routing

In this project, the authors developed a centrally coordinated shuttle scheduling and routing management system for mixed fleets of diesel and electric shuttles using a digital twin of LAX to LA downtown traffic road network by optimizing the total combined cost of energy consumption and travel time.

This research assessed the changes in Metropolitan Atlanta Rapid Transit Authority (MARTA) service configurations by reviewing the pre-pandemic vs. during-pandemic General Transit Feed Specification (GTFS) files.

Researchers at the University of Southern California developed a real-time, distributed algorithm for offering personalized incentives to individual drivers to make socially optimal routing decisions.

The results dataset used to populate the analyses presented in the report, "Combined Effect of Changes in Transit Service and Changes in Occupancy on Per-Passenger Energy Consumption". 

This data is from the project, Dynamic Routing for Ridesharing. The data is randomly generated within grids where each unit of the grid represents a 1-mile by 1-mile square. It is used to generate the origins and destinations of passengers.

Research performed in this supplemental NCST study improved model algorithms to increase analytical efficiency and to integrate ridership demographics, so that energy use impacts could be assessed across demographic groups for use in social sustainability analysis.

The research report explored the use of High Occupancy Vehicle (HOV) lanes and meeting points in a ride-sharing system where drivers have their own origin and destination.

Researchers examined the possibility of ride-sharing being able to mitigate traffic congestion by developing a two-stage algorithm to solve the routing problem with ride-share in real-time within a context where ride-sharing drivers are traveling toward their own destinations while making detours to serve passengers with flexible pickup and drop-off locations.