TY - GEN
T1 - On modeling and evolutionary optimization of nonlinearly coupled pedestrian interactions
AU - Shukla, Pradyumn Kumar
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Social force based modeling of pedestrians is an advanced microscopic approach for simulating the dynamics of pedestrian motion. The developments presented in this paper extend the widespread social force model to include improved velocity-dependent interaction forces. This modeling considers interactions of pedestrians with both static and dynamic obstacles, which can be also be effectively used to model pedestrian-vehicle interactions. The superiority of the proposed model is shown by comparing it with existing ones considering several thought experiments. Moreover, we apply an evolutionary algorithm to solve the model calibration problem, considering two real-world instances. The objective function for this problem comes from a set of highly nonlinear coupled differential equations. An interesting feature that came out is that the solutions are multi-modal. This makes this problem an excellent example for evolutionary algorithms and other such population based heuristics algorithms.
AB - Social force based modeling of pedestrians is an advanced microscopic approach for simulating the dynamics of pedestrian motion. The developments presented in this paper extend the widespread social force model to include improved velocity-dependent interaction forces. This modeling considers interactions of pedestrians with both static and dynamic obstacles, which can be also be effectively used to model pedestrian-vehicle interactions. The superiority of the proposed model is shown by comparing it with existing ones considering several thought experiments. Moreover, we apply an evolutionary algorithm to solve the model calibration problem, considering two real-world instances. The objective function for this problem comes from a set of highly nonlinear coupled differential equations. An interesting feature that came out is that the solutions are multi-modal. This makes this problem an excellent example for evolutionary algorithms and other such population based heuristics algorithms.
KW - Complex systems
KW - Microscopic modeling
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=77952349521&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-12239-2-3
DO - 10.1007/978-3-642-12239-2-3
M3 - Conference contribution
AN - SCOPUS:77952349521
SN - 3642122388
SN - 9783642122385
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 21
EP - 30
BT - Applications of Evolutionary Computation - EvoApplicatons 2010
T2 - EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, EvoApplicatons 2010
Y2 - 7 April 2010 through 9 April 2010
ER -