Joana Maria Hora

Abstract
This study estimates alighting stops and transfers from entry-only Automatic Fare Collection (AFC) data. The methodology adopted includes two main steps: an implementation of the Trip Chaining Method (TCM) to estimate the alighting stops from AFC records and the subsequent application of criteria for the identification of transfers. For each pair of consecutive AFC records on the same smart card, a transfer is identified considering a threshold for the walking distance, a threshold for the time required to perform an activity, and the validation of different boarding routes. This methodology was applied to the case study of Porto, Portugal, considering all trips performed by a set of 19999 smart cards over one year. The results of this methodology allied with visualization techniques allowed to study Origin-Destination (OD) patterns by type of day, seasonally, and by user frequency, each analyzed at the stop level and at the geographic area level.

Abstract
Due to an increase in population, urban centers are currently seeing an increase in traffic, resulting in negative consequences such as pollution and congestion. Efforts have been made to promote a modal shift towards the use of more sustainable means of transport, such as walking and cycling, but several deterrents influence the citizens' perceptions of safety, security and comfort, discouraging their choice of active modes of transport. This study focuses on the importance of providing meaningful information to vulnerable road users (VRUs) to support their perceptions and objectives while moving within urban spaces through a novel concept of route planning. A broad survey of the needs and concerns of VRUs through interviews, focus groups and questionnaires, applied to the Portuguese population of the Metropolitan Area of Porto, led to the development of a new concept of route planners that show personalized routes according to the individual perceptions of each user. This concept is materialized in a route planner prototype that has been extensively tested by potential users. Subjective evaluation and feedback showed the usefulness of the concept and added value to a familiar product, leading to a satisfying experience for participants. This study shows that there is an opportunity to improve these tools to provide a higher degree of power and customization to users on route planning, which includes addressing mobility restrictions and personal perceptions of safety, security and comfort. The ultimate goal of this new approach is to persuade citizens to switch to more sustainable means of transport.

Abstract
Promoting active modes of transport, such as walking and cycling, has a positive impact on environmental sustainability and the health and well-being of citizens. This study explores the elderly population’s perception of comfort, safety and security when using active modes of transport. It begins with a systematic review of the literature considering research works that relate to active travel, the elderly population, and random forest. Then a questionnaire was applied to 653 participants and the results were analyzed. This analysis consisted of using statistics to evaluate the socio-demographic profile, the preferences regarding the use of active modes of this population, and the importance given to each dimension: comfort, safety, distance, and time, comparing these indicators through the Wilcoxon Rank Sum test and the Random Forest algorithm. The results showed that people over 56 years old walk as much as younger people. Furthermore, the importance given by this group of people to indicators referring to active modes is related to safety and security, distance, time, and comfort. The statistical results of the Wilcoxon Rank Sum test indicate the most important indicators: Adequate Travel Distance & Time and Existence of Commercial Areas by age group [0–55], and Absence of Allergenics and Existence of Green Areas by age group [56+]. Finally, the Random Forest algorithm provides the relative importance for both age groups, [0–55] and [56+], where the indicators that stand out in the [56+] age group, which is the focus of our study, are air quality, adequate travel distance & time, adequate crowd density, adequate thermal sensation, absence of allergenic, good street illumination level, adequate traffic volume, and adequate noise level. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
This article presents a framework to assist in the design of technology-based interactive services for active mobility, which allows the data collected from the sensors to be made available to citizens. The proposed framework was developed based on data collected in focus group sessions held with potential stakeholders and on related models and frameworks. It consists of 8 steps, namely: strategy, scope, structure, skeleton, aesthetics and execution. It will enable the presentation of relevant information that will help users of active modes of transport in decision making in choosing a safe and comfortable route, assist professionals involved in the elaboration of interactive projects and promote more collaborative urban planning. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract
This work proposes an architecture to treat georeferenced data from the OpenStreetMap to plan routes. The methodology considers the following steps: collecting data, incorporating data into a data manager, importing data into a data model, executing routing algorithms, and visualizing routes. Our proposal incorporates the following features characterizing each street segment: safety & security, comfort, accessibility, air quality, time, and distance. Routes can be calculated considering any specified weighting system of these features. The outcome of the application of this architecture allows to calculate and visualize routes from georeferenced data, which can support researchers in the study of multi-criteria routes. Furthermore, this framework enhances the OSM data model adding a multi-criteria dimension for route planning.