A modified universal pedestrian motion model: Revisiting pedestrian simulation with bottlenecks

Pedestrian flow through narrow exits is one the most important features of crowd dynamics and evacuation.This is a particularly important aspect of pedestrian simulation models in that the accuracy is highly dependent on their ability to produce realistic exit flow rates.We firstly identified the four parameters that are most critical for physical interactions of the social force model and then calibrated them against two well-controlled pedestrian experiments.With these calibrated parameters,we discussed the reasonable settings of sensitive parameters for different levels of pedestrian competitiveness.Then,we revisited the basic questions about the effect of the exit location,the bottleneck length,and the effect of obstacles on pedestrian egress.Our simulation results indicated that:(1)The effect of the exit location on the pedestrian egress efficiency is uncertain,and the evacuation efficiency is also related to the exit width and the level of urgency.(2)The"pass-way"after the exit also named as the bottleneck length has a negative impact on the evacuation performance only in the scenarios that the bottleneck length is not more than 2.0 meters.When the bottleneck length exceeds 2.0 meters,pedestrian outflow efficiency reaches an asymptotic.(3)Setting an obstacle near an exit is not leading to a longer pedestrian evacuation time,instead,it is effectively improving pedestrian evacuation.

A new heuristics model of simulating pedestrian dynamics based on Voronoi diagram

A new heuristics model based on the Voronoi diagram is presented to simulate pedestrian dynamics with the noncrowded state, in which these mechanisms of preference demand evading and surpassing, microscopic anti-deadlock, and site-fine-tuning are considered. The preference demand describes the willingness determination of detouring or following other pedestrians. In the evading and surpassing mechanisms, in order to achieve a balance between avoiding conflicts and minimizing detour distances, a new pair of concepts: "allow-areas and denial-areas" are introduced to divide the feasible region for pedestrians detour behaviors, in which the direction and magnitude of detour velocity are determined.A microscopic anti-deadlock mechanism is inserted to avoid deadlock problem of the counter-directional pedestrian. A site-fine-tuning mechanism is introduced to describe the behavior of avoiding getting too close to the neighbors in pedestrian movement. The presented model is verified through multiple scenarios, including the uni-or bi-direction pedestrian flow in the corridor without obstacles, the uni-direction pedestrian flow in the corridor with obstacles, and the pedestrian evacuation from a room with single-exit. The simulation results show that the velocity–density relationship is consistent with empirical data. Some self-organizing phenomena, such as lanes formation and arching are observed in the simulation.When pedestrians detour an obstacle, the avoiding area before the obstacle and the unoccupied area after the obstacle can be observed. When pedestrians evacuate through a bottleneck without panic, the fan-shaped crowd can be found, which is consistent with the actual observation. It is also found that the behavior of following others in an orderly manner is more conducive to the improvement of the overall movement efficiency when the crowd moves in a limited space.

