The COVID-19 pandemic has affected our cities in monumental ways with no sector likely being more severely impacted than transport. Lockdowns, physical spacing, transport restrictions and stay-at-home guidelines have transformed personal mobility and highlighted the mistakes of an unbalanced pro-car culture that defined a century of urban planning. One immediate effect of the virus in relation to travel demand and supply was the emergence of active travel modes because of their unique ability to provide a socially distanced way of transport. Cycling is one of the modes that has enjoyed significant attention. Numerous cities have reallocated street and public space to cyclists and introduced pro-bike interventions like pop-up cycle lanes, e-bike subsidies, free bike-share use and traffic calming measures. This newly found outbreak-induced momentum creates an opportunity to establish a new ethos that allows the promotion of potentially permanent strategies that may help cycling to be (re-)established as a robust, mainstream and resilient travel mode for inner city trips and not as a second-class alternative operating under the automobile’s giant shadow. This paper provides a state-of-the-art description of the anti-COVID cycling-friendly initiatives that have been introduced globally, the successes and failures of these initiatives, the lessons learnt that can help us redefine the bicycle’s role in local societies today and a best cycling practice policy guide for planning a more bike-centric future.

Shifting from a fossil-fueled to an eco-friendly vehicle fleet in cities could pave the way towards a more sustainable future. Electric Vehicles (EVs) should thus be prioritized, so that they could replace conventional vehicles gradually. In this context, an EV-accommodating infrastructure, which ensures the functionality of the entire system, is essential. This study aims to develop a methodological framework to identify suitable locations for the deployment of EV charging points in urban environments. To meet this objective, we acquired a mixed method approach including a systematic literature review, 12 semistructured stakeholder interviews which were thematically analyzed, and an Analytical Hierarchy Process (AHP). The outcome is a spatial model function, which consists of parameters and weights for estimating the suitability of each urban road link that will allow the establishment of EV charging points. Results show that the key location selection factors are: transport hubs, marked or controlled parking spaces, and points of interest. The less significant factor is public services. Therefore, there is a preference, in stakeholder level, for transport features over the land use ones (69% over 31%). Although this research is conducted in Greece, we intend to suggest methods and generate valuable findings that may be valid and generalizable for a more global context.

Shared Autonomous Vehicles (SAVs) are expected to have a transformative role in future transportation systems, by reducing vehicle ownership, helping in alleviating congestion, improving accessibility and traffic safety, and changing travel behavior and urban infrastructure. The potential introduction of SAVs in transportation systems has triggered the need of exploiting suitable tools for designing and planning SAV operations and services and assessing their impacts. An explicit category of such tools are agent-based models (ABMs), whose advantage in efficiently representing transportation systems with a fine level of detail, has allowed them to gain importance in modeling SAVs. This paper systematically reviews and organizes the current state-of-the-art on ABMs dealing with SAVs. The review is two-fold: first, the methodological aspects of exploiting ABMs in the context of SAV services and operations are analyzed and second, ABM-based findings on the anticipated impacts of SAVs to traffic, travel behavior, land uses, the environment and so on, are presented and discussed. The paper concludes with recommendations for future research on SAVs and other, potential ABM applications for that purpose.

Cycling tourism is an environmentally friendly way to explore a destination. Nowadays, it is becoming more and more popular worldwide, since it permits an in-depth communication both with nature and people. In this context, the aim of this paper is to explore, in detail, mainly the environmental motivators of cycling tourists, and their significance, in Greece, by using qualitative social research (in-depth interviews and focus groups) and participative analytical hierarchical process. The results show that regarding physical environment, the element which attracts cycle tourists the most is the variety of scenic views along their route. Existence of lakes, rivers and beaches were also valued. On the contrary, “Biodiversity” and “Untouched natural landscapes” were ranked low as a description of the quality of the natural environment. However, the rise of cycling tourism depends considerably on the appropriate infrastructure, namely roads with low slopes, appropriate quality of surfaces and cycling infrastructure. Planners, policy-makers, and competent authorities should give emphasis on the critical factors in order to enhance cycling tourism, thus resulting in positive multiplying effects such as environmental protection and economic growth.

E-scooters aspire to provide flexibility to their users while covering the first/last mile of a multimodal trip. Yet, their dual travel behavior, i.e., utilizing both vehicles’ roadways and pedestrians’ sidewalks, creates new challenges to transport modelers. This study aims to model e-scooter riding behavior in comparison to traditional urban transport modes, namely car and walking. The new modeling approach is based on perceived safety that is influenced by the road environment and affects routing behavior. An ordinal logistic model of perceived safety is applied to classify road links in a 7-point Likert scale. The parametric utility function combines only three basic parameters: time, cost, and perceived safety. First/last mile routing choices are modeled in a test road network developed in Athens, Greece, utilizing the shortest-path algorithm. The proposed modeling approach proved to be useful, as the road environment of an urban area is heterogenous in terms of safety perceptions. Indeed, the model outputs show that the flexibility of e-scooters is limited in practice by their low-perceived safety. To avoid unsafe road environments where motorized traffic dominates, e-scooter riders tend to detour. This decision-making process tool can identify road network discontinuities. Nevertheless, their significance regarding routing behavior should be further discussed.

Currently, there is a growing consensus that the use of more sustainable urban freight transportation has the potential to offer major energy and efficiency benefits which can be achieved through the appropriate combination of cargo bikes and the integration of drones into the urban logistics system. This study presents the results of a stepwise regression analysis that examines the role, benefits, and impact of electric vehicles such as e-bikes, cargo bikes, and drones for intermodal freight transportation in five Greek cities to support the green logistics paradigm. The results show that between routes of almost equal length, the most bicycle-friendly routes, such as routes along pedestrian areas or residential streets, should be avoided, as they reduce delivery speed and increase delivery costs in terms of energy and time expenditure. In addition, priority roads, which usually have higher traffic speeds and more trucks, are preferred by cyclists due to the quality of the road surface, even though the feeling of safety is lower on such roads. Finally, regarding drones, energy consumption is relatively low in the 0–5 mph and 6–10 mph wind speed ranges, indicating efficient energy use. In the 11–15 mph and 16–20 mph wind speed ranges, energy efficiency is significantly lower than the battery capacity, indicating that the cargo drone exhibits excessive energy consumption under these conditions.