Using a Machine Learning Approach to Implement and Evaluate Product Line Features

Bike-sharing systems are a means of smart transportation in urban environments with the benefit of a positive impact on urban mobility. In this paper we are interested in studying and modeling the behavior of features that permit the end user to access, with her/his web browser, the status of the Bike-Sharing system. In particular, we address features able to make a prediction on the system state. We propose to use a machine learning approach to analyze usage patterns and learn computational models of such features from logs of system usage. On the one hand, machine learning methodologies provide a powerful and general means to implement a wide choice of predictive features. On the other hand, trained machine learning models are provided with a measure of predictive performance that can be used as a metric to assess the cost-performance trade-off of the feature. This provides a principled way to assess the runtime behavior of different components before putting them into operation.Comment: In Proceedings WWV 2015, arXiv:1508.0338

Conceptualizing environmental effects of carsharing services: A system thinking approach

Emerging carsharing services and their interconnections with other modes of urban transport, regulations, car manufacturing and population have affected the dynamics of energy consumption, environmental pollution and greenhouse gas emission within a complex system. However, although some aspects of environmental impacts of transport sector have been investigated in the literature, well-deserved studies on the environmental effects of carsharing services following a system thinking approach is missing. This research aims at providing a comprehensive conceptual framework to systematize the interconnections between carsharing services and their environmental effects. To do this, system dynamics (SD) modeling, as a tool to simulate complex and dynamic systems, is applied and the proposed framework model is illustrated by using a causal-loop diagram (CLD). Along with analyzing the main identified causal loops within the presented CLD, relevant strategies are proposed to reduce the negative environmental effects associated with the carsharing services, considering the whole lifecycle of a shared vehicle. The proposed framework can help environment policy makers and shared mobility practitioners in long-term strategic decision-making. Moreover, it can be applied by the researchers as a basis for future research, not only for SD modeling but also other simulation and analysis structures

Investigating individual preferences for new mobility services: the case of “mobility as a service” products

In just a few years, the Mobility as a Service (MaaS) concept has gone from an idea discussed by very few, to being a prominent topic in any transportation related debate. However, within this time, there have only been few rigorous studies that explore the various aspects of MaaS. This thesis aims to contribute to existing knowledge by providing empirical evidence on individual preferences for MaaS plans and their components. In doing so, first desk-research is conducted to summarise existing MaaS schemes and outline the MaaS ecosystem. Next, MaaS surveys that are able to capture individual preferences for MaaS products are designed and specific challenges in the design process identified. The MaaS surveys, including MaaS plan stated preference experiments, are applied in two case study areas of London and Greater Manchester. Using the novel data collected, individual preferences for MaaS plans are examined using two distinct studies: (1) a mixed methods research conducted in London, which expands the survey by adding a qualitative (in-depth interview) element to examine user preferences for MaaS plans and the ways individuals choose between them; and (2) a latent class choice model based on data collected from Manchester to examine whether there is heterogeneity in preferences. Finally, implications for industry and policy stakeholders are discussed as well as interventions that can best support the widespread adoption of MaaS. The results of this thesis show there is interest in the concept of MaaS among potential users as many see value in a single app that integrates different transport modes into a single service. In general, individuals are hesitant in purchasing pre-payed MaaS plans and would be more comfortable with a pay-as-you-go product option. While many people are reluctant towards MaaS plans, the results indicate that heterogeneity exists in preferences towards them and there are different user groups based on socio-demographic characteristics and current mobility habits. Smaller, less expensive plans including modes such as public transport and bike sharing can be used to target students or middle-income people with have high overall mode usage. Larger, more expensive plans that include modes such as taxi and car sharing in addition to public transport, will be attritive to individuals who are likely younger, male, well-educated, have higher income and already use many transport modes. Older population groups, individuals with low income and those that do not use any transport modes or are uni-modal are least likely to adopt MaaS plans. The thesis also provides insights into individuals’ preferences towards transport modes within MaaS plans. The analysis showed that respondents classify modes within MaaS plans into three categories: ‘essential’ modes that are pivotal to the individual and which they most likely already frequently use; ‘considered’ modes are those that they would be willing to include but may not yet use; and ‘excluded’ modes are those that they definitely do not want in their plans and would eliminate any plan that included these. Public transport consistently proved to be an essential mode, while taxi, car sharing and bike sharing could be ‘essential’, ‘considered’ or ‘excluded’ depending on the characteristics of the individual. The main contributions of this thesis are the novel data collected in two case study cities about individuals’ preferences for MaaS plans and the findings gained through the analysis providing insights into possible target audiences and product designs for MaaS plans

