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In the evolving domain of urban mobility systems, the integration of technology with user-centric strategies is pivotal. This research stands on the foundational concept of Mobility-as-a-Service, a user-centric intelligent mobility management distribution system that seeks to prioritize human needs over mere technological infrastructure. The study delves deep into the wealth of data available through mobile sensing technologies, highlighting the unprecedented understanding it offers into human mobility patterns, thus facilitating personalized route recommendations.

Many shipping companies tackle the challenge of potentially replacing conventional trucks with electric ones in economically developed countries. The aim of this work is to describe the principle of scaling models for analysing the operation of a fleet of vehicles, when the decision to use a particular type of model is made considering the accuracy and completeness of the initial data, as well as the goals of modelling. At the end of the report, information is provided on the TraPodSim simulation system developed by the authors, which is based on a multi-agent simulation model created using AnyLogic software.

The paper is based on the research project ePIcenter (www.ePIcenterproject.eu) supported by the EU HORIZON 2020 Programme. ePIcenter connects thirty-six partners: port authorities, logistic service providers, manufacturers, academic institutions, and technology partners. The main goal is to develop and test AI driven logistic software solutions, apply new technologies and methodologies to increase the efficiency of global supply chains and reduce their environmental impact. One of the significant aspect the project focusses on is optimisation, using AI, digitalisation, automation and innovations in freight transport and handling technologies. Finally, modelling powerful solutions to enable resilient, efficient and environment friendly supply chains.

In today’s daily traveller world, not only the time and money became important, but climate change and pandemic raised the importance of safety and sustainability of future trip plans. In order to provide such a wide coverage for a variety of important information, a sustainable trip planner needs to receive a lot of data from a variety of differentiated data sources. Provided review of related works shows that a lot of started activities in this aspects gives all of us promises and hope that available Big Data sources will be wisely used in order to bring added value not only to individual travellers, but also society, the transportation services will become better structured and information will be easily available for smart and safe decision making, that gradually will increase life quality.

The present paper aims at measuring the satisfaction of travellers and stakeholders on perceived quality of service provided at the Latvian interchange “Riga International Coach Terminal” and understand whether there are any gaps between the two groups of involved parties, based on their perceptions and expectations. To this end, a travellers’ attitudinal survey was organized and interviews with representative stakeholders were conducted, in order to capture and analyse their attitudes and preferences and extract those attributes that affect their satisfaction. Results showed that the interchange performs well in physical quality attributes, such as travel and wayfinding information provision, but in terms of access and aesthetics expectations in the internal and external design, some contradictory findings were revealed between travellers and stakeholders, validating the fact that understanding users’ perceptions can work as vital input to policy makers’ perceptions of an integrated sustainable public transport system.

This paper introduces a decision tree approach, which can be used for the assessment of the design, operation and services provided at urban transport interchanges. Realizing a customer satisfaction survey, feedback was received from 239 users of the Riga International Coach Terminal on crucial attributes, including: travel information, wayfinding information, time and movement, access, comfort and convenience, station attractiveness, safety and security, emergency situation handling and overall satisfaction. Findings revealed the most significant parameters that need to be addressed in order to increase users’ satisfaction, which can gradually improve the overall attractiveness of the terminal and the efficient provision of its services.

The present paper aims at analysing the concept of “urban interchanges” as a solution towards seamless transportation and sustainable mobility. Based on an extensive review of policies, initiatives and data analysis coming from interviews and meetings with stakeholders, a coherent interchange design typology was formulated that links seamless transport and urban interchanges to spatial and urban planning. Focusing on the impact of user satisfaction as a priority towards user travel choices, a list of indicators was valuated. The comparative analysis of interchange typology performance formulated by the users’ perception regarding network accessibility, surrounding area, offered interchange time facilities and environmentally friendly services and infrastructure revealed fruitful findings on proper interchange design towards sustainability and reformation of the city-hubs into true green urban interchanges.

This introductory paper gives the readers a brief description of the scope and contents of this Special Issue that consists of papers devoted to Sustainable Transport Interchanges and intermodal networks. The issue depicts the results of the EU project ALLIANCE, which addresses the topic of intermodal interconnections and presents the results of the international collaboration teams, which were established within the context of the project.

In the coming years, mobility initiatives should focus on sustainability, safety, and social equity. This can be achieved by introducing innovative transportation methods, implementing novel approaches for endusers, and optimizing the utilization of traditional modes of transport. To achieve this goal, it is essential to utilize pervasive sensing and computing technologies, along with intelligent information processing systems, to assist decision makers, managers, and transport operators. To effectively address unforeseen events and disruptions, mobility services should promptly adapt and improve their flexibility. Furthermore, these services should be adaptable to meet the unique needs and evolving demands of individuals. Current research focuses on understanding how individuals make decisions about when and where they engage in walking, driving, and travel activities. Therefore, it is important to develop reliable human mobility models in this context. Big data and Artificial Intelligence (AI) are important in this context as they enable data generators to identify individual patterns and quickly adapt solutions. This paper aims to conduct a literature review on Mobility-as-a-Service (MaaS), focusing on personalization, to identify gaps in current MaaS initiatives. This assessment is essential for creating inclusive, user-friendly, personalized, and customizable MaaS solutions. To conclude, the existing challenges have been addressed in comprehending the characteristics of MaaS in terms of personalization. Additionally, they have been proposed further research questions to delve deeper into this aspect. [ABSTRACT FROM AUTHOR]

This research considers the aspects of decision-making according to the airport activities. The decision about airport planning and management should be comprehensive and operative and of course, the assessment of alternative decisions is necessary. The purpose of this research is to highlight the role of simulation modelling at the stage of airport development. The authors present the methodology of a model-driven decision-making approach and then describe 2 cases of using simulation for Riga International Airport (RIX) development. The 1st case study is used for analysis possibility of the development of the airport's surrounding territory. The planned massive development of RIX and the surrounding area requires detailed analysis for increasing its positive impact on regional and national business economics, social aspects, business and the environment. The 2nd case supports decision-making for the needs of the terminal reconstruction, presents a helpful tool for visualization of the tendencies in the future, and allows the analysis of the different infrastructure layouts. Both cases give the possibility to predict the situation and evaluate the service provided for passengers (travellers) of the airport. Simulation modelling allows to study complex system - airport and evaluate direct and indirect impacts of planned reconstruction. [ABSTRACT FROM AUTHOR]

Sustainable urban mobility remains an emerging research topic during last decades. In recent years, the smart card data collection systems have become widespread and many studies have been focused on usage of anonymized data from these systems for better understanding of mobility patterns of Public Transport (PT) passengers. Data-driven mobility patterns can benefit transport planners at strategic, tactical, and operational levels. A particular point of interest is a spatiotemporal dynamics of mobility patterns that highlights transformation of the PT passenger flows over the time continuously or in response to modifications of the PT system and policies. This study is aimed to estimation and analysis of the spatiotemporal dynamics of PT passenger flows in Riga (Latvia). A multi-stage methodology was proposed and includes three main stages: (1) estimation of individual trip vectors, (2) clustering of trip vectors into spatiotemporal mobility patterns, and (3) further analysis of mobility patterns' dynamics. The best practice methods are applied at every stage of the proposed methodology: the smart card validation flow is used for extracting information on boarding locations; the trip chain approach is used for estimation of individual trip destinations; vector-based clustering algorithms are utilised for identification of mobility patterns and discovering their dynamics. The resulting methodology provides an advanced tool for observing and managing of PT demand fluctuation on a daily basis. The methodology was applied for mining of a large smart card data set (124 million records) for year 2018. Most important empirical results include obtained daily mobility patterns in Riga, their clusters, and within-cluster dynamics over the year. Obtained daily mobility patterns allows estimation of a city-level PT origin-destination matrix that is useful in many applied areas, e.g., dynamic passenger flow assignment models. Mobility pattern-based clustering of days allows effective comparison and flexible tuning of the PT system for different days of a week, public holidays, extreme weather conditions, and large events. Dynamics of mobility patterns allows estimating the effect of implementing changes (e.g., fare increase or road maintenance) and demand forecasting for user-focused development of PT system. [ABSTRACT FROM AUTHOR]