of different types of passenger vehicles and artificially generated data.

Lecture Notes in Computer Science Volume 7619, 2012., In this paper we study the deviation of bus trip duration and its causes. Deviations are obtained by comparing scheduled times against actual trip duration and are either delays or early arrivals. We use distribution rules, a kind of association rules that may have continuous distributions on the consequent. Distribution rules allow the systematic identification of particular conditions, which we call contexts, under which the distribution of trip time deviations differs significantly from the overall deviation distribution. After identifying specific causes of delay the bus company operational managers can make adjustments to the timetables increasing punctuality without disrupting the service., (undefined)

This chapter also illustrates the potential of the proposed approach as a practical and readily implementable management decision aid in the context of a current case that involved the maintenance team of a Portuguese regional office of a worldwide equipment company.