Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data

Johansson, Anders; Helbing, Dirk; Shukla, Pradyumn Kumar

doi:10.1142/s0219525907001355

Cited by 450 publications

(358 citation statements)

References 26 publications

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“…In order to determine a reasonable value for the interaction strength A and the interaction range B, the calibration method of Johansson et al (2008) is followed: the trajectory of an individual agent is simulated while the agent is reacting to close-by agents (cars or pedestrians) who are moving according to the tracked trajectories. A relative distance error is calculated at the end of each run.…”

Section: Calibration Methodology and Resultsmentioning

confidence: 99%

“…However, the full representation of reality is strongly dependent on the choice of interaction parameters. During the past years, researchers have progressively calibrated the SFM using empirical data (Helbing, et al, 2000;Johansson, et al, 2008;Steiner, et al, 2007). Since the SFM is extended for shared space environments, the new interaction strengths and ranges need to be calibrated.…”

Section: Calibration and Simulationmentioning

confidence: 99%

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Modelling shared space users via rule-based social force model

Anvari

Bell

Sivakumar

et al. 2015

Transportation Research Part C: Emerging Technologies

131

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The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design, achieve solutions for optimal design features before implementation, and help getting the design closer to the system optimal. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since car movements are not as flexible as pedestrian movements, velocity angle constraints are included for cars. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs.

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Section: Calibration Methodology and Resultsmentioning

confidence: 99%

Section: Calibration and Simulationmentioning

confidence: 99%

Modelling shared space users via rule-based social force model

Anvari

Bell

Sivakumar

et al. 2015

Transportation Research Part C: Emerging Technologies

131

View full text Add to dashboard Cite

show abstract

“…For statistically investigating pedestrian flow, Lv et al [8] analyzed the similarity between the vehicle following and the pedestrian following at the single lane and developed the optimal velocity model to study the pedestrian following behavior. Then, the social force model was calibrated and developed to simulate real-world scenarios in the pedestrian movement for evacuation scenarios, pilgrimage, and urban environments [9][10][11]. Support 2 Journal of Advanced Transportation Vector Machine (SVM) algorithm, cellular automata model, and normal cloud model have been created to reveal the pedestrian density-flow relationship and evaluate pedestrian dynamics following behavior in a subway station [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Time Warping Algorithm Based Analysis of Pedestrian Shockwaves at Bottleneck

Sun

Gong

Yao

et al. 2018

Journal of Advanced Transportation

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Since the quantitative methodology analysis of the high-density pedestrian shockwaves at a bottleneck is limited, this paper proposes a dynamic time warping (DTW) algorithm for identifying, analyzing, and verifying the shockwaves. A set of real-world trajectory data is used to illustrate the proposed algorithm. Results show that the DTW algorithm is capable of depicting the pedestrian shockwaves elaborately and accurately. Results also show that the shockwave velocity is unsteady, as throughout time the gathering wave velocity and the evanescent wave velocity are decreasing and increasing, respectively. The mutual influence between followers and leaders is decreased when the shockwave spreads. There is a linear relationship between the shockwave velocity and density. Furthermore, singularities present a potential match solution to help identify the changing of pedestrian behaviors. The DTW algorithm for evaluating the pedestrian system stability has significant intrinsic features in the pedestrian traffic control and management.

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“…To address the issues above, various data-driven approaches have been proposed in the past few years. Some approaches aim to learn examples (mostly in terms of stateaction pairs) from video data which is then used to update the movement in particular situations instead of using behavior rules [7]- [12], while others try to calibrate the model parameters through automatic methods, so that the simulated behaviors can match the video data [13]- [17]. Existing works have shown the potential of data-driven approaches in crowd modeling, but they mainly focus on microscopic spatial crowd behaviors or motion update among existing examples.…”

Section: Introductionmentioning

confidence: 99%

A Generic Bi-Layer Data-Driven Crowd Behaviors Modeling Approach

Xing

Zhao

Zhang

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYCrowd modeling and simulation is an active research field that has drawn increasing attention from industry, academia and government recently. In this paper, we present a generic data-driven approach to generate crowd behaviors that can match the video data. The proposed approach is a bi-layer model to simulate crowd behaviors in pedestrian traffic in terms of exclusion statistics, parallel dynamics and social psychology. The bottom layer models the microscopic collision avoidance behaviors, while the top one focuses on the macroscopic pedestrian behaviors. To validate its effectiveness, the approach is applied to generate collective behaviors and re-create scenarios in the Informatics Forum, the main building of the School of Informatics at the University of Edinburgh. The simulation results demonstrate that the proposed approach is able to generate desirable crowd behaviors and offer promising prediction performance. key words: agent-based modeling, crowd simulation, data-driven approach, pedestrian behaviors

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Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data

Cited by 450 publications

References 26 publications

Modelling shared space users via rule-based social force model

Modelling shared space users via rule-based social force model

A Dynamic Time Warping Algorithm Based Analysis of Pedestrian Shockwaves at Bottleneck

A Generic Bi-Layer Data-Driven Crowd Behaviors Modeling Approach

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