Abstract
Urban population is increasing fast. This is creating new challenges to public transport systems since some groups of citizens as elderly people may have sensory, cognitive or motor impairments that need to be addressed. This work explores the potential of a Demand Responsive Transport (DRT) system for people with reduced mobility in an urban environment. For this purpose, the Dial-A-Ride Problem (DARP) was implemented using a multivariable minimisation approach. In this approach, an Assigning Request to Vehicles (ARV) algorithm is used to obtain an initial solution. Then a Multi-Objective Tabu Search Algorithm (MOTSA) is applied to the initial solution to search for the non-dominated solution (optimisation phase). In this optimisation phase, the total travelled distance, the deadheading distance and the number of vehicles were minimised. The performance of the model was computed combining different parameters' values of the number of requests, boarding time for each user, the number of seats in each vehicle, vehicle's speed, the total number of iterations, and candidate threshold number (the algorithm's parameter). The computational results found a strong positive correlation between the number of requests and the: total travelled distance (rs = 0.977, p-value<0.001) and the number of vehicles (rs =0.883, p-value<0.001); and a low positive correlation between the number of requests and the optimised total travelled distance (rs =0.331, p-value<0.001) and the optimised number of vehicles (rs =0.340, p-value<0.001). © 2020 The Authors. Published by ELSEVIER B.V.

Abstract
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. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
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.

Abstract
Social networks are strongly present in the daily life of modern society. Most people use these social networks to share information about their lives, their opinions, places they visit and their state of mind. Generally, these posts are composed of various information, being the location of the users location part of the data. The purpose of this work is to obtain the location of the posts and observe the users mobility pattern in the city of Porto, Portugal. This paper discusses the technologies available for obtaining the data, the social networks currently worth studying and their respective restrictions. It also explores new approaches to collect the data from the desired social networks, respecting all restrictions currently applied. The different software solutions developed for the social networks interactions are explored and described in depth. Subsequently, the necessary software for social networks is reviewed, the possible algorithms for data mining are discussed and its implementation is presented. Finally, the results obtained are interpreted and studied according to the characteristics of the city, tourism promotions and transport routes. © 2020 The Authors. Published by ELSEVIER B.V.

Abstract
Technological advances and the use of mobile solutions to make smartphone users’ daily life easier is a mindset that has revolutionized the society lifestyle in the past years. In the public transport sector, mobile ticketing is an example of the applicability of mobile solutions in a real context. Using one smartphone to purchase and validate tickets is a revolutionary idea that has acquired fans around the world. The convenience of use and time savings throughout the process are positive aspects, however, the success of the adoption of such services is limited. Based on the case of Porto, Portugal and particularly of the mobile app And, this study intends to understand customer churn factors of mobile ticketing services by analysing data from customer complaints and from usage history. Thus, an analysis of the complaints, the complainers and the effects of complaints is presented. A strategy for capturing and retaining users is also proposed considering four stages of mobile ticketing apps lifecycle: user onboarding, user engagement, user retention and user reinstall. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract