Is that Route Really the Most Fuel-Efficient?
Many travelers use Google Maps to select the route for their trip and the Google recommendation can have a significant impact on traffic congestion. Google recently added a new route option: the most fuel-efficient route. In theory, the algorithm behind this route selection examines the current travel conditions on the available routes and estimates typical fuel use based on those conditions. This includes acceleration/deceleration events. These change in speed events significantly impact fuel use and is a critical aspect of selecting the most fuel-efficient route, especially when comparing freeway general purpose lanes (GPLs) to Express Lanes (ELs). Initial testing of the Google Maps algorithm indicates it may not account for these changes. This research will examine if the new route guidance from Google Maps is accurately identifying the most fuel-efficient routes with a focus on busy freeways with ELs. To begin, researchers will examine typical travel conditions on GPLs and ELs on two Dallas freeways with ELs. Next, several vehicles will be equipped with on-board diagnostic (OBD) data loggers that record key aspects of the vehicle operations while they are driving in real-world traffic conditions. These vehicles will be driven on the Dallas freeways (both GPLs and ELs) during various traffic conditions, which will allow for detailed fuel use to be estimated based on the OBD data collected. Finally, the most fuel-efficient route will be calculated based on the OBD data and this will be compared to the Google Maps recommendations.
Language
- English
Project
- Status: Active
- Funding: $46620
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Contract Numbers:
69A3551947136
79075-00-B
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620 -
Project Managers:
Zhang, Yu
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Performing Organizations:
Texas A&M Transportation Institute (TTI)
400 Harvey Mitchell Parkway South
Suite 300
College Station, TX United States 77845-4375 -
Principal Investigators:
Burris, Mark
- Start Date: 20220401
- Expected Completion Date: 20221004
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Automatic data collection systems; Express lanes; Fuel conservation; Routes and routing
- Identifier Terms: Google Maps
- Geographic Terms: Dallas (Texas)
- Subject Areas: Data and Information Technology; Energy; Highways;
Filing Info
- Accession Number: 01853965
- Record Type: Research project
- Source Agency: National Institute for Congestion Reduction
- Contract Numbers: 69A3551947136, 79075-00-B
- Files: UTC, RIP
- Created Date: Aug 7 2022 4:19PM