In shared space environments the movements of road users is not regulated by traffic rules, but is the result of spontaneous interaction between traffic users, who negotiate the priority according to social rules such as eye contact or courtesy behavior. However, appropriate micro simulation tools, which can reproduce the operation of shared spaces, are currently lacking. In this paper, a multi-layer approach for representing the movement of road users and their interaction, based on the Social Force Model, is developed. In a free-flow layer a realistic path is calculated for each user towards his destination, while a conflict layer is used for detecting possible conflict situations and computing an appropriate reaction. The novelty of this work in the field of shared space modeling is in the implementation of group dynamics and a SFM based approach for cyclists. The presented approach is qualitatively tested in different traffic situations involving cyclists, pedestrians and pedestrian groups, and shows realistic behavior.

A multi-layer social force approach to model interactions in shared spaces using collision prediction

A hybrid social influence model (HSIM) has been proposed which is a novel and automatic method for pedestrian motion segmentation. One of the major attractions of the HSIM is its capability to handle motion segmentation when the pedestrian flow is randomly distributed. In the proposed HSIM, first the motion information has been extracted from the input video through particle initialization and optical flow. The particles are then examined to keep only the significant and nonstationary particles. To detect consistent segments, the communal model (CM) is adopted that models the influence of particles on each other. The CM infers influence from uncorrelated behaviors among particles and models the effect that particle interactions have on the spread of social behaviors. Finally, the detected segments are refined to eliminate the effects of oversegmentation. Extensive experiments on four benchmark datasets have been performed, and the results have been compared with two baseline and four state-of-the-art motion segmentation methods. The results show that HSIM achieves superior pedestrian motion segmentation and outperforms the compared methods in terms of both Jaccard Similarity Metric and F-score.

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A hybrid social influence model for pedestrian motion segmentation

The turning behavior is one of the most challenging driving maneuvers under non-protected phase at mixed-flow intersections. Currently, one-dimensional simulation models focus on car-following and gap-acceptance behaviors in pre-defined lanes with few lane-changing behaviors, and they cannot model the lateral and longitudinal behaviors simultaneously, which has limitation in representing the realistic turning behavior. This paper proposes a three-layered “plan-decision-action” (PDA) framework to obtain acceleration and angular velocity in the turning process. The plan layer firstly calculates the two-dimensional optimal path and dynamically adjusts the trajectories according to interacting objects. The decision layer then uses the decision tree method to select a suitable behavior in three alternatives: car-following, turning and yielding. Finally, in the action layer, a set of corresponding operational models specify the decided behavior into control parameters. The proposed model is tested by reproducing 210 trajectories of left-turn vehicles at a two-phase mixed-flow intersection in Shanghai. As a result, the simulation reproduces the variation of trajectories, while the coverage rate of the trajectories is 88.8%. Meanwhile, both the travel time and post-encroachment time of simulation and empirical turning vehicles are similar and do not show statistically significant difference.

A two-dimensional simulation model for modelling turning vehicles at mixed-flow intersections

Virtual geographic environments (VGEs) are extensively used to explore the relationship between humans and environments. Crowd simulation provides a method for VGEs to represent crowd behaviors that are observed in the real world. The social force model (SFM) can simulate interactions among individuals, but it has not sufficiently accounted for inter-group and intra-group behaviors which are important components of crowd dynamics. We present the social group force model (SGFM), based on an extended SFM, to simulate group behaviors in VGEs with focuses on the avoiding behaviors among different social groups and the coordinate behaviors among subgroups that belong to one social group. In our model, psychological repulsions between social groups make them avoid with the whole group and group members can stick together as much as possible; while social groups are separated into several subgroups, the rear subgroups try to catch up and keep the whole group cohesive. We compare the simulation results of the SGFM with the extended SFM and the phenomena in videos. Then we discuss the function of Virtual Reality (VR) in crowd simulation visualization. The results indicate that the SGFM can enhance social group behaviors in crowd dynamics.

Social Force Model-Based Group Behavior Simulation in Virtual Geographic Environments

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Advances in Complex Systems: Already a New Name!

In the field of traffic road design, the shared space approach aims to develop roads from mere traffic infrastructures to public spaces, compelling higher interaction between road users. In this paper we develop the fundamentals for a micro-simulation tool based on the Social Force Model, to represent the motion of road users in such layouts. Working with the observed behavior of users in a pedestrian-friendly intersection in the city of Braunschweig (D), a multi-layer structured model is developed, in which each layer is designated to handle different situations, from free-flow movements to user interactions in crowded situations. Visibility graphs and clothoid estimations are used for designing trajectories of road users for the free flow movement. Furthermore, an enhancement of the classical Social Force Model is provided in order to model long-range collision avoidance behavior. Finally, the enhanced simulation framework is validated by two observed scenarios, which include various conflicts between pedestrians and cars.

Modeling of shared space with multi-modal traffic using a multi-layer social force approach

When streets are designed according to the shared space principle, road user are encouraged to interact spontaneously with each other for negotiating the space These interaction mechanisms do not follow clearly defined traffic rules but rather psychological and social principles related to aspects of safety, comfort and time pressure However, these principles are hard to capture and to quantify, thus making it difficult to simulate the behavior of road users This work investigates traffic conflict situations between pedestrians and motorized vehicles, with the main objective to formulate a discrete choice model for the identification of the proper conflict solving strategy A shared space street in Hamburg, Germany, with high pedestrian volumes is used as a case study for model formulation and calibration Conflict situations are detected by an automatic procedure of trajectory prediction and comparison Standard evasive actions are identified, both for pedestrians and vehicles, by observing behavioral patterns A set of potential parameters, which may affect the choice of the evasive action, is formulated and tested for significance These include geometrical aspects, like distance and speed of the conflicting users, as well as conflict-specific ones, like time to collision A multinomial logit model is finally calibrated and validated on real situations The developed approach is realistic and ready for implementation in motion models for shared space or any other less organized traffic environment

N. Rinke

Papers

A multi-layer social force approach to model interactions in shared spaces using collision prediction

Modeling of shared space with multi-modal traffic using a multi-layer social force approach

A discrete choice model for solving conflict situations between pedestrians and vehicles in shared space

Simulating quality assurance and efficiency analysis between construction management and engineering geodesy

Should I Stay or Should I Go? A Discrete Choice Model for Pedestrian–Vehicle Conflicts in Shared Space