CO2NNIE: Personalized Fuel Consumption and CO2 Emissions

Benjamin Bjerre Krogh; Ove Andersen; Edwin Lewis-Kelham; Kristian Torp

doi:10.1145/2820783.2820790

CO2NNIE: Personalized Fuel Consumption and CO2 Emissions

Benjamin Bjerre Krogh, Ove Andersen, Edwin Lewis-Kelham, Kristian Torp

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

We propose a system for calculating the personalized annual fuel consumption and CO2 emissions from transportation. The system, named CO2NNIE, estimates the fuel consumption on the fastest route between the frequent destinations of the user. The travel time and fuel consumption estimated are based on 3.8 billion GPS records from 16 thousand cars and 198 million records from 218 cars annotated with fuel consumption data, respectively. The fuel consumption estimates from the system are validated using fuel-pump data. We find that estimates have good accuracy, i.e., are generally within 10% of the actual fuel consumption (4.6% deviation on average). We conclude, that the system provides new detailed information on CO2 emissions and fuel consumption for any make and model.

Original language	English
Title of host publication	23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Publisher	Association for Computing Machinery
Publication date	2015
Article number	92
ISBN (Print)	978-1-4503-3967-4
DOIs	https://doi.org/10.1145/2820783.2820790
Publication status	Published - 2015
Event	SIGSPATIAL '15: International Conference on Advances in Geographic Information Systems - Bellevue, WA, United States Duration: 3 Nov 2015 → 6 Nov 2015

Conference

Conference	SIGSPATIAL '15
Country/Territory	United States
City	Bellevue, WA
Period	03/11/2015 → 06/11/2015

Keywords

Fuel-consumption
Transportation,
GPS
CANBus
CO2

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10.1145/2820783.2820790

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Cite this

@inproceedings{d14d7f98f1544539ad85556d38123aab,

title = "CO2NNIE: Personalized Fuel Consumption and CO2 Emissions",

abstract = "We propose a system for calculating the personalized annual fuel consumption and CO2 emissions from transportation. The system, named CO2NNIE, estimates the fuel consumption on the fastest route between the frequent destinations of the user. The travel time and fuel consumption estimated are based on 3.8 billion GPS records from 16 thousand cars and 198 million records from 218 cars annotated with fuel consumption data, respectively. The fuel consumption estimates from the system are validated using fuel-pump data. We find that estimates have good accuracy, i.e., are generally within 10% of the actual fuel consumption (4.6% deviation on average). We conclude, that the system provides new detailed information on CO2 emissions and fuel consumption for any make and model.",

keywords = "Fuel-consumption, Transportation,, GPS, CANBus, CO2",

author = "Krogh, {Benjamin Bjerre} and Ove Andersen and Edwin Lewis-Kelham and Kristian Torp",

year = "2015",

doi = "10.1145/2820783.2820790",

language = "English",

isbn = "978-1-4503-3967-4",

booktitle = "23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems",

publisher = "Association for Computing Machinery",

address = "United States",

note = "SIGSPATIAL '15 : International Conference on Advances in Geographic Information Systems ; Conference date: 03-11-2015 Through 06-11-2015",

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CO2NNIE: Personalized Fuel Consumption and CO2 Emissions. / Krogh, Benjamin Bjerre; Andersen, Ove; Lewis-Kelham, Edwin et al.
23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Association for Computing Machinery, 2015. 92.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - CO2NNIE

T2 - SIGSPATIAL '15

AU - Krogh, Benjamin Bjerre

AU - Andersen, Ove

AU - Lewis-Kelham, Edwin

AU - Torp, Kristian

PY - 2015

Y1 - 2015

N2 - We propose a system for calculating the personalized annual fuel consumption and CO2 emissions from transportation. The system, named CO2NNIE, estimates the fuel consumption on the fastest route between the frequent destinations of the user. The travel time and fuel consumption estimated are based on 3.8 billion GPS records from 16 thousand cars and 198 million records from 218 cars annotated with fuel consumption data, respectively. The fuel consumption estimates from the system are validated using fuel-pump data. We find that estimates have good accuracy, i.e., are generally within 10% of the actual fuel consumption (4.6% deviation on average). We conclude, that the system provides new detailed information on CO2 emissions and fuel consumption for any make and model.

AB - We propose a system for calculating the personalized annual fuel consumption and CO2 emissions from transportation. The system, named CO2NNIE, estimates the fuel consumption on the fastest route between the frequent destinations of the user. The travel time and fuel consumption estimated are based on 3.8 billion GPS records from 16 thousand cars and 198 million records from 218 cars annotated with fuel consumption data, respectively. The fuel consumption estimates from the system are validated using fuel-pump data. We find that estimates have good accuracy, i.e., are generally within 10% of the actual fuel consumption (4.6% deviation on average). We conclude, that the system provides new detailed information on CO2 emissions and fuel consumption for any make and model.

KW - Fuel-consumption

KW - Transportation,

KW - GPS

KW - CANBus

KW - CO2

U2 - 10.1145/2820783.2820790

DO - 10.1145/2820783.2820790

M3 - Article in proceeding

SN - 978-1-4503-3967-4

BT - 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

PB - Association for Computing Machinery

Y2 - 3 November 2015 through 6 November 2015

ER -

CO2NNIE: Personalized Fuel Consumption and CO2 Emissions

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