Abstract
Activity-based models, as a specific instance of agent-based models, deal with agents that structure their activity in terms of (daily) activity schedules. An activity schedule consists of a sequence of activity instances, each with its assigned start time, duration and location, together with transport modes used for travel between subsequent activity locations. A critical step in the development of simulation models is validation. Despite the growing importance of activity-based models in modelling transport and mobility, there has been so far no work focusing specifically on statistical validation of such models. In this paper, we propose a six-step Validation Framework for Activity-based Models (VALFRAM) that allows exploiting historical real-world data to assess the validity of activity-based models. The framework compares temporal and spatial properties and the structure of activity schedules against real-world travel diaries and origin-destination matrices. We confirm the usefulness of the framework on three activity-based transport models.
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Notes
- 1.
Valid model is a model of sufficient accuracy. We use these terms interchangeably in the following text.
- 2.
We have also experimented with related Anderson-Darling and Cramér–von Mises statistics getting similar results. Kolmogorv-Smrnov was finally selected as it is widely known and easier to get insight into.
- 3.
Note, that none activities are added to the beginning and end of the activity schedule in order to preserve information about initial/terminal activity.
- 4.
Although we call M\(_{\text {A}}\) the rule-based model, it estimates activity count, durations and occasionally start times using linear-regression models based on data. All other activity schedule properties are based on rules constructed using expert knowledge.
- 5.
At least given the limited size of the RNN training dataset.
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Acknowledgement
This publication was supported by the European social fund within the framework of realizing the project “Support of inter-sectoral mobility and quality enhancement of research teams at Czech Technical University in Prague”, CZ.1.07/ 2.3.00/30.0034, period of the project’s realization 1.12.2012 – 30.6.2015. This publication was further supported by the Technology Agency of the Czech Republic (grant no. TE01020155).
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Drchal, J., Čertický, M., Jakob, M. (2016). Data Driven Validation Framework for Multi-agent Activity-Based Models. In: Gaudou, B., Sichman, J. (eds) Multi-Agent Based Simulation XVI. MABS 2015. Lecture Notes in Computer Science(), vol 9568. Springer, Cham. https://doi.org/10.1007/978-3-319-31447-1_4
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DOI: https://doi.org/10.1007/978-3-319-31447-1_4
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