Pedestrian flow parameters are analysed in this study considering linear and non-linear relationships between stream flow parameters using conventional and soft computing approach. Speed-density relationship serves as...Pedestrian flow parameters are analysed in this study considering linear and non-linear relationships between stream flow parameters using conventional and soft computing approach. Speed-density relationship serves as a fundamental relationship, Single-regime con- cepts and deterministic models like Greenshield and Underwood were applied in the study to describe bidirec- tional flow characteristics on sidewalks and carriageways around transport terminals in India. Artificial Neural Net- work （ANN） approach is also used for traffic flow mod- elling to build a relationship between different pedestrian flow parameters. A non-linear model based on ANN is suggested and compared with the other deterministic models. Out of the aforesaid models, ANN model demonstrated good results based on accuracy measure- ment. Also these ANN models have an advantage in terms of their self-processing and intelligent behaviour. Flow parameters are estimated by ANN model using MFD （Macroscopic Fundamental Diagram）. Estimated mean absolute error （MAE） and root mean square error （RMSE）values for the best fitted ANN model are 3.83 and 4.73 m/ min, respectively, less than those for the other models for sidewalk movement. Further estimated MAE and RMSE values of ANN model for carriageway movement are 4.02 and 4.98 m/min, respectively, which are comparatively less than those of the other models. ANN model gives better performance in fitness of model and future prediction of flow parameters. Also when using linear regression model between observed and estimated values for speed and flow parameters, performance of ANN model gives better fitness to predict data as compared to deterministic model. R value for speed data prediction is 0.756 and for flow data pre- diction is 0.997 using ANN model at sidewalk movement around transport terminal.展开更多
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...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.展开更多
基金the research project ‘‘INDO HCM WP-7’’ sponsored by CSIR-CRRI
文摘Pedestrian flow parameters are analysed in this study considering linear and non-linear relationships between stream flow parameters using conventional and soft computing approach. Speed-density relationship serves as a fundamental relationship, Single-regime con- cepts and deterministic models like Greenshield and Underwood were applied in the study to describe bidirec- tional flow characteristics on sidewalks and carriageways around transport terminals in India. Artificial Neural Net- work （ANN） approach is also used for traffic flow mod- elling to build a relationship between different pedestrian flow parameters. A non-linear model based on ANN is suggested and compared with the other deterministic models. Out of the aforesaid models, ANN model demonstrated good results based on accuracy measure- ment. Also these ANN models have an advantage in terms of their self-processing and intelligent behaviour. Flow parameters are estimated by ANN model using MFD （Macroscopic Fundamental Diagram）. Estimated mean absolute error （MAE） and root mean square error （RMSE）values for the best fitted ANN model are 3.83 and 4.73 m/ min, respectively, less than those for the other models for sidewalk movement. Further estimated MAE and RMSE values of ANN model for carriageway movement are 4.02 and 4.98 m/min, respectively, which are comparatively less than those of the other models. ANN model gives better performance in fitness of model and future prediction of flow parameters. Also when using linear regression model between observed and estimated values for speed and flow parameters, performance of ANN model gives better fitness to predict data as compared to deterministic model. R value for speed data prediction is 0.756 and for flow data pre- diction is 0.997 using ANN model at sidewalk movement around transport terminal.
基金The research was supported from the National Natural Science Foundation of China(No.71871189,No.72104205,and No.71974161)the Science and Technology Development Funds of Sichuan Province(No.2020YFS0291)the Open Research Fund of SKLFS(No.HZ2019-KF14),China Scholarship Council,and the transportation research group at The University of Melbourne.
文摘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.
