INFORMATICS FOR COLLECTIVE DYNAMICS

The course will provide a rigorous introduction to collective dynamics of human crowds and similar systems (vehicles, animal collective motion, etc.). The students may benefit the concepts illustrated in various modeling problems involving multiple independent agents or congestion control.

At the end of the course, the students will

- Overview a variety of technologies necessary to observe complex systems consisting of many moving entities.
- Comprehend key concepts and measures utilized in assessing system states.
- Review and compare different modeling approaches.
- Understand the multitude of factors influencing the collective motion of independent agents.
- Recognize the broad applicability of these concepts across a wide range of practical problems.

This structured understanding will equip students with a comprehensive foundation for analyzing and modeling complex systems in various scientific and engineering contexts.

General understanding of tracking, modeling and simulation.

1. Sensing
Sensor technologies, tracking, counting and density estimation, localization

2. Key concepts in crowd dynamics:
Level of service, Fundamental diagram, Faster-is-slower effect etc.

3. Motion models:
Mechanics-based models, cellular automaton, stochastic models, agent based models, data driven models

4. Human factors:
Social groups, intrinsic features and intermittent features, synchronization, stability etc.

5. Collective dynamics of non-pedestrian flows:
Vehicular traffic, granular flows, animal swarms etc.

The referral text (articles) will be pointed out during the lecture.

One of the following:
- discussion of an existing article in the field
- implementation of a concept introduced in the course and discussion
- original research (proposal/implementation of a new technique that may lead to an original publication) and discussion

oral

1. scores in the 18-22 range will be awarded in the case of answers to the oral test that indicate sufficient knowledge and understanding of the topics addressed in the course; limited ability to develop autonomous solutions and application of the methods studied; limited ability in explaining methods and solutions.

2. scores in the 23-26 range will be awarded in the case of answers to the oral test that indicate a fair knowledge and understanding of the topics addressed in the course; discrete ability to develop autonomous solutions and application of the methods studied; discrete ability in explaining methods and solutions and ability to create connections between topics studied.

3. scores in the 27-30 range will be awarded in the case of answers to the oral test that indicate good or excellent knowledge and understanding of the topics addressed in the course; good or excellent ability to develop autonomous solutions and apply the methods studied; good or excellent ability to explain methods and solutions and ability to create connections between topics studied.

4. praise will be awarded only in the presence of demonstration of excellent knowledge, ability to understand with reference to the program, excellent ability to connect topics and illustrate with excellent communication skills.

The course is composed of frontal lessons based on slides. Students will also be proposed some discussion topics.