Apostolos Anagnostopoulos

Advances in artificial intelligence and computer vision have enabled the use of Surrogate Safety Measures (SSMs) for proactive traffic safety assessment. This study, conducted within the STREET21 project, investigates the safety impacts of autonomous vehicle (AV) integration at a signalized intersection in Thessaloniki, Greece. Four hours of video data were processed with GoodVision software, allowing precise detection of pedestrian and vehicle trajectories. The extracted data supported the development, calibration, and validation of a PTV VISSIM microsimulation model, used with the Surrogate Safety Assessment Model (SSAM) to evaluate conflict indicators, particularly Post-Encroachment Time (PET). Multiple scenarios examined AV penetration rates and driving behaviors (cautious, normal, aggressive). Results indicate pedestrian–vehicle conflicts remain significant, especially during right-turn movements under amber phases. Increasing AV penetration improves safety outcomes, depending on driving behavior. The methodology demonstrates the robustness of combining AI-based video analytics with microsimulation for identifying traffic conflicts and assessing infrastructure readiness.

The present study investigates the impact of aesthetic interventions on urban streets and their influence on the behavior and perceptions of urban road users. A structured questionnaire was distributed to a sample of 169 residents of Volos, Greece, to assess perceptions of street aesthetics and mobility habits. Data analysis included descriptive statistics to identify patterns and factors influencing user preferences and behavioral changes. Study findings indicate that road users are willing to incur higher travel costs in exchange for aesthetic improvements, particularly when paired with reduced travel times. Moreover, pedestrians reported a tendency to modify their routes in response to enhanced urban aesthetics. Moreover, it was found that prior mobility patterns and environmental awareness can impact the acceptability of aesthetic interventions, while demographic factors, such as age and gender exert a lesser influence. Results further demonstrate that thoughtfully designed streetscapes improve pedestrian comfort and safety, promoting higher rates of walking and cycling. The study underscores the importance for policymakers and urban planners to integrate aesthetic improvements into broader sustainable transportation strategies to foster healthier and more attractive urban environments.

Urban intersection design generally assumes that drivers follow idealised turning paths defined by circular arcs and, in some cases, transition curves. In practice, however, observed left-turn trajectories often depart from these theoretical paths. This study proposes a curvature-based framework for quantifying such deviations at the movement level by directly comparing observed vehicle paths with theoretical design arcs derived from intersection geometry. Naturalistic traffic data were collected at five urban intersections in Thessaloniki, Greece, using elevated video cameras. Left-turn passenger-vehicle trajectories were extracted, georeferenced, and compared with corresponding theoretical paths. For each trajectory, a best-fit circular arc was estimated, and the deviation between observed and theoretical path geometry was quantified through radius- and curvature-based percentage indicators. These indicators were then aggregated at the intersection and movement level using medians, deciles and the relative shares of flatter-than-theoretical and tighter-than-theoretical trajectories. The results show that deviations from theoretical geometry are strongly movement-specific and that the strongest flattening and tightening patterns were statistically supported by movement-level Wilcoxon signed-rank tests. In some cases, drivers systematically opened the turn relative to the design path, with median curvature deviations reaching about −14% and flatter-than-theoretical shares as high as 94%. In other cases, the opposite pattern was observed, with median curvature deviations exceeding +37% and tighter-than-theoretical shares reaching 100%. Other movements remained close to the theoretical path or displayed substantial internal heterogeneity. Overall, the proposed framework offers a practical and interpretable way to screen left-turn movements for systematic departure from design intent. This is important because it allows the analysis to move from individual path overlays to a movement-level geometric reading that can support consistency checks, intersection review and future integration with speed- and conflict-based safety analyses. These results should nonetheless be regarded as exploratory and descriptive: neither the circle-fitting residuals nor the coordinate-level geometric accuracy of the extracted trajectories were formally validated in the present study, and the reported RDP/CDP values are, therefore, not intended for use as precision-survey quantities or as a stand-alone design basis.

