Virtualized traffic via various simulation models and real‐world traffic data are promising
approaches to reconstruct detailed traffic flows. A variety of applications can benefit from the …

Human crowds have become hotspot research, particularly in crowd analysis to ensure
human safety. Adaptations of machine learning (ML) approaches, especially deep learning …

In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to
learn the collective behavior patterns of pedestrians in crowded scenes. Collective …

This paper analyzes literatures on crowd evacuation based on data extracted from Web of
Science by applying bibliometric approaches. In specific, reference co-citation analysis …

Understanding human behavior and predicting evacuation processes subsequently to an
earthquake are critical aspects to provide valuable information to support disaster response …

Collective behaviors characterize the intrinsic dynamics of the crowds. Automatically
understanding collective crowd behaviors has important applications to video surveillance …

Overcrowding and stampedes may occur in public places with the gathering of crowds. To
mitigate and prevent risk, the accident mechanism and methods for monitoring and …

Due to the high volume of documents in the pedestrian safety field, the current study
conducts a systematic bibliometric analysis on the researches published before October 3 …

The literature of pedestrian, crowd and evacuation dynamics is captured in its approximate
full scope and is analysed at various levels using scientometric indicators of its underlying …

Modeling pedestrian dynamics and their implementation in a computer are challenging and
important issues in the knowledge areas of transportation and computer simulation. The aim …