Relationships and Characteristics of Self-Organized Vehicle Groups and Other Remaining Vehicles in Disordered Heterogeneous Traffic

This study examines the relationships between self-organized vehicle groups and remaining vehicles (referred to as "remains") within heterogeneous, disordered traffic flows, and compares their characteristics. The findings reveal that leader–follower relationships are less prevalent among the remains, whereas connections with grouped vehicles are more frequent in both groups and remains. Additionally, groups form longer leader-follower networks with diverse pathways for the propagation of acceleration and deceleration waves. Furthermore, the results suggest that a typical vehicle platoon comprises a sparse distribution of remains interspersed around longer groups. Moreover, owing to their extended network lengths and varied densities, groups are likely to feature amplified acceleration and deceleration waves. The findings also suggest that some remains may gradually disperse, hindering the backward propagation of waves. Thus, this study provides novel insights into the formation and dynamics of groups and remains in disordered traffic, with the aim of enhancing traffic-flow modeling

Nudging Pedestrian Walking Dynamics Using Light Intensity and Color: A Virtual Reality Study

Crowd management attempts to efficiently and safely guide pedestrian crowds. "Nudging" is one way to steer the crowd, gently coaxing people in the right direction. In this study, we study whether light can be used to "nudge" pedestrians' operational walking dynamics. Specifically, we aim to determine the extent to which light intensity and light color influence the average walking speed of pedestrians. Six light conditions are tested in a VR experiment: regular white light (approx. 100 lux), dark (approx. 1 lux), bright (approx. 300 lux), blue, green, and red light. This study concludes that A) the average walking speed decreases in darker light (10.4%) conditions and increases in brighter light (7.7%) or colored (2.8% - 8%) conditions. In addition, pedestrians decelerate more slowly and cautiously in dark light conditions, while the acceleration and deceleration profile do not significantly change for bright, blue, green, and red light conditions. In addition, this study assessed whether a wireless HMD can be used to study pedestrians' average walking dynamics because a relatively new type of VR simulator was adopted. The validation analysis concludes that VR experiments featuring wireless HMD and open-plan movements overestimate step time (+7.5%) and step length (+12.8%) and underestimate the average walking speed (-22.8%). In addition, we find that relative trends regarding the impact of socio-demographic characteristics on the mean of the three analyzed metrics can, in most cases, be reproduced

Glossary for Research on Human Crowd Dynamics - 2nd Edition

Pedestrian and crowd dynamics involves multiple disciplines, including computer science, engineering, mathematics, physics, bio-mechanics, psychology, social science and more. For effective collaboration between disciplines, researchers need a common understanding of key concepts. To address this challenge, A Glossary for Human and Crowd Dynamics was published six years ago, providing researchers with a valuable reference for cross-disciplinary communication. We now present the second version, which includes 53 new concepts and 12 revisions from the first glossary, collaboratively developed by 65 contributors from various disciplines and regions around the world through a multi-stage process. This process involved identifying new concepts not covered in the first glossary and suggesting revisions to existing entries, voting on proposed additions and modifications, writing definitions for the selected concepts, and collaboratively revising and editing the entries. By introducing new terms and refining existing definitions, this glossary aims to facilitate clearer communication, improve conceptual consistency, and support collaboration among researchers working within the field of human and crowd dynamics from diverse perspectives

Effect of Response Time Distribution in Weak Lane Discipline on Linear Stability

The increase in mixed traffic with weak lane discipline (2D mixed traffic) has attracted significant research attention. To better replicate and understand traffic with weak lane discipline, this study examined the variation in response time relative to the position of the leading vehicle, including lateral shifts. Through experiments conducted using a driving simulator and functional fitting, we demonstrated that changes in response time due to longitudinal and lateral locational shifts are well represented by linear and exponential functions, respectively. Additionally, we proposed an extended formulation of the 2D optimal velocity model (2D OVM) that incorporates variable response times, termed the 2D OVM with varying sensitivities (2D OVMVS). The stability condition was derived using a linear approximation. A comparative analysis of the phase diagrams of the 2D OVM and 2D OVMVS, along with a sensitivity analysis, revealed that the proposed 2D OVMVS exhibited a larger unstable region in the phase diagram and lower stability in stable regions than the 2D OVM. As a result, in 2D traffic with weak lane discipline, the equilibrium formation of vehicles was more susceptible to disruption. Our findings indicate that variable response times, as observed in this study, substantially influence the stability of no-lane traffic. Unlike fixed-response models, incorporating response time variability accentuates unstable tendencies. This underscores the necessity of accounting for non-uniform response time distributions in future traffic models

Older Adult Stair and Walking Speeds from Controlled Trials as Inputs into Simulations of Retirement Home Evacuation

