Real-time marginal cost estimation for eco-routing navigation guidance
Transportation caused 27% of US greenhouse gas emissions in 2022 (EPA), so reducing emissions from transportation is important to resolving the climate crisis. Towards this goal, Google Maps recently introduced a new default navigation mode: they suggest routes to drivers to minimize their own CO2 emissions instead of minimizing their travel time. Since Google Maps is widely used, this switch could result in correspondingly large changes in how drivers choose routes. However, the goal is to reduce total systems emissions (system-optimal (SO) eco-routing), but Google Maps routes drivers to minimize their individual emissions, which is user-optimal (UO) eco-routing. With a large proportion of drivers trying to minimize their individual emissions, that significantly changes congestion patterns, and traffic congestion increases emissions per mile compared to less-congested traffic. In fact, the researcher's preliminary work in IEEE Transactions on Intelligent Transportation Systems demonstrates that UO eco-routing could have higher emissions than UO travel time routing. In other words, Google Maps’ well-intentioned change to routing behavior could in fact be causing transportation emissions to become worse! The purpose of this project is to develop a real-time navigation guidance that gets closer to SO eco-routing, i.e. an improved algorithm that Google Maps or similar systems could use instead. The main challenge is predicting how the route choices of drivers affect congestion for other drivers. Since the purpose is for actual use, realistic models of traffic flow behavior need to be used, which also make computation more difficult, and the system must operate in real-time to be useful. Therefore, the researcher's theoretical approach to this problem is based on marginal-cost routing, which is guaranteed to find SO eco-routes if marginal costs are estimated correctly. Due to the difficulty of calculating marginal costs, the researcher proposes a heuristic to estimate them, and simulations to validate the effectiveness of the heuristic.
Language
- English
Project
- Status: Active
- Funding: $75000
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Contract Numbers:
CTS #2025005
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Sponsor Organizations:
Center for Transportation Studies, University of Minnesota
University Office Plaza, Suite 440
2221 University Avenue SE
Minneapolis, MN United States 55414 -
Performing Organizations:
University of Minnesota Department of Civil, Environmental and Geo-Engineering
500 Pillsbury Drive SE
Minneapolis, MN United States 55455 -
Principal Investigators:
Levin, Michael
- Start Date: 20240101
- Expected Completion Date: 20250630
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Aids to navigation; Algorithms; Cost estimating; Pollutants; Route choice; Routes and routing; Traffic congestion
- Subject Areas: Data and Information Technology; Environment; Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01910287
- Record Type: Research project
- Source Agency: University of Minnesota, Minneapolis
- Contract Numbers: CTS #2025005
- Files: RIP
- Created Date: Feb 28 2024 11:42AM