routing | National Center for Sustainable Transportation

Integrating Transit Paths and Transit Occupancy Data into Activity-Based Travel Demand Model Outputs to Support Sustainability Analysis across Modes

Principal Investigator Randall Guensler, Ph.D.
Georgia Institute of Technology

The research team will develop Python code to integrate TransitSim shortest transit path predictions for every origin-destination pair and departure time into regional activity-based travel demand model (ABM) outputs.

Project Status

Complete

Learning Drivers’ Utility Functions in a Coordinated Freight Routing System Based on Drivers’ Actions

Principal Investigator Petros Ioannou, Ph.D.
University of Southern California

This project explores the probability of developing a centrally coordinated routing system for trucks. The project develops a method for estimating the utility functions of truck drivers based on their response to a centrally coordinated routing system that they are participating, and it also evaluates the impact of assumed wrong utility functions that could be viewed as non-compliance on the system optimum cost.

Project Status

In Progress

Real-Time Large-Scale Ridesharing with Flexible Meeting Points

Principal Investigator Maged Dessouky, Ph.D.
University of Southern California

This project will develop a framework that will, in real-time, match drivers to passengers and route rideshare drivers that incorporates traffic data to provide improved solutions. The resulting solution framework will use commercial traffic simulation software to achieve this goal.

Project Status

In Progress

The Ridesharing Routing Problem with Flexible Pickup and Drop-off Points

Research Product Type

Research Report

This research project proposes three different solution approaches for solving the ride share routing problem with flexible pickup and drop-off points. Results show that the approaches are efficient, solving instances with up to 300 nodes within 130 CPU seconds. The methodologies in this study can help transportation planners design more efficient rideshare systems with less waiting, better passenger service, and less travel time.

Using Multi-Modal Path-Specific Transit Trips in Transportation Social Sustainability Analysis: Case Study in Atlanta, GA

Principal Investigator Huiying Fan
Georgia Institute of Technology

This study will extend Georgia Tech’s previous efforts in the application of regional travel demand model path retention algorithms, the regional TransitSim shortest transit path simulator, to social sustainability analysis.

Project Status

In Progress

Webinar: Congestion Reduction via Personalized Incentives

This webinar discussed research on developing real-time algorithms to reduce traffic congestion and improve routing efficiency via offering personalized incentives to drivers.