Research On Slow Traffic Simulation Based On Netlogo And Social Force Model

Slow travel is an important part of the travel chain.China ’s long-term traditional caroriented traditional transportation planning allocates more road space to motor vehicles,which leads to it show the obvious feature of“pedestrian-bike-common board” and backward and inefficient development.As the population grows,the problem of mixed traffic security becomes more prominent,which places higher demands on slow travel research.The paper takes traffic individuals as the research object,analyzes its feature and the defects of the traditional social force model,to construct mixed traffic simulation models and build a simulation platform for verification and application.This promotes the perfection and development of the social force model and provides a theoretical basis for the design and management of slow moving facilities.Firstly,using video technology collect pedestrian trajectories to analyze pedestrian flow,speed,acceleration and other parameters.And the paper summarize the spatial motion,mass,speed,and acceleration of traffic individuals’ micro-movement feature.These lay a foundation to improve and verify traffic models for the paper.And then,the paper analyze the principle and defects of the original social force and its revised model,and introduce the semi-ellipsoidal scope,the painter algorithm’s vision occlusion mechanism,anisotropy,and critical action distance,and further improve the psychological force,self-drive,and exit attractive to build a relatively complete pedestrian model.Then,the paper analyze the principles and defects of the Moussaid grouping model,and propose a basic group model based on normal repulsion,normal attraction,and angular communication force with the grouping feature to make it more realistic.Then,the paper abstract bicycle’s shape and construct it’s elliptical model;and then consider the interference of pedestrians and bicycle to establish a pedestrian-bicycle interactive social force model with the improved pedestrian model and the bicycle’s feature.And the paper sorts out the relationship of forces in the model and proposes a parameter calibration idea based on selfdriving force.Next,the accurate range of the self-driving force is calibrated with pedestrian data,and then other parameter values are repeatedly optimized by combining the effects of simulation and data analysis.Finally,using netlogo set up a simulation environment to reproduce the transcendence and avoidance behavior of traffic individuals in simple scenes,then the phenomenon of selforganization,bottleneck swing,exit arching in complex scenarios,then the interaction between bicycle and pedestrian at the crossroads,and then to analyse the density-speed basic map data,these comprehensively verified the validity of the model.Finally,the paper analyzes the influence of different channel widths on the flow velocity and the suggested channel widths under different mixed flow rates.