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Title: Incremental calibration of seat selection preferences in agent-based simulations of public transport scenarios
Authors: Andelfinger, Philipp
Chen, Yihao
Su, Boyi
Cai, Wentong
Zehe, Daniel
Eckhoff, David
Knoll, Alois
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Andelfinger, P., Chen, Y., Su, B., Cai, W., Zehe, D., Eckhoff, D., & Knoll, A. (2018). Incremental calibration of seat selection preferences in agent-based simulations of public transport scenarios. Proceedings of the 2018 Winter Simulation Conference, 833-844. doi:10.1109/WSC.2018.8632292
metadata.dc.contributor.conference: 2018 Winter Simulation Conference (WSC)
Abstract: The calibration of agent-based pedestrian simulation models requires empirical data. To avoid cost-intensive real-world experiments, human-in-the-loop simulations can be applied in which simulated pedestrians interact with human-controlled agents. However, the experiment results may be unrealistic if the human participants are presented with agents acting according to an uncalibrated model. We propose an incremental calibration approach that aims to address the circular dependency between the behaviour of human and simulated pedestrians. By incrementally adapting the parameters of the simulated agents to match the behaviour of the human participants, we aim to gradually approach a realistic interaction. We evaluate our approach using the simulation of the boarding procedure of a public transport vehicle in 2D and virtual reality experiments. The calibration results are compared with those gathered from a traditional non-incremental calibration. Our results indicate the feasibility of our approach and highlight the necessity for future research on efficient simulation model calibration.
ISBN: 9781538665725
DOI: 10.1109/WSC.2018.8632292
Schools: School of Computer Science and Engineering 
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:
Fulltext Permission: open
Fulltext Availability: With Fulltext
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