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Audiovisual . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Audiovisual . 2025
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2025
License: CC BY
Data sources: Datacite
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How 東京's Scramble Crossing Works - Explained with Petri Nets

Authors: Hense, Andreas;

How 東京's Scramble Crossing Works - Explained with Petri Nets

Abstract

How can a Petri net explain the behavior of one of the world’s busiest pedestrian crossings?This video analyzes the Shibuya Scramble Crossing in Tokyo, often perceived as chaotic due to its extremely high pedestrian density, and demonstrates how its operation is in fact governed by a well-structured control logic. The video explains how traffic light phases for vehicles and pedestrians are coordinated to maximize throughput while maintaining safety. Using a Petri net model, the timing, synchronization, and mutual exclusion between traffic flows are made explicit. The model reveals that the apparent disorder of the crossing emerges from a carefully designed and formally structured system. The example illustrates how Petri nets can be used to analyze, communicate, and reason about complex real-world control systems where concurrency, safety, and efficiency are critical. This is video #65 of the BPASeries. Acknowledgements:The author gratefully acknowledges Professor Kimio Momose for hosting him in Tokyo during a sabbatical stay and for providing an inspiring research environment. Sincere thanks are also extended to Professor Wil van der Aalst for introducing Professor Momose and enabling this valuable academic connection.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average