Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published online January 1, 2014

Ecolane Applications: Preliminary Testing and Evaluation

Abstract

This study investigated the feasibility of ecolane applications along a section of Interstate 66 in Northern Virginia. In ecolanes, drivers are required to operate the vehicle at recommended or variable speed limits to reduce transportation energy consumption and improve vehicle mobility. The study focused its efforts on evaluation of various eco-lane algorithms and speed harmonization (SPD-HARM) applications through the use of INTEGRATION microscopic traffic simulation software. The study demonstrated that the proposed ecolanes system could significantly improve fuel efficiency and air quality while reducing average vehicle travel time and total delay. For this case study, the eco-lane system reduced delay, fuel consumption, and emissions of hydrocarbon (HC), carbon monoxide (CO), and carbon dioxide (CO2) by 23%, 4.5%, 3.1%, 3.4%, and 4.6%, respectively, compared with those in the base case scenario. The study also examined the feasibility of a predictive ecolane system and demonstrated that such a system could improve the performance of the original ecolane system. Furthermore, this study demonstrated that optimum throttle levels and optimum eco-speed limits (speed limits that were optimized for mobility, fuel consumption, and emissions levels) could significantly improve the performance of the ecolane system. Finally, the study demonstrated that SPD-HARM across all vehicles and lanes reduced the system delay, fuel consumption, and emissions of HC, CO, oxides of nitrogen, and CO2 by 7.6%, 6.3%, 23.9%, 26.1%, 17.2%, and 4.4%, respectively, compared with those in the base case scenario.

Get full access to this article

View all access and purchase options for this article.

References

1. U.S. Department of Transportation. AERIS Transformative Concepts. http://www.its.dot.gov/aeris/pdf/Draft_Transformative_Concepts.pdf. Accessed July 20, 2013.
2. U.S. Department of Transportation. Applications for the Environment: Real-Time Information Synthesis (AERIS). http://www.its.dot.gov/aeris/. Accessed July 30, 2013.
3. Fontes T., Fernandes P., Rodrigues H., Bandeira J., Pereira S. R., Khattak A. J., and Coelho M. C. Are Ecolanes a Sustainable Option to Reduce Emissions in a Medium-Sized European City? Presented at 92nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2013.
5. U.S. Department of Transportation. Dynamic Ecolanes Transformative Concept. http://www.its.dot.gov/aeris/pdf/AERIS%202013%20Workshop%20–%20Dynamic%20ecolanes%20ConOps%20Handout-03-14-2013.pdf. Accessed July 20, 2013.
6. Ploeg J., Scheepers B