Social force models for pedestrian traffic – state of the art

Xu, Chen; Treiber, Martin; Kanagaraj, Venkatesan; Li, Haiying

doi:10.1080/01441647.2017.1396265

Cited by 116 publications

(58 citation statements)

References 61 publications

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“…The pedestrian database of simulation software used to simulate pedestrian flow is based on the SFM [24]. The SFM can simulate important phenomena of escape panic [1,25,[28][29][30][32][33][34][35][36][37][38], such as "clogging", "faster is slower", and "mass behavior".…”

Section: Social Force Model (Sfm) Methodsmentioning

confidence: 99%

“…Porter et al [27] presented an integrated modeling framework to capture pedestrian walking behavior in congested and uncongested conditions, which the framework was built using a combination of concepts from the social force model. In addition, the robust model was also applied to provide valuable insights into simulate the dynamical features of escape panic [1,21,22], abnormal behaviors localization [28], exit-selecting behaviors analysis [29], detour behavior description [30], exit assignment strategy [31], pedestrian behavior analysis [32][33][34][35][36][37], and pedestrian traffic [38]. The main contribution of this study is the development of a pedestrian evacuation route choice model based on social force theory, which enables to consider the characteristics of pedestrian behavior in the large-scale public space (LPS).…”

Section: Social Force Model For Pedestrian Simulationmentioning

confidence: 99%

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Simulation of pedestrian evacuation route choice using social force model in large-scale public space: Comparison of five evacuation strategies

et al. 2019

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The primary objective of this study is to compare pedestrian evacuation strategies in the large-scale public space (LPS) using microscopic model. Data were collected by video recording from Tian-yi square for 36 hours in city of Ningbo, China. A pedestrian evacuation simulation model was developed based on the social force model (SFM). The simulation model parameters, such as reaction time, elasticity coefficient, sliding coefficient, et al, were calibrated using the real data extracted from the video. Five evacuation strategies, strategy 1 (S1) to strategy 5 (S5) involving distance, density and capacity factors were simulated and compared by indicators of evacuation time and channel utilization rate, as well as the evacuation efficiency. The simulation model parameters calibration results showed that a) the pedestrians walking speed is 1.0~1.5m/s; b) the pedestrians walking diameter is 0.3~0.4m; c) the frequency of pedestrian arrival and departure followed multi-normal distribution. The simulation results showed that, (a) in terms of total evacuation time, the performance of S4 and S5 which considering the capacity and density factors were best in all evacuation scenarios, the performance of S3 which only considering the density factor was the worst, relatively, and S1 and S2 which considering the distance factor were in the middle. (b) the utilization rate of channels under S5 strategy was better than other strategies, which performs best in the balance of evacuation. S3 strategy was the worst, and S1, S2 and S4 were in the middle. (c) in terms of the evacuation efficiency, when the number of evacuees is within 2, 500 peds, the S1 and S2 strategy which considering the distance factor have best evacuation efficiency than other strategies. And when the number of evacuees is above 2, 500 peds, the S4 and S5 strategy which considering the capacity factor are better than others.

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Section: Social Force Model (Sfm) Methodsmentioning

confidence: 99%

Section: Social Force Model For Pedestrian Simulationmentioning

confidence: 99%

Simulation of pedestrian evacuation route choice using social force model in large-scale public space: Comparison of five evacuation strategies

et al. 2019

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“…In the same year, Lakoba et al [22] explored several values for the social force model parameters and proposed a density‐based modification in the definition of the interactions, in order to produce a more realistic behaviour for low‐density conditions, preserving the original reliability in the high‐density situations. Recently, in [23], an updated and comprehensive review of the social force models was reported, pointing out several model variants, individual attributes, motion base cases, collective and emergent phenomena, and special examples of application. This continuous investigation of pedestrian behaviours led to the development of different simulation models: this is the case of PEDFLOW [24], where an agent‐based system is implemented in which each individual ‘negotiate’ its walking space or NOMAD [25, 26] where the social force concept is combined with an activity choice approach.…”

Section: State‐of‐the‐artmentioning

confidence: 99%

Simulation framework for pedestrian dynamics: modelling and calibration

Liberto

Nigro

Carrese

et al. 2020

IET Intelligent Transport Systems

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“…Internal driven movement is more complicated because it can be observed only under certain conditions such as location and flow status. By expanding the summary of individual and crowd motion cases, which are primarily internal driven as highlighted in [39], we developed a comprehensive classification of the internal driven movement as shown in Figure 2.…”

Section: Complex Movements Of Pedestrian Flowmentioning

confidence: 99%

A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement

Shi

Shiwakoti

et al. 2018

Journal of Advanced Transportation

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Complex movement patterns of pedestrian traffic, ranging from unidirectional to multidirectional flows, are frequently observed in major public infrastructure such as transport hubs. These multidirectional movements can result in increased number of conflicts, thereby influencing the mobility and safety of pedestrian facilities. Therefore, empirical data collection on pedestrians’ complex movement has been on the rise in the past two decades. Although there are several reviews of mathematical simulation models for pedestrian traffic in the existing literature, a detailed review examining the challenges and opportunities on empirical studies on the pedestrians complex movements is limited in the literature. The overall aim of this study is to present a systematic review on the empirical data collection for uni- and multidirectional crowd complex movements. We first categorized the complex movements of pedestrian crowd into two general categories, namely, external governed movements and internal driven movements based on the interactions with the infrastructure and among pedestrians, respectively. Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, diverging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, diverging, and random flows. We put emphasis on the need for the future global collaborative efforts on data sharing for the complex crowd movements.

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Social force models for pedestrian traffic – state of the art

Cited by 116 publications

References 61 publications

Simulation of pedestrian evacuation route choice using social force model in large-scale public space: Comparison of five evacuation strategies

Simulation of pedestrian evacuation route choice using social force model in large-scale public space: Comparison of five evacuation strategies

Simulation framework for pedestrian dynamics: modelling and calibration

A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement

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