Smartphone-based Solution to Monitor and Reduce Fuel Consumption and CO2 Footprint

Project Title

Smartphone-based Solution to Monitor and Reduce Fuel Consumption and CO2 Footprint

University

Old Dominion

Principal Investigator

Mecit Cetin, Ph.D.
Assistant Professor, Old Dominion University

Hesham Rakha, Ph.D.
Director of the Center for Sustainable Mobility at the Virginia Tech Transportation Institute, Virginia Tech

Fengxiang Qiao
TSU Representative to TranLIVE, Texas Southern University

PI Contact Information

Mecit Cetin, Ph.D.

Hesham Rakha, Ph.D.

Fengxiang Qiao

Funding Sources and Amounts Provided

US Department of Transportation/TranLIVE — $250,000
Old Dominion University — $150,000
Virginia Tech — $50,000
Texas Southern University $50,000

Total Project Cost

$500,000

Agency ID or Contract Number

DTRT12-G-UTC17; KLK900-SB-001

Start Date

1/1/14

End Date

1/31/16

Description of Research Project

The overall goals of this project are to develop smartphone-based solutions to monitor and reduce FC and C0₂ footprints and to provide feedback to a driver for a given multi-modal trip. The specific goals of the proposed research are:

• Develop new algorithms to estimate the mode of travel and operating mode of a vehicle (e.g., idling, accelerating) based on low-energy sensors (e .g., gyroscope, compass, and accelerometer) available within all smartphones. Even though researchers used cell phones for trajectory estimation before, these relied on GPS which has the disadvantages of low accuracy in urban canyons and depleting the phone battery quickly.
• Estimate carbon footprint for a multi-modal trip and develop a smartphone application. An application will be developed to automatically detect the traveler's mode of transportation (walking, biking, train, car, bus, etc.) and compute the C0₂ emissions. The user will receive feedback for each trip completed so that he/she can make more informed choices about mode, route, and departure time options.
• Evaluate the effectiveness of fuel-consumption and C0₂ estimation from probe vehicles at various participation or market penetration levels. This will be done in a microsimulation environment.
• Develop shortest path algorithms for finding eco-friendly routes in near real-time in large-scale transportation networks.

Implementation of Research Outcomes

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Impacts and Benefits of the Project

Papers

• Ustun, A. Alasaadi, T. Nadeem, M. Cetin, “Detecting Vehicle Stops from Smartphone Accelerometer Data”, The 21st ITS World Congress, Detroit, MI, Sept 7-11, 2014.
• Jahangiri A. and Rakha H. (2015), "Distributed Learning: An Application to Transportation Mode Identification," Presented at the 94th Transportation Research Board Annual Meeting, Washington DC, January 11-15, CD-ROM [Paper # 15-0826].
• “Collecting Vehicle Trajectory Information by Smartphones when GPS Signal is Lost” M. Cetin, T. Nadeem, I. Ustun, A. Alasaadi, M. Orensky, VASITE Annual Meeting, Virginia Beach, VA, June 25 - 27, 2014.
• I. Makohon, Z. Li, M. Sosonkina, Y. Shen, M. Cetin, M. Ng, D.T. Nguyen, “JAVA Based Visualization and Animation for Teaching Dijkstra Shortest Path Algorithm in Transportation Networks”, to be presented at the MODSIM ‘2015 conference, Virginia Beach Convention & Visitor Bureau, VA Beach, VA, March 31-April 2, 2015.
• Z. Li, I. Makohon, M. Sosonkina, Y. Shen, D.T. Nguyen, “Visualization and Animation for Teaching Frank-Wolfe Transportation Network Equilibrium”, to be presented at the MODSIM ‘2015 conference, Virginia Beach Convention & Visitor Bureau, VA Beach, VA, March 31-April 2, 2015.
• M. Cetin and T. Nadeem "Mining Motion Sensor Data from Smartphones for Estimating Vehicle Motion" NSF Drive Sense 2014 Workshop,Norfolk, VA, Oct 30-31, 2014. http://swimsys.cs.odu.edu/DriveSense14/Site/Agenda.html.
• Jahangiri and H. Rakha “Transportation Mode Recognition using Smartphone Sensor Data” NSF Drive Sense 2014 Workshop,Norfolk, VA, Oct 30-31, 2014. http://swimsys.cs.odu.edu/DriveSense14/Site/Agenda.html.
• D.T. Nguyen, M. Ng “Domain Decomposition, Parallel Computing and Traffic Assignment”, invited presentation (P15-6590; 9:00am-9:20am; January 11-2015) at the TRB’2015 Annual Meeting (Workshop on Parallel Computing in Traffic Simulation and Assignment: Moving from Innovations to Practice), Washington, D.C. , January 11- 15, 2015.
• A. Salem, T. Nadeem, M. Cetin, S. EL-Tawab, “DriveBlue: Traffic Incident Prediction through Single Site Bluetooth”, To be presented at the 18th International IEEE Conference on Intelligent Transportation Systems, Spain, 15 – 18 September 2015.
• Jahangiri A. and Rakha H. (2015) Applying Machine Learning Techniques to Transportation Mode Recognition Using Mobile Phone Sensor Data, IEEE ITS Transactions, 2015.
• Ruksana Rahman, Fengxiang Qiao, Qing Li, and Lei Yu. (2015). Identifying suitable warning message from smartphone app to enhance safety in work zone. Presenter: Fengxiang Qiao. Accepted for presentation in the 2015 Intelligent Transportation System World Conference, October 3 - 11, 2015, Bordeaux, France.

Presentations

• Jahangiri A. and Rakha H. (2015), "Distributed Learning: An Application to Transportation Mode Identification," Presented at the 94th Transportation Research Board Annual Meeting, Washington DC, January 11-15, CD-ROM [Paper # 15-0826].
• Dijkstra Shortest Path Algorithm in Transportation Networks”, to be presented at the MODSIM ‘2015 conference, Virginia Beach Convention & Visitor Bureau, VA Beach, VA, March 31-April 2, 2015.
• Z. Li, I. Makohon, M. Sosonkina, Y. Shen, D.T. Nguyen, “Visualization and Animation for Teaching Frank-Wolfe Transportation Network Equilibrium”, to be presented at the MODSIM ‘2015 conference, Virginia Beach Convention & Visitor Bureau, VA Beach, VA, March 31-April 2, 2015.
• D.T. Nguyen, M. Ng “Domain Decomposition, Parallel Computing and Traffic Assignment”, invited presentation (P15-6590; 9:00am-9:20am; January 11-2015) at the TRB’2015 Annual Meeting (Workshop on Parallel Computing in Traffic Simulation and Assignment: Moving from Innovations to Practice), Washington, D.C. , January 11- 15, 2015.
• A. Salem, T. Nadeem, M. Cetin, S. EL-Tawab, “DriveBlue: Traffic Incident Prediction through Single Site Bluetooth”, To be presented at the 18th International IEEE Conference on Intelligent Transportation Systems, Spain, 15 – 18 September 2015.
• Ruksana Rahman, Fengxiang Qiao, Qing Li, and Lei Yu. (2015). Identifying suitable warning message from smartphone app to enhance safety in work zone. Presenter: Fengxiang Qiao. Accepted for presentation in the 2015 Intelligent Transportation System World Conference, October 3 - 11, 2015, Bordeaux, France.

Web Links

Final Report: ODUVTUTC Final ReportSmartphones

Keywords

• Smartphones
• fuel consumption
• C02 emissions

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