<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T22:01:06Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/113106" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/113106</identifier><datestamp>2026-06-06T00:48:55Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Moshe E. Ben-Akiva.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Srinivasan, Arjun, M. Eng. Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-01-12T20:56:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-01-12T20:56:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/113106</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1016447803</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 51-53).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Transportation is a major source of energy consumption in developed countries [4]. Unfortunately, people have little incentive to change their habits, relying on inefficient transportation sources. The "Sustainable Travel Incentives with Prediction, Optimization and Personalization" (Tripod) project seeks to incentivize people to improve their transportation-related behavior through redeemable tokens. These tokens are rewarded through city-wide, energy-optimized transportation decisions decided in real-time. As part of this initiative, I have developed an initial prototype Android application named FMS Advisor that allows users to interact with the larger Tripod system before, during, and after their journey. Working off an initial design, I designed a trip planner interface that uses optimized route planning information to display a personalized trip menu. I also developed trip validation algorithms such as vehicle occupancy detection and driving-style detection using dynamic time warping (DTW) and threshold-based methods. These methods were then evaluated through group user sessions and controlled trip experiments. This resulted in a functional end-to-end user experience, though trip validation methods require additional data to have properly tuned detection. In the future, token redemption will be possible through an integrated marketplace for rewards that can be accessed at the end of a trip.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Arjun Srinivasan.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">53 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Leveraging smartphones to incentivize city-wide, energy ecient transportation</dim:field>
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   	&lt;Title>Leveraging smartphones to incentivize city-wide, energy ecient transportation&lt;/Title>
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   	&lt;PublicationDate>2017&lt;/PublicationDate>
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        	&lt;DisplayName>Srinivasan, Arjun, M. Eng. Massachusetts Institute of Technology&lt;/DisplayName>
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   	&lt;Abstract>Transportation is a major source of energy consumption in developed countries [4]. Unfortunately, people have little incentive to change their habits, relying on inefficient transportation sources. The &amp;quot;Sustainable Travel Incentives with Prediction, Optimization and Personalization&amp;quot; (Tripod) project seeks to incentivize people to improve their transportation-related behavior through redeemable tokens. These tokens are rewarded through city-wide, energy-optimized transportation decisions decided in real-time. As part of this initiative, I have developed an initial prototype Android application named FMS Advisor that allows users to interact with the larger Tripod system before, during, and after their journey. Working off an initial design, I designed a trip planner interface that uses optimized route planning information to display a personalized trip menu. I also developed trip validation algorithms such as vehicle occupancy detection and driving-style detection using dynamic time warping (DTW) and threshold-based methods. These methods were then evaluated through group user sessions and controlled trip experiments. This resulted in a functional end-to-end user experience, though trip validation methods require additional data to have properly tuned detection. In the future, token redemption will be possible through an integrated marketplace for rewards that can be accessed at the end of a trip.&lt;/Abstract>
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