Panagiotis G. Tzouras

Bicycles play a protagonist role as a sustainable transport mode, especially in complementing public transport by serving as an effective last-mile solution. Although shared micromobility systems are increasingly used to address last-mile gaps in urban neighborhoods, many cities like Penteli, a municipality in the metropolitan area of Athens, Greece lack a complete cycle lane network. Given the spatial and financial constraints associated with developing cycling infrastructure, this study empirically examines the potential of a relatively low-cost alternative—cycle streets—using Penteli in Athens, Greece, as a living lab. These are horizontally marked living streets leveraging Greece’s revised Road Traffic Code, which enforces a default speed limit of 30 km/h in urban streets. In this ex-ante quantitative assessment, traffic speeds were measured at six checkpoints of the network using radar sensors. Additionally, a stated preference survey explores awareness, perception, and readiness of citizens to change both driving and travel behavior. The findings reveal how a cycle street network can establish the necessary dynamics to foster a safer, more cycle-friendly environment in the long-term.

The rapid emergence of shared mobility solutions has been accompanied by the determination of multiple indicators. However, this abundance has led to a fragmented landscape, what can be described as a new “Babel” of impact assessment. Without a common language, it has become increasingly difficult to compare results across contexts and draw meaningful conclusions about the true impacts of shared mobility. In response, this study aims to establish a Standardized Impact Evaluation Framework (SIEF) to effectively assess and understand the broader implications of New and Shared Modes (NSMs). SIEF integrates four horizontal levels: policies, transport system performance, modal split, and sustainability impacts. Each level distinguishes between actual and perceived changes, acknowledging the role of user perceptions in expected behavioral shifts. SIEF becomes operational through the development of a new user-friendly Open-Data Platform (ODP), designed to analyse and compare city performance, assess the direct and indirect impacts of measures to integrate NSMs, and identify the most effective ones. This study presents a clear path to collaboratively explore, discuss, and understand the positive effects of NSMs and related innovations, if such benefits truly exist.

There is a growing emphasis on active transport, prompting cities to be redesigned as more pedestrian-friendly environments. This shift has fueled interest in proximity-based planning models, such as the X-minute city, which are increasingly promoted for their potential public health and environmental benefits. However, equity considerations in the assessment of such models are often neglected or rely on local datasets that limit broader applicability. In response, we introduce a method for evaluating equity under the X-minute city paradigm using open data and established accessibility metrics and grounded in the ethical frameworks of egalitarianism and sufficientarianism. Applying our method to Athens, Stockholm, and Amsterdam, we assess equitable access to essential services and amenities, including supermarkets, playgrounds, and public transport stations. Our findings demonstrate that the choice of ethical framework plays a critical role in shaping equity assessments, and that disaggregating by destination type reveals distinct spatial patterns of accessibility, shedding light on both the strengths and limitations of different urban areas. The application of our method also surfaces unexpected insights: Athens—despite its car-dependent image—emerges as the most aligned with the X-minute city model, while Stockholm’s decentralized form underscores the need to adapt time thresholds to local urban structure and behavior. Overall, the method’s reproducibility and use of open-data support cross-city comparisons and contribute to the evolving methodological toolkit for evaluating proximity-based planning.

The limited availability of mobility data makes it challenging to model demand, especially its spatiotemporal variations. Simultaneously, traditional transport modeling tools often rely on less disaggregated approaches, leading to gaps in understanding. To overcome these limitations, this study introduces the spectral clustering method to uncover major demand patterns considering various transport modes. It focuses on Athens, Greece, and utilizes a set of 1347 reported trips. The study reveals six distinct trip clusters. The first group, “an evening stroll nearby”, captures short distance tours typically undertaken by walking. The second cluster, “my work is nearby but I use my car” highlights a significant trend where individuals with short commutes, less than 6 km, predominantly use private cars. The third cluster, “commuting by metro”, features long-distance trips primarily for work. The fourth cluster reveals long-distance work-related trips with private cars, favored by active residents with high income. The fifth pattern, “trips of young people”, involves midnight recreational and moderate-distance morning trips for education, with an increased usage of public transport. The sixth cluster concerns short distance tours for various activities. The findings indicate that the second cluster’s high reliance on private cars for short trips is problematic. Reducing this reliance should be a priority for policymakers.