Khaleghian, Seyedmehdi (The University of Tennessee at Chattanooga), Harris, Austin (UTC Research Institute), Bang, Tam (The University of Tennessee, Chattanooga), Sartipi, Mina (University of Tennessee at Chattanooga)

Digital Twin for Road Diet Analysis: A Decision Support System for Safety Enhancements on Chattanooga’s Frazier Avenue

Scheduled for presentation during the Poster Session "Validation, simulation, and virtual testing II" (ThAT15), Thursday, September 26, 2024, 10:30−12:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 14, 2024

Abstract

This research presents a comprehensive digital twin model of the urban corridor network in downtown Chattanooga, United States, developed using the Simulation of Urban MObility (SUMO) microscopic traffic simulation platform. The model is subsequently employed to evaluate the effectiveness of proposed street design modifications, utilizing real-world demand data as input. A well-defined and calibrated simulation model enables in-depth analysis of the transportation network and the movement patterns of vehicles within it. We then compared two scenarios, before and after the implementation of road diet, and provided comprehensive network measurements to quantify the variations for decision-makers. It was highlighted that the average queueing length increased by approximately 50%, while the average queueing time increased by only 12%, suggesting that the road diet results in smoother traffic flow. The study presents a methodology for incorporating a microscopic model into a decision support system to assess and efficiently apply complete streets and tactical urbanism techniques.