Framework de Tomada de Decisão para Last-Mile Sustentável

The e-commerce growth, propelled by factors like globalization, urbanization, or the COVID-19 pandemic, has been raising the demand for logistic activities. This affects the entire supply chain, especially the last-mile, as it is considered the most ineffective part of the supply chain and a source of negative externalities. Although various solutions promise to alleviate these problems, understanding them and selecting the best has proven to be difficult due to conflicting criteria, multiple perspectives, and trade-offs. The vicissitudes of complex and sensitive urban contexts like historic centers also contribute to this difficulty. This work contributes an integrated framework that may assist the involved stakeholders in decision-making. To this end, this work is based on a three-part methodology. The extensive systematic literature review developed provided an integrated overview of this fragmented research area. This review confirmed the multidisciplinary nature of the topic, as there is an increasing number of studies conducted under very different perspectives. Furthermore, it was found that the economic dimension is the most considered; the most polluting countries contributed little to the research; and the solutions involve trade-offs. The literature review supported the definition of the hierarchical model that structures last-mile operations in historic centers. This model was evaluated by interviewing a group of experts. After integrating the experts’ feedback, the model was quantified by the same experts according to an AHP-TOPSIS approach. This quantification had as a case study the historic center of Porto, Portugal. The experts considered the three sustainability dimensions identically important. Air pollution was the most valued sub-criterion whereas Visual pollution was the least. All last-mile solutions considered in the model achieved similar results, therefore suggesting a combined distribution strategy. Nevertheless, the use of parcel lockers is the most favorable solution and seems adequate in Porto’s historic center.O crescimento do e-commerce, impulsionado por fatores como a globalização, a urbanização ou a pandemia de COVID-19, tem aumentado a procura por atividades logísticas. Isto afeta toda a cadeia de abastecimento, principalmente a última-milha, por ser considerada a parte mais ineficaz da cadeia de abastecimento e uma fonte de externalidades negativas. Embora existam várias soluções que prometem aliviar estes problemas, entendêlas e selecionar a melhor tem se provado difícil devido a critérios conflituosos, múltiplas perspetivas e trade-offs. As vicissitudes de contextos urbanos complexos e sensíveis como os centros históricos também contribuem para essa dificuldade. Este trabalho contribui um framework integrado que pode auxiliar os stakeholders envolvidos na tomada de decisão. Para este fim, este trabalho é baseado numa metodologia composta por três partes. A extensa revisão sistemática da literatura desenvolvida forneceu uma visão integrada desta área de investigação fragmentada. Esta revisão confirmou o caráter multidisciplinar do tema, pois há um número crescente de estudos conduzidos sob perspetivas muito diferentes. Além disso, verificou-se que a dimensão económica é a mais considerada; os países mais poluentes contribuíram pouco para a pesquisa; e as soluções envolvem trade-offs. A revisão da literatura suportou a definição do modelo hierárquico que estrutura as operações de última-milha em centros históricos. Este modelo foi avaliado entrevistando um grupo de experts. Após a integração do feedback dos experts, o modelo foi quantificado pelos mesmos de acordo com uma abordagem AHP-TOPSIS. Esta quantificação teve como caso de estudo o centro histórico do Porto, Portugal. Os experts consideraram as três dimensões da sustentabilidade identicamente importantes. O subcritério relativo à poluição atmosférica foi o mais valorizado, enquanto o menos foi o relativo à poluição visual. Todas as soluções de últimamilha consideradas no modelo alcançaram resultados semelhantes, sugerindo uma estratégia de distribuição combinada. No entanto, o uso de parcel lockers é a solução mais favorável e é aparentemente adequada para o centro histórico do Porto

Sustainability in urban logistics : a literature review

Purpose: The importance of urban logistics is on the rise. On the one hand, the population in cities is growing due to urbanization processes. On the other hand, there is a significant increase in the flow of goods (e.g., a boost in online purchases). Such changes are leading cities to face social, economic, and environmental issues, which urge to be addressed. Based on these premises, this study aims to identify, classify and provide an overview of the environmentally sustainable logistics solutions for urban contexts. Methodology: This study performs a systematic literature review. First, it provides a quantitative description of the results, highlighting eventual trends; second, it displays a narrative description of the papers considered to map the current solution and of the related methodology. Findings: The study highlights the maturity and interest in adopting more sustainable delivery options in urban logistics. The selection of suitable transport means, the engagement of stakeholders, as well as the definition of norms and regulations, emerge as the most discussed and promising solutions. Originality: This study is a first attempt to classify the existing body of knowledge related to urban logistics, analysing contributions based on different axes of classification and highlighting cutting-edge solutions to propose possible research directions

Mobility mining for time-dependent urban network modeling

170 p.Mobility planning, monitoring and analysis in such a complex ecosystem as a city are very challenging.Our contributions are expected to be a small step forward towards a more integrated vision of mobilitymanagement. The main hypothesis behind this thesis is that the transportation offer and the mobilitydemand are greatly coupled, and thus, both need to be thoroughly and consistently represented in a digitalmanner so as to enable good quality data-driven advanced analysis. Data-driven analytics solutions relyon measurements. However, sensors do only provide a measure of movements that have already occurred(and associated magnitudes, such as vehicles per hour). For a movement to happen there are two mainrequirements: i) the demand (the need or interest) and ii) the offer (the feasibility and resources). Inaddition, for good measurement, the sensor needs to be located at an adequate location and be able tocollect data at the right moment. All this information needs to be digitalised accordingly in order to applyadvanced data analytic methods and take advantage of good digital transportation resource representation.Our main contributions, focused on mobility data mining over urban transportation networks, can besummarised in three groups. The first group consists of a comprehensive description of a digitalmultimodal transport infrastructure representation from global and local perspectives. The second groupis oriented towards matching diverse sensor data onto the transportation network representation,including a quantitative analysis of map-matching algorithms. The final group of contributions covers theprediction of short-term demand based on various measures of urban mobility