AB065. Pedestrian modeling using the least-action principle

Background:In this work,we present a theoretical and experimental study of the natural movement of pedestrians when passing through a limited and known area of a shopping center.The modeling problem for the motion of a single pedestrian is complex and extensive;therefore,we focus on the need to design models taking into account mechanistic aspects of human locomotion.The theoretical study used mean values of pedestrian characteristics,e.g.,density,velocity,and many obstacles.We propose a human pedestrian trajectory model by using the least-action principle,and we compared it against experimental results.The experimental study is conducted in a Living Lab inside a shopping center using infrared cameras.For this experiment,we collected highly accurate trajectories allowing us to quantify pedestrian crowd dynamics.The tests included 20 runs distributed over five days with up to 25 test persons.Additionally,to gain a better understanding of subjects’trajectories,we simulated a background of different pathway scenarios and compared it with real trajectories.Our theoretical framework takes the minimum error between previously simulated and real point pathways to predict future points on the subject trajectory.Methods:This paper explores paths of 25 pedestrians along a known area.After obtaining the trajectory and their points of origin,we evaluated the speed with the objective to calculate the kinetic force of the pedestrian.In the present model,we assume that the principle of least action holds and using this concept we can obtain the potential force.Once all the forces of pedestrian movement are known,then we calculate the adjustment of the parameters employed in the equations of the social force model.Results:It is possible to reproduce observed results for real pedestrian movement by using the Principle of Least Action.In the first scenario,we focused on a pedestrian walking without obstacles.Using the actual trajectories of the experiment we obtained the necessary information and applied it to the Social Force Model.Our simulations were clearly able to reproduce the actual observed average trajectories for the free obstacle walking conditions.Conclusions:When a scenario does not represent free walking(obstacles,constraints),the potential energy and the kinetic energy are modified.Note that when the trajectory is real,the action is assumed to equal zero.That is the value of the potential energy changes in each interaction with a new obstacle.However,the value of the action remains.It is shown here that we can clearly reproduce some scenarios and calibrate the model according to different situations.Using different values of potential energy,we can obtain the values of the actual pathway.Nevertheless,as a significant extension concerning this model,it would be desirable to simulate cellular automata that could learn the situation and improve the approximation model to predict the real trajectories with more accuracy.

Temporal and spatial compliance behaviour of pedestrians under the influence of time pressure at signalized intersections:A pedestrian simulator study

Pedestrian safety is at high stakes due to the non-compliance practices of pedestrians at signalized intersections.Additionally,when pedestrians are hurrying,they deliberately engage in such unsafe behaviour.Therefore,the purpose of this study was to understand how time pressure(i.e.,feeling of hurry or saving time)affected pedestrians'decisions to follow traffic rules at signalized junctions.To achieve the study objectives,a pedestrian simulator setup was used to collect the crossing behaviour of forty participants at a four-legged signalized intersection.Non-compliance,one of the riskiest pedestrian behaviours,was examined with respect to three different forms,comprising dangerous temporal non-compliance(D-TNC),non-dangerous temporal non-compliance(ND-TNC),and spatial non-compliance(SNC)behaviour under two distinct conditions:baseline(i.e.,no time pressure)and time pressure conditions.The effects of demographics,usual walking features,and time pressure on D-TNC and ND-TNC were investigated using a multinomial regression model,while SNC behaviour was investigated using a binary regression model.It was interesting to note that the majority of the factors related to pedestrians’usual walking behaviour had an impact on all kinds of non-compliance behaviours.Importantly,the results also showcased that time pressure had a contrasting impact on D-TNC and ND-TNC behaviour whereas SNC behaviour increased under time pressure.Additionally,the varying impacts of D-TNC,ND-TNC,and SNC were also reflected in the occurrence of the crashes,which were probably triggered by discrepancies in the influence of time pressure on non-compliance behaviours.These findings highlight the need for technical solutions,educational outreach,and efficient enforcement practices to reduce pedestrians'non-compliant behaviour.

Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks

When arranging the pedestrian infrastructure,one of the most important components that make a tangible contribution to the safety of pedestrians is to organize the safe road crossing.In cities,pedestrians often cross a road in the wrong place due to established routes or inadequate location of crosswalks.Accidents with the participation of pedestrians who crossed the road neglecting the traffic rules,make up a significant part of the total amount of road accidents.In this paper,we propose a method that allows us,on the basis of the results of a computer simulation of pedestrian traffic,to obtain predicted routes for road crossing and to indicate optimal locations for crosswalks that take into account established pedestrian routes and increase their safety.The work describes an extension for the existing AntRoadPlanner simulation algorithm,which searches for and clusters points where pedestrians cross the roadway and suggests locations for new crosswalks.This method was tested on the basis of a comparative simulation of several territories before and after its application,as well as on the basis of a field study of the territories.The developed algorithm can also be used to search for other potentially dangerous places for pedestrians on plans of districts,for example,crossings in places with limited visibility.