Lane Formation Beyond Intuition Towards an Automated Characterization of Lanes in Counter-flows

Pedestrian behavioural dynamics have been growingly investigated by means of (semi)automated computing techniques for almost two decades, exploiting advancements on computing power, sensor accuracy and availability, computer vision algorithms. This has led to a unique consensus on the existence of significant difference between unidirectional and bidirectional flows of pedestrians, where the phenomenon of lane formation seems to play a major role. The collective behaviour of lane formation emerges in condition of variable density and due to a self-organisation dynamic, for which pedestrians are induced to walk following preceding persons to avoid and minimize conflictual situations. Although the formation of lanes is a well-known phenomenon in this field of study, there is still a lack of methods offering the possibility to provide an (even semi-) automatic identification and a quantitative characterization. In this context, the paper proposes an unsupervised learning approach for an automatic detection of lanes in multi-directional pedestrian flows, based on the DBSCAN clustering algorithm. The reliability of the approach is evaluated through an inter-rater agreement test between the results achieved by a human coder and by the algorithm

Age and Group-driven Pedestrian Behaviour: from Observations to Simulations

The development of pedestrian simulation systems requires the acquisition of empirical evidences about human behaviour for sake of model validation. In this framework, the paper presents the results of an on field observation of pedestrian behaviour in an urban crowded walkway. The research was aimed at testing the potentially combined effect of ageing and grouping on speed and proxemic behaviour. In particular, we focused on dyads, as the most frequent type of groups in the observed scenario. Results showed that in situation of irregular flows elderly pedestrians walked the 40% slower than adults, due to locomotion skill decline. Dyads walked the 30% slower than singles, due to the need to maintain spatial cohesion to communicate (proxemics). Results contributed to refine the parametric validation of the agent-based simulation system ELIAS38

Calibration and validation of a simulation model for predicting pedestrian fatalities at unsignalized crosswalks by means of statistical traffic data

This work presents a simulation model for unsignalized crosswalks which takes into account collisions between vehicles and pedestrians, thus allowing to assess the estimated yearly pedestrian fatality. In particular, we focus on a method to calibrate such a model combining measurable crosswalk characteristics, such as maximum speed limit or drivers' compliance, with statistical data for past accidents obtained from local municipality. In order to perform simulations under realistic conditions, we constructed a one-week scenario where pedestrian and vehicle traffic vary using specific patterns each hour of the week. The constructed traffic profile is based on openly available data and the suitability for the scenario considered (a crosswalk in Milan, Italy) is investigated showing that cultural/lifestyle elements determine the variation of weekly traffic. Simulations using the constructed one-week scenario were used to obtain the only non-measurable parameter which account for pedestrians' and drivers' distraction. In addition, we also focused on the presence of elderly pedestrians which have different physiological characteristics compared to adults or children and are becoming an important part of the population in several countries around the globe. The simulation model presented here and the method suggested for calibration may be employed in different contexts, thus allowing to build an important tool to be used not only for transportation efficiency/optimization but also for safety analysis. Keywords: Traffic simulation, Accident prevention, Unsignalized crosswalk, Vehicle-pedestrian interaction, Weekly traffic variatio

Methodology for Gender Analysis in Transport: Factors with Influence in Women’s Inclusion as Professionals and Users of Transport Infrastructures

This work analyzes gendered processes by a methodology based on clustering factors with influence in the decision-making process of women as users or employees of the transport system. Considering gender as a social construction which changes over time and space, this study is based on the concept of a woman as a person who adopts this role in society. This paper performs a deep analysis of those factors women consider as needs and barriers to use or work in the transport system in four scenarios: railway public transport infrastructures, automated vehicles, bicycle sharing, and jobholders. A literature review and focus group discussions were performed under the consideration that the definition of woman includes the addition of several personal characteristics (age, sexual orientation, family responsibilities, and culture). The data analysis allowed the identification of fairness characteristics (FCs) that affect the interaction of women with the transport system for each scenario. A methodology for clustering the fairness characteristics identified the main areas of action to improve the inclusion of women within each use case. Further studies will be focused on the quantification and prioritization of the FCs through mathematical methods and the suggestion of inclusive measures by an interdisciplinary panel