2026-09-18T22:53:05Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/599402022-01-13T07:54:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
Sanjay Sarma.
Khoury, Joe, S.B. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2010-11-08T17:49:19Z
2010-11-08T17:49:19Z
2010
2010
http://hdl.handle.net/1721.1/59940
676913133
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references.
This thesis looks into the ability to collect driving data reliably and cost-effectively, characterize driving behavior, categorize roads, and finally link all together in a way to minimize the fuel consumption in cars. Using an OBDII scanner, a Smartphone, and an accelerometer, we were able to collect data from various types of cars. Then, we used Matlab in order to analyze the data and compare them visually. We found out that using a Smartphone's built-in GPS and accelerometer is sufficient to record all the basic information required to enable us to model driving behavior and characterize roads. This thesis also aims at establishing a basis for future work to determine how driving patterns relate to fuel consumption.
by Joe Khoury.
S.B.
63 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Traffic characterization and road categorization
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>This thesis looks into the ability to collect driving data reliably and cost-effectively, characterize driving behavior, categorize roads, and finally link all together in a way to minimize the fuel consumption in cars. Using an OBDII scanner, a Smartphone, and an accelerometer, we were able to collect data from various types of cars. Then, we used Matlab in order to analyze the data and compare them visually. We found out that using a Smartphone's built-in GPS and accelerometer is sufficient to record all the basic information required to enable us to model driving behavior and characterize roads. This thesis also aims at establishing a basis for future work to determine how driving patterns relate to fuel consumption.</Abstract>
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