This work aims to add to the current database of human movement data, specifically, 3-stair descent speeds from controlled trials of typically aging older adults (n=212, aged 60-99) with and without mobility impairments. Additionally, to explore the impacts of model input parameters, stair and walking speeds obtained from controlled trials are used to simulate first-iteration Canadian retirement home egress scenarios with Pathfinder. Analysis of descending stair speeds reveal interesting trends and key inter-population variations. Moreover, when the stair and horizontal walking speeds determined from these controlled trials are used as inputs into the illustrative egress simulations, a difference in predicted egress outcomes are seen compared to when model defaults are used. Together, the findings indicate important egress considerations for a vulnerable population

The Evaluation of Data Fitting Approaches for Speed/Flow Density Relationships

This paper presents guidance on data-fitting approaches in the context of pedestrian and evacuation dynamics research. In particular, it examines parametric and non-parametric regression techniques for analysing speed/flow density relationships. Parametric models assume predefined functional forms, while non-parametric models provide flexibility to capture complex relationships. This paper evaluates a range of traditional statistical approaches and machine-learning techniques. It emphasises the importance of weighting unbalanced datasets to enhance model accuracy. Practical applications are illustrated using traffic and pedestrian evacuation data. This paper is intended to stimulate discussion on best practices for developing, calibrating, and testing macroscopic and microscopic evacuation models. It does not prescribe a one-size-fits-all solution for evacuation data fitting approaches, but it provides an overview of existing methods and analyses their advantages and limitations

Viral Transmission in Pedestrian Crowds: Coupling an Open-source Code Assessing the Risks of Airborne Contagion with Diverse Pedestrian Dynamics Models

We study viral transmission in crowds via the short-ranged airborne pathway using a purely model-based approach. Our goal is two-pronged. Firstly, we illustrate with a concrete and pedagogical case study how to estimate the risks of new viral infections by coupling pedestrian simulations with the transmission algorithm that we recently released as open-source code. The algorithm hinges on pre-computed viral concentration maps derived from computational fluid dynamics (CFD) simulations. Secondly, we investigate to what extent the transmission risk predictions depend on the pedestrian dynamics model in use. For the simple bidirectional flow under consideration, the predictions are found to be surprisingly stable across initial conditions and models, despite the different microscopic arrangements of the simulated crowd, as long as the crowd evolves in a qualitatively similarly way. On the other hand, when major changes are observed in the crowd's behaviour, notably whenever a jam occurs at the centre of the channel, the estimated risks surge drastically

The Birth of a New BIM Standard: From PED 2018 to 2023, New Parameters and Workflows "Going Live" for Everyone

Building Information Modelling (BIM) has become the de facto standard for the digital representation of buildings. However, from the pedestrian dynamics perspective, BIM Industry Foundation Classes (IFC) schema specification do not fully support data properties required for two-way data sharing with pedestrian modelling tools. An international team of academic and industry researchers, supported by buildingSMART International (bSI), is developing an Occupant Movement Analysis (OMA) standard. The project is focused on expanding the IFC schema specification to support workflows for pedestrian simulation tools and is close to completion. So far, multiple process maps and a list of data properties synchronised with several representative pedestrian modelling tools have been produced. This list of data properties was then converted into bSI's recommended flexible and machine interpretable Information Delivery Specification (IDS) format for specifying data exchange requirements and to add clarity. Currently, this is undergoing testing and review by the project team. Once completed, it will be submitted to bSI’s committees for review. Also, to support this work, a prototype open-source Add-in has been developed to demonstrate a two-way integrated data sharing between BIM authoring tools and pedestrian simulation tools. This standard will enhance data sharing between BIM authoring and pedestrian modelling tools by facilitating the capturing of the required data and addressing friction in multiple design iterations and reassessment

Effectiveness Verification of Evacuation Guidance Including Underground Passages Using Multi-objective Optimization

In this study, we approach the optimization problem of evacuation guidance assuming major terminal stations in Tokyo using crowd simulation and optimization algorithms. We propose a method to optimize multiple indicators with various guidance variables, including underground passages, and evaluate multiple scenarios obtained through optimization. The results of experiments using three algorithms: Random search, NSGA-II, and MOTPE, showed that MOTPE can be used to search for high-quality solutions quickly. Additionally, scenarios with guidance shortened the total evacuation time and reduced the congestion levels compared to scenario without guidance

Asymmetries in Group-Individual Collision Avoidance due to Social Factors

This research centers on analyzing frontal encounters between dyads (two-person groups) and individuals, aiming to measure each participant's role in avoiding collisions based on their deviation from their intended path. To achieve this, we establish the intended trajectory of each party by taking into account their walking direction leading up to the encounter. The largest discrepancy between this intended path and the observed path can be interpreted as the pedestrian's maximum lateral deviation.We show a noteworthy discrepancy in deviation between group members and individuals in face-to-face encounters. Furthermore, we conduct an in-depth analysis of how the intensity of interaction among group members impacts collision avoidance dynamics. Notably, the contrast in deviation between individuals and group members is most pronounced when the level of interaction within the group is high. Ultimately, our findings consistently indicate that higher levels of interaction lead to more substantial deviations in the trajectories of encountered individuals and underscore the significant role of social dynamics in influencing pedestrian behavior during frontal encounters