A Comparative Analysis of Multi-Modal Transportation Network Resilience: Evaluating Stochastic Dynamic Traffic Assignment Algorithms

Kim Anderson; Taylor White; Sam White; Chris Harris

Authors

Kim Anderson PhD
Taylor White Associate Professor
Sam White Professor
Chris Harris Dr. Sc

Keywords:

Multi-modal transportation, Traffic assignment algorithms, Network resilience, Stochastic modeling, Urban transportation systems, Dynamic traffic management

Abstract

This study examines the resilience of multi-modal transportation networks through a comparative analysis of stochastic dynamic traffic assignment algorithms. By incorporating real-time data and predictive modeling, the research offers insights into optimizing traffic flow and enhancing network robustness. Findings indicate that advanced algorithms significantly improve transportation efficiency under varied conditions. The study contributes to the field by providing a framework for evaluating algorithm efficacy in complex urban environments.

Author Biographies

Kim Anderson, PhD

PhD
Massachusetts Institute of Technology
77 Massachusetts Avenue, Cambridge, MA 02139, USA

Taylor White, Associate Professor

Associate Professor
University of Cambridge
The Old Schools, Trinity Ln, Cambridge CB2 1TN, UK

Sam White, Professor

Professor
Monash University
Wellington Rd, Clayton VIC 3800, Australia

Chris Harris, Dr. Sc

Dr. Sc
University of Toronto
27 King's College Cir, Toronto, ON M5S, Canada

References

Yu Timkina, S., Stepanchuk, O. V., & Bieliatynskyi, A. A. (2019, December). The design of the length of the route transport stops’ landing pad on streets of the city. In IOP Conference Series: Materials Science and Engineering (Vol. 708, No. 1, p. 012032). IOP Publishing.