Teresa Galvão

Abstract
The proliferation of new technologies is revolutionizing the public transport sector, allowing Operators to replace complex and expensive infrastructures by travellers' mobile devices and online management channels and platforms. This paper aims to present the Seamless Mobility platform, a disruptive solution based on these new channels, which main goal is to facilitate and promote public transport usage for travellers, as well as reducing operational costs for public transport companies. The Seamless Mobility platform integrates three main components: (i) mobile payments, (ii) route planner, and (iii) social network. The payment component is based on the pay-as-you-go concept with check-in and check-out requiring the reading of the corresponding QR Code station. The route planner combines information from published schedules with real-time information to identify the nearest stops, the next departures, or the best route for a scheduled trip. The social network component allows real time sharing among travellers of public transport information, related to several aspects of the service (e.g. noise, skilfulness of drivers). To test the concept, a mobile application, called OneRide, was developed. This application was tested by users in real environment, in the city of Porto, Portugal. The results show that users considered the system extremely useful, since it is more convenient than traditional systems. It was also clear that users valued the integration of additional and complementary services with mobile payments, such as information about their journey, maps and schedules. Regarding the social component some users found it difficult to understand the concept, but once they understood they considered it very useful. The use of the QR Codes to perform the payment has shown to be one of the main challenges to be addressed, since lighting conditions, position and distance to the QR Code influences the reading process. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
Nowadays, mobile phones are ubiquitous systems of our society. Nevertheless, the adoption of this technology to perform mobile payments, namely in public transport, was only implemented in a few number of transport networks. Thus, this paper aims to understand which are the main factors that may influence the adoption of mobile payments in public transport. For this purpose, a survey was applied to different groups of population. The study was conducted on the public transport networks of a medium-sized metropolitan area (Oporto-Portugal) and of a big-sized metropolitan area (Beijing-China). The evaluation results of the current services of purchase and validation of public transport tickets almost never show significant statistical differences (p>0.05) for the traditional variables used by the literature. This is particularly true for age. Nevertheless, some mobility factors can sometimes play an important role in the assessment of ticketing systems. Moreover, although the high differences between the ticketing systems in both cities, Chinese and Portuguese have a similar opinion about the systems implemented in their cities. Still, Chinese reveal a higher motivation to adopt the new ticketing system. In general, such system is greatly accepted by the respondents and the potential market is expected to be high (30-68%). Although this technology cannot replace the traditional systems, it can contribute to increasing the overall efficiency of the transport networks. The improvement of the passengers' appraisal, the reduction of operational and the maintenance costs of transport operators are the network impacts most expected. Convenience and time saving are the main advantages mentioned while questions about privacy, interaction and reliability are stated as the main concerns to adopt it. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
This paper proposes an ontology-based approach to support the process of visualizing urban mobility data. The approach consists of building a visualization-oriented urban mobility ontology, focused on themes such as ridership, vehicle flows and the like. Existing ontologies focus on modelling the overall structure of transportation networks, and do not address the formalization of such themes. The ontology also allows characterizing visualization techniques with human perception factors, so that they can be used to automatically infer recommended techniques for a dataset. The ultimate goal is to benefit decision makers, by providing an ontology that can assist with the process of developing semantically-rich visualizations, with increased data interoperability and knowledge extraction capabilities. We provide an example with real data of the public transportation system of the city of Porto, Portugal. The example shows the semantic characterization of a visualization technique, and how semantics can assist the task of automatically recommending visualizations. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract

Abstract
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. © 2017 The Authors. Published by Elsevier B.V.