Under growing urbanization and environmental challenges, sustainable urban mobility has become a critical priority for cities worldwide. Public Transport (PT) systems play a central role in reducing car dependency, lowering emissions, increasing network capacity, and promoting more equitable and efficient access to urban spaces for all users. Hence, the present paper aims to investigate PT preferences in the city of Larissa, Greece. Larissa is a medium-sized city currently serviced only by buses, and is currently focusing on the potential introduction of a new tram system to operate in parallel with existing bus services. To this end, a SP survey was designed and implemented, resulting in 972 observations that were collected for further statistical analysis. Survey results show a slight preference for trams over buses, with 54.63% selecting the tram and 45.37% favoring the buses. Moreover, a context-based segmentation pipeline was established using PCA, DBSCAN and t-SNE algorithms, aiding the visualization of existing clusters for transport choice approaches. Afterwards, a series of mixed logit models was applied, and statistically significant variables influencing mode choice were determined. The study also examines Value of Time (VoT) metrics and finds that respondents assign lower VoTs to trams than to buses, especially in out-of-vehicle segments of the journey, such as waiting and walking, and therefore consider trams as more pleasant and less burdensome. The findings also indicate that passengers place a high value on the quality of infrastructure related to access and waiting times, underlining the need to improve the overall user experience beyond the vehicle itself. In summary, the present research offers valuable insights into how the introduction of a tram system could possibly reshape PT usage patterns when compared with the legacy existing bus services.

This study investigates left-turn safety at urban intersections using surrogate safety measures derived from field video observations. Time-to-Collision (TTC) among motorized traffic and Post-Encroachment Time (PET) among pedestrian and motorized traffic were extracted for left-turn conflicts across five intersection types in Thessaloniki, Greece, and linked to geometric attributes, signal operations, and traffic conditions. Count-based models (Poisson, Negative Binomial) were estimated alongside machine-learning approaches (Random Forest, Gradient Boosting with Poisson loss). For PET events, the Poisson model had the best balance of parsimony and predictive accuracy, whereas the Negative Binomial model provided a superior fit for TTC events. Results indicate that PET-defined conflicts increased with pedestrian volume and the presence of shared and protected left-turn lanes, and decreased with higher opposing flow, greater average acceleration, and wider end-approach lanes. By contrast, TTC events were associated with lower average speeds, the presence of protected signal phasing for left turns, and the number of passenger cars. Machine-learning models underperformed relative to classical count models, reflecting limited sample size and the discrete event structure. The analysis indicates that the determinants of TTC and PET differ, with certain variables such as pedestrian activity and lane configuration having contrasting effects on the two surrogate safety measures. The analysis reveals that pedestrian demand and shared lane configurations significantly increase PET occurrences, whereas TTC events are more strongly associated with vehicle volumes, speeds, and signal phasing. This distinction underscores the importance of tailoring safety assessment and intervention strategies to the type of interaction being evaluated.

With advancements in computer vision and cloud computing, Surrogate Safety Measures (SSMs) now provide actionable insights to mitigate safety concerns before collisions occur. This study, conducted as part of the STREET21 research project and contributes to the existing body of knowledge by examining Post-Encroachment Time (PET), a time-based SSM, at a high-traffic urban intersection which many young vulnerable users (university students) cross as pedestrians for their daily commuting needs. In total 513 traffic conflict events were identified and mapped for the purposes of the analysis. The spatial analysis provides critical insights into the patterns of traffic conflicts. Results of the quantitative analysis demonstrate that pedestrian conflicts predominantly involved right-turning vehicles, followed by through vehicles, potentially indicative of red-light violations. The applied methodology underscores the efficacy of video analytics as a scalable alternative to traditional crash data analysis, enabling the evaluation of intersection designs and temporary treatments before permanent implementation.

The EU sets the path towards zero CO₂ emissions for new passenger cars in the future. Reaching net zero, there will be a period of co-existence between conventional vehicles and zero-emission vehicles. Engineers and policymakers should proceed to direct approaches, taking steps to reduce road pollution by reassessing the road design. Roundabouts enforce speed variations. Depending on the driving behaviour, can result in high pollutant emissions. The objective of this paper is to understand the factors and the parameters that contribute to high pollutant emissions. The trajectories of 260 vehicles at six multilane roundabouts were analyzed. Video image processing techniques allowed the extraction of accurate kinematic characteristics gathered on the field using a UAV. The VSP methodology was applied to calculate carbon dioxide. The results of the quantitative analysis demonstrate strong relationships with road geometry. Road designers should consider the aspect of the environment and choose geometric variables wisely.