Computational Model Library

Pedestrian Scramble (2.0.0)

This is a model intended to demonstrate the function of scramble crossings and a more efficient flow of pedestrian traffic with the presence of diagonal crosswalks.

Pedestrian Scramble V2.0.0 Screenshot.png

Release Notes

v2.0.0 serves as the full release of the Pedestrian Scramble model. This expands on v1.0.0 of the model by addressing a few major items from the “EXTENDING THE MODEL” section in the narrative documentation, like the ability for agents to change between walking types and the presence of intermediate travelling when the diagonals are enabled. While I do list one more way to extend the model further, your input on other ways to improve is much appreciated!

Associated Publications

Takami, Sho, “Estimating Pedestrian Crossing Times at Scramble Crossings via Machine Learning and Agent-Based Modeling” (2025). CURE Proceedings. 18. https://huskiecommons.lib.niu.edu/studentengagement-cureposters/18

Takami, Sho, “Estimating Pedestrian Crossing Times at Scramble Crossings via Machine Learning and Agent-Based Modeling” (2025). Honors Capstones. 1561. https://huskiecommons.lib.niu.edu/studentengagement-honorscapstones/1561

Pedestrian Scramble 2.0.0

This is a model intended to demonstrate the function of scramble crossings and a more efficient flow of pedestrian traffic with the presence of diagonal crosswalks.

Release Notes

v2.0.0 serves as the full release of the Pedestrian Scramble model. This expands on v1.0.0 of the model by addressing a few major items from the “EXTENDING THE MODEL” section in the narrative documentation, like the ability for agents to change between walking types and the presence of intermediate travelling when the diagonals are enabled. While I do list one more way to extend the model further, your input on other ways to improve is much appreciated!

Version Submitter First published Last modified Status
2.0.0 Sho Takami Tue Jun 10 16:10:58 2025 Tue Jun 10 16:20:09 2025 Published
1.0.0 Sho Takami Tue Nov 30 03:17:35 2021 Tue Jun 10 16:20:01 2025 Published

Discussion

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept