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Multilevel Modeling as a Methodology for the Simulation of Human Mobility

Luca Serena, Moreno Marzolla, Gabriele D'Angelo, Stefano Ferretti

TL;DR

It is argued that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the “micro” and “macro” layer, where individual entities and long-range interactions are described.

Abstract

Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably exists between the sub-models, however, implies the need for maintaining consistency between the various components, more so when different simulation paradigms are employed (e.g., sequential vs parallel, discrete vs continuous). In this paper we argue that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the "micro" and "macro" layer, where individual entities (micro) and long-range interactions (macro) are described. In this paper we investigate the challenges of multilevel modeling, and describe some preliminary results using prototype implementations of multilayer simulators in the context of epidemic diffusion and vehicle pollution.

Multilevel Modeling as a Methodology for the Simulation of Human Mobility

TL;DR

It is argued that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the “micro” and “macro” layer, where individual entities and long-range interactions are described.

Abstract

Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably exists between the sub-models, however, implies the need for maintaining consistency between the various components, more so when different simulation paradigms are employed (e.g., sequential vs parallel, discrete vs continuous). In this paper we argue that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the "micro" and "macro" layer, where individual entities (micro) and long-range interactions (macro) are described. In this paper we investigate the challenges of multilevel modeling, and describe some preliminary results using prototype implementations of multilayer simulators in the context of epidemic diffusion and vehicle pollution.
Paper Structure (10 sections, 2 equations, 6 figures, 1 table)

This paper contains 10 sections, 2 equations, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background and Related Works
  3. Multilevel Modeling
  4. Advantages
  5. Challenges
  6. Implementation
  7. Case Studies
  8. Epidemic Modeling
  9. Green Mobility to Reduce Pollution
  10. Conclusions

Figures (6)

  • Figure 1: Multilayer model using different types of sub-models and execution policies.
  • Figure 2: Top: Classification of the simulators used in the case studies. Bottom: classification of the models used in the case studies.
  • Figure 3: Rationale of the multilevel models for our use cases.
  • Figure 4:
  • Figure 5: Four snapshots of the NetLogo model at different times. Green turtles = electric vehicles. Blue turtles = LGP-based vehicles. Black turtles = gasoline vehicles. White patches = no pollution. Red patch = medium pollution. Black patches = maximum pollution (best viewed in color).
  • ...and 1 more figures