TY  - JOUR
PY  - 2020//
TI  - Simulating crowd evacuation in a social force model with iterative extended state observer
JO  - Journal of advanced transportation
A1  - Wei, Juan
A1  - Fan, Wenjie
A1  - Li, Zhongyu
A1  - Guo, Yangyong
A1  - Fang, Yuanyuan
A1  - Wang, Jierui
SP  - e4604187
EP  - e4604187
VL  - 2020
IS  - 
N2  - Due to the interaction and external interference, the crowds will constantly and dynamically adjust their evacuation path in the evacuation process to achieve the purpose of rapid evacuation. The information from previous process can be used to modify the current evacuation control information to achieve a better evacuation effect, and iterative learning control can achieve an effective prediction of the expected path within a limited running time. In order to depict this process, the social force model is improved based on an iterative extended state observer so that the crowds can move along the optimal evacuation path. First, the objective function of the optimal evacuation path is established in the improved model, and an iterative extended state observer is designed to get the estimated value. Second, the above model is verified through simulation experiments. The results show that, as the number of iterations increases, the evacuation time shows a trend of first decreasing and then increasing.<p />  <p>Language: en</p>
LA  - en
SN  - 0197-6729
UR  - http://dx.doi.org/10.1155/2020/4604187
ID  - ref1
ER  -