Research theme · 03
Multi-Modal Transportation Systems
Integrating roadway, transit, parking, bicycle, energy, and emissions data so that decisions in one mode account for impacts on the others.
Overview
The center collects and integrates multi-modal datasets across the Pittsburgh region — roadway traffic, probe vehicles, public transit, parking, incidents, bicycles, buildings, energy consumption, emissions, social media, and more.
Decision-making in one mode of the transportation system must take into account its impact on the other modes, and vice versa. Our work enables integrated analysis rather than siloed departmental operations.
Featured Projects
- Mobility Data Analytics Center: the Engine for Building a Regional Traveler Information System for Pittsburgh — Team: Xidong Pi, Zhangning Hu.
- Transit Service Performance Analysis and Bunching Detection Using APC and AVL Data — Team: Xidong Pi.
- Optimal first- and last-mile mobility services — Team: Rick Grahn.
- CPS: Small: Collaborative Research: Optimal Ride Service For All: Users, Service Providers and Society — Team: Zemian Ke, Matt Battifarano.
- Measuring time-dependent accessibility with emerging mobility options: a generic multi-modal network modeling framework — Team: Katherine Flanigan, Lindsay Graff.
Projects
MAC: The Engine for Building a Regional Traveler Information System for PittsburghA centralized data engine and web platform for managing, fusing, and analyzing large-scale mobility information across roadway, incident, parking, transit, weather, EV, and mobile data sources.
Sean Qian · Benedum Foundation
- Optimal First- and Last-Mile Mobility Services
Modeling and optimizing an existing first-mile / last-mile transit operation in Robinson Township, PA — including ride coordination, predictive routing, and trip prioritization.
Sean Qian · U.S. Department of Transportation, National Science Foundation
- CPS: Small: Collaborative Research: Optimal Ride Service For All — Users, Service Providers and Society
A framework for guiding emerging mobility services toward system-wide objectives via rider surcharges/credits and provider subsidies tied to performance guarantees.
Sean Qian · National Science Foundation
- Measuring Time-Dependent Accessibility with Emerging Mobility Options: A Generic Multi-Modal Network Modeling Framework
A multi-modal accessibility framework that incorporates travel time, cost, reliability, safety, and comfort across personal vehicles, ride-hailing, transit, bikes, scooters, and walking.
Sean Qian · U.S. Department of Transportation
Transit Service Performance Analysis and Bunching Detection Using APC and AVL DataUsing automatic passenger counters (APC) and automatic vehicle location (AVL) data to analyze transit service performance and detect bus bunching.
Sean Qian · Pennsylvania Infrastructure Technology Alliance