From mindless masses to small groups: conceptualizing collective behavior in crowd modeling
Computer simulations are increasingly used to monitor and predict behavior at large crowd
events, such as mass gatherings, festivals and evacuations. We critically examine the crowd …
events, such as mass gatherings, festivals and evacuations. We critically examine the crowd …
Pedestrian crowd flows in shared spaces: Investigating the impact of geometry based on micro and macro scale measures
The motion dynamics of humans in crowded built environments during evacuations are
impacted by individuals' interactions with the physical environment particularly when the …
impacted by individuals' interactions with the physical environment particularly when the …
Detecting, tracking and counting people getting on/off a metropolitan train using a standard video camera
The main source of delays in public transport systems (buses, trams, metros, railways) takes
place in their stations. For example, a public transport vehicle can travel at 60 km per hour …
place in their stations. For example, a public transport vehicle can travel at 60 km per hour …
RDC-SAL: Refine distance compensating with quantum scale-aware learning for crowd counting and localization
As one of the most meaningful research topics in computer vision, crowd counting and
localization problems have been applied in many applications such as Video surveillance …
localization problems have been applied in many applications such as Video surveillance …
Convolutional neural network for crowd counting on metro platforms
J Zhang, J Liu, Z Wang - Symmetry, 2021 - mdpi.com
Owing to the increased use of urban rail transit, the flow of passengers on metro platforms
tends to increase sharply during peak periods. Monitoring passenger flow in such areas is …
tends to increase sharply during peak periods. Monitoring passenger flow in such areas is …
QE-DAL: A quantum image feature extraction with dense distribution-aware learning framework for object counting and localization
R Hu, Z Tang, R Yang - Applied Soft Computing, 2023 - Elsevier
Object counting and localization (OCL) was an essential problem in intelligent transportation
fields. The convolutional neural network (CNN)-based models transformed the OCL …
fields. The convolutional neural network (CNN)-based models transformed the OCL …
Real-time passenger flow anomaly detection considering typical time series clustered characteristics at metro stations
J Gu, Z Jiang, WD Fan, J Wu, J Chen - Journal of Transportation …, 2020 - ascelibrary.org
Real-time anomaly detection at metro stations is a very important task with considerable
implications for massive passenger flow organization and train timetable rescheduling. State …
implications for massive passenger flow organization and train timetable rescheduling. State …
Random utility models of pedestrian crowd exit selection based on SP-off-RP experiments
Detailed understanding of the factors based on which individual pedestrians select an exit in
a confined area, is of crucial importance in modelling crowd movement. Lack of explanatory …
a confined area, is of crucial importance in modelling crowd movement. Lack of explanatory …
Pedestrian monitoring techniques for crowd-flow prediction
The high concentration and flow rate of people in train stations during rush hours can pose a
prominent risk to passenger safety and comfort. In situ counting systems are a critical …
prominent risk to passenger safety and comfort. In situ counting systems are a critical …
Automated solutions for crowd size estimation
The crowd phenomenon frequently occurs in dense urban living environments. Crowd
counting or estimation helps to develop management strategies such as designing safe …
counting or estimation helps to develop management strategies such as designing safe …