Evaluating the effectiveness of “Smart Pedal” systems for vehicle fleets
Data files
May 21, 2023 version files 159.63 MB
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README.md
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Unit_1200_Baseline.csv
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Unit_1200_SmartPedal.csv
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Unit_3001_Baseline.csv
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Unit_3001_SmartPedal.csv
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Unit_3002_Baseline.csv
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Unit_3002_SmartPedal.csv
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Unit_3003_Baseline.csv
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Unit_3003_SmartPedal.csv
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Unit_3004_Baseline.csv
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Unit_3004_SmartPedal.csv
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Unit_3005_Baseline.csv
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Unit_3005_SmartPedal.csv
Abstract
California has major initiatives for reducing greenhouse gas (GHG) emissions by 40% below 1990 levels by 2030, and 80% reduction below 1990 levels by 2050. In recent years, there have been a number of “Smart Pedal” systems that emerged, both as automotive OEM equipment and as third-party hardware. These “Smart Pedal” systems can be installed in vehicles with the potential to reduce fuel consumption and GHG emissions by smoothing a driver’s acceleration and deceleration patterns, with little effect on travel time or safety. This research investigates the effectiveness of a select “Smart Pedal” system in reducing fuel consumption and GHG emissions. The SmartPedalTM technology was evaluated using six Caltrans vehicles, each monitored for two data collection periods: 1) without the SmartPedalTM device, to collect the baseline data sets, and 2) with the SmartPedalTM device, to collect a comparison data set with the “Smart Pedal” technology. The collected data is presented here.
Methods
Data were collected using Global Positioning Systems (GPS) enabled Engine Control Unit (ECU) data loggers from the HEM corporation. The raw data files were converted to .csv files using HEM software. The HEM software also provides fuel economy based on the Mass Air Flow (MAF) sensor which was available for each test vehicle. Recorded GPS data was used for map matching to determine road grade and road type. This information is provided here, when available, however, GPS data is not provided due to privacy-related restrictions.
Usage notes
The README file provides information on the data file name structure, test vehicle information, and a variable guide for the vehicle data files. The data files are in standard .csv format.