Aim: Ride-sharing is an innovative on-demand transport service that aims to promote sustainable transport, reduce car utilization, increase vehicle occupancy and public transport ridership. By reviewing ride-sharing studies around the world, this paper aims to map major aspects of ride-sharing, including online platforms, user factors and barriers that affect ride-sharing services, and extract useful insights regarding their successful implementation. Method: A systematic literature review is conducted on scientific publications in English language. Articles are eligible if they report a study on user factors affecting ride-sharing use and/or barriers preventing ride-sharing implementation; ride-sharing online platforms in these articles are also recorded and are further explored through their official websites. A database is built that organizes articles per author, year and location, summarizes online platform attributes, and groups user factors associated with the likelihood to ride-share. Findings: The review shows that the term “ride-sharing” is used in the literature for both profit and non-profit ride-sharing services. In total, twenty-nine ride-sharing online platforms are recorded and analyzed according to specific characteristics. Sixteen user factors related to the likelihood to ride-share are recorded and grouped into sociodemographic, location and system factors. While location and system factors are found to follow a pattern among studies, mixed findings are recorded on the relationship between sociodemographic factors and ride-sharing. Factors that may hinder the development of ride-sharing systems are grouped into economic, technological, business, behavioral and regulatory barriers. Conclusion: Opportunities exist to improve the quality of existing ride-sharing services and plan successful new ones. Future research efforts should focus towards studying ride-sharing users' trip purpose (i.e., work, university, shopping, etc.), investigating factors associated to ride-sharing before and after implementation of the service, and perform cross-case studies between cities and countries of the same continent to compare findings.

The COVID-19 pandemic had a significant effect in urban mobility, while essential changes are being observed in travelers’ behavior. Travelers in many cases shifted to other transport modes, especially walking and cycling, for minimizing the risk of infection. This study attempts to investigate the impact that COVID-19 had on travelers’ perceptions towards bike-sharing systems and whether the pandemic could result in a greater or lesser share of trips that are being conducted through shared bikes. For that reason, a questionnaire survey was carried out in the city of Thessaloniki, Greece, and the responses of 223 people were analyzed statistically. The results of the analysis show that COVID-19 will not affect significantly the number of people using bike-sharing for their trips. However, for a proportion of people, bike-sharing is now more attractive. Moreover, the results indicate that bike-sharing is now more likely to become a more preferable mobility option for people who were previously commuting with private cars as passengers (not as drivers) and people who were already registered users in a bike-sharing system. The results also provide evidence about the importance of safety towards COVID-19 for engaging more users in bike-sharing, in order to provide them with a safe mobility option and contribute to the city’s resilience and sustainability.

As part of the overall goal of carbon emissions reduction, European cities are expected to encourage the electrification of urban transport. In order to prepare themselves to welcome the increased number of electric vehicles circulating in the city networks in the near future, they are expected to deploy networks of public electric vehicle chargers. The Electric Vehicle Charging Infrastructure Location Problem is an optimization problem that can be approached by linear programming, multi-objective optimization and genetic algorithms.

Rising interest in the field of Intelligent Transportation Systems combined with the increased availability of collected data allows the study of different methods for prevention of traffic congestion in cities. A common need in all of these methods is the use of traffic predictions for supporting planning and operation of the traffic lights and traffic management schemes. This paper focuses on comparing the forecasting effectiveness of three machine learning models, namely Random Forests, Support Vector Regression, and Multilayer Perceptron—in addition to Multiple Linear Regression—using probe data collected from the road network of Thessaloniki, Greece. The comparison was conducted with multiple tests clustered in three types of scenarios. The first scenario tests the algorithms on specific randomly selected dates on different randomly selected roads. The second scenario tests the algorithms on randomly selected roads over eight consecutive 15 min intervals; the third scenario tests the algorithms on random roads for the duration of a whole day. The experimental results show that while the Support Vector Regression model performs best at stable conditions with minor variations, the Multilayer Perceptron model adapts better to circumstances with greater variations, in addition to having the most near-zero errors.

Mobility as a Service (MaaS) is an innovative mobility service that aims to redesign the future of urban mobility by integrating multi-modal transportation and app-based technologies to enable seamless urban mobility. While MaaS pilot demonstrations and schemes implementation have taken place in different cities at a global level, and relevant studies focus on the MaaS barriers and users’ characteristics, the planning process for implementing MaaS is rarely presented. This paper summarizes the services to be integrated into the MaaS Athens’ demo site in Greece and describes the planning process that was followed to showcase the demo. The demo site is located within the urban area of Athens, including a public transport operator, a bike-sharing service, a taxi operator, and a municipality public transport operator. The demonstration runs developments in a real corridor that has the potential to prepare the MaaS eco-system deployment and market uptake. Three travel cases are planned: (1) Multimodal work trip; (2) MaaS for tourists; and (3) Interurban/urban interfaces, for work and shopping/leisure trips. The user journeys are defined in detail and the main information for each user journey is presented. The study concludes with challenges that were faced during the demo planning and recommendations for achieving the MaaS goals.

The hyperloop is an innovative land transport mode for passengers and freight that travels at ultra-high speeds. Lately, different stakeholders have been engaged in the research and development of hyperloop components. The novelty of the hyperloop necessitates certain directions to be followed toward the development and testing of its technological components as well the formation of regulations and planning processes. In this paper, we conduct a comprehensive literature review of hyperloop publications to record the current state of progress of hyperloop components, including the pod, the infrastructure, and the communication system, and identify involved EU stakeholders. Blending this information results in future directions. An online search of English-based publications was performed to finally consider 107 studies on the hyperloop and identify 81 stakeholders in the EU. The analysis shows that the hyperloop-related activities are almost equally distributed between Europe (39%) and Asia (38%), and the majority of EU stakeholders are located in Spain (26%) and Germany (20%), work on the traction of the pod (37%) and the tube (28%), and study impacts including safety (35%), energy (33%), and cost (30%). Existing tube systems and testing facilities for the hyperloop lack full-scale tracks, which creates a hurdle for the testing and development of the hyperloop system. The presented analysis and findings provide a holistic assessment of the hyperloop system and its stakeholders and suggest future directions to develop a successful transport system.