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Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Team: Sean Qian (PI, CMU), Qiling Zou (CMU), Pengji Zhang (CMU)

Funding source: US Department of Energy

Start/End time: 2020-2023


This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level simulation framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency.  We consider a regional mobility system with a focus on solo-driving, ride sharing and parking in this project. Parking availability, accessibility and prices are central to travel behavior. The search for parking can result in substantial use of energy and travel time from unnecessary cruising. Additionally, emerging ride-sharing brings in revolutionary changes in the way how, when and where trips are made. Shared mobility is likely to drastically impact solo-driving, parking, and ultimately the resultant energy use patterns. To have a better understanding of the linkage among driving, ride sharing and parking in high spatial and temporal resolutions, we propose to establish a novel modeling framework to encapsulate both passenger and vehicular flow in a roadway-parking transportation network. The analytical model takes input of data collected from various sources (such as roadway traffic, parking, and vehicle inspections), and models demand trips and behavior in the mobility system. Three types of system-level management strategies will be examined, each corresponding to one source of energy efficiency: vehicle electrification, demand management through incentives and information provision for both ride-sharing and parking, as well as roadway/parking expansion/closures. The system performance is measured in terms of travel time, vehicle-miles traveled, energy use, emissions, accessibility, and mobility-energy productivity (MEP).  MEP is an emerging energy and user cost weighted accessibility metric and provides a mobility benefit per unit of energy performance lens from which to assess impacts on transportation energy use. Finally, a management strategy optimization framework will be developed to improve the system efficiency and MEP in both Philadelphia and Pittsburgh regions.

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