Mobile ticketing services allow urban transport passengers to travel in a convenient and easy way, enhancing their travelling experience. In recent years several mobile ticketing services have started to be developed and launched, but there is still a lot to be done in terms of its effectiveness, efficiency and innovation. This paper presents a micro-location mobile ticketing solution based on Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technologies, calledAnda. This solution is based on a check-in/be-out scheme and requires the minimum intervention from the passenger. It is really innovative in the urban transport field, as it takes advantage of BLE technology not usually used for this purpose, it is based on a concept of post-billing with a fare optimization algorithm associated and it allows the micro-location of passengers throughout their journeys. This paper details the architecture of the solution and its mode of operation. It also presents the evaluation methodology that was followed during the pilot trial that took place in the Metropolitan Area of Porto (AMP), Portugal, during one year with 140 real passengers. A set of design lessons were identified as a result of the field tests and materialized in five mobile ticketing design dimensions, constituting important contributions to the design of future mobile ticketing services.Andawas commercially deployed in the AMP in 2018 and is used by thousands of passengers every day.

The increasing growing need for optimization of transportation in a sustainable and green environment is fundamental for the future of mobility. Companies, governments, and non-governmental institutions are trying to find new ways to contribute to this challenge. In particular, the approach is to improve the efficiency and the quality of the movement of diversification of an integrated way of transportation of people and goods. Many people may need to be at some location at some point in time, or many goods may need to be transported to nearby destinations with the same packaging conditions. The main goal of this Special Issue was to integrate the most recent advances in transportation that connect the hybrid point of view. In particular, key contributions integrate several interesting topics related to earning algorithms for the integration of passengers and goods, gamification techniques, semantic data, blockchain, and edge computing. Other topics in urban mobility, railway, and highways were considered, and hot topics on shared autonomous vehicles (SAVs) brought huge value. Moreover, the Internet of Things (IoT) opens the doors for new development in Vehicle to Everything (V2X), which are crucial for the development of new services that generate business and social impact in the future of a diversified way of the integration of passengers and goods mobility.

Origin-destination matrices help understand the movement of people within cities. This work is built upon the premise that stakeholders, e.g. decision makers, need to analyze mobility flows from spatio-temporal perspectives that are appropriate to their context of analysis. The data retrieved from sensors and Intelligent Transportation Systems are useful for this purpose due to their lower acquisition costs and fine granularity, although it is complex to use such data in an integrated way, as they might have heterogeneous representations of spatio-temporal attributes and granularities. Most of the related works on the analysis of OD flows consider matrices with a fixed spatio-temporal aggregation level, and do not explore the intrinsic issue of data heterogeneity. Herein we report our findings on building the semantic foundation of knowledge-assisted visualization tools for analyzing OD matrices from multiple stakeholder levels. We propose a set of ontology design patterns for modeling the semantics of OD data, and the relations between the spatio-temporal constructs that stakeholders ought to choose when visualizing urban mobility flows. Our approach aims to be reusable by researchers and practitioners. We describe a practical implementation using estimated flows from smart card data from Porto, Portugal.

A methodology for estimating the destination of passenger journeys from automated fare collection (AFC) system data is described. It proposes new spatial validation features to increase the accuracy of destination inference results and to verify key assumptions present in previous origin-destination estimation literature. The methodology applies to entry-only system configurations combined with distance-based fare structures, and it aims to enhance raw AFC system data with the destination of individual journeys. This paper describes an algorithm developed to implement the methodology and the results from its application to bus service data from Porto. The data relate to an AFC system integrated with an automatic vehicle location system that records a transaction for each passenger boarding a bus, containing attributes regarding the route, the vehicle, and the travel card used, along with the time and the location where the journey began. Some of these are recorded for the purpose of allowing onboard ticket inspection but additionally enable innovative spatial validation features introduced by the methodology. The results led to the conclusion that the methodology is effective for estimating journey destinations at the disaggregate level and identifies false positives reliably.

In recent years, the significant advancements in miniaturised computing and pervasive communication networks have paved the way for ubiquitous computing environments. In such environments users interact with systems through novel and implicit methods. In this context, affective computing provides a dimension of interaction, raising a number of opportunities to address not only utilitarian but also hedonic needs. At the same time, a number of challenges arise beyond the technical aspects, that are related to the individual and other societal implications. A review of the main opportunities and challenges is presented, supporting the identification of the main requirements for the design and development of systems in interactive pervasive environments, focusing on an affective loop of interaction. A framework is proposed, identifying main modules and functionality alongside a methodology to instantiate in specific domains of application.

In recent years, the technological developments in mobile and communication networks have paved the way for smart environments, whose final goal is to provide users with enhanced experiences. The measure of user experience satisfaction, or quality of experience, may be defined as an affective state in response to a service. Thus, an experiment was devised to explore the relationship between users' affective state and their context, for assessing quality of experience in urban public transport services. A pilot study, conducted to evaluate the feasibility and requirements of such an experiment is presented, leading to a large scale field study.

The convergence of personal devices, pervasive communication networks and remote computing has caused a fundamental shift in the user interaction paradigm. Multiple methods have enabled an implicit loop of interaction that goes beyond the traditional graphical interfaces. Human emotion is one of such dimensions, supporting the development of empathic systems. Thus, quality of user experience, a subjective measure, may be defined as the resulting affective state from an interaction, which can be dynamically assessed. In mobile ubiquitous settings, leveraging this affective interaction for providing personalisation and immersive digital services has the potential to significantly impact user experience. This paper investigates the relationship between user affect and experience in the context of urban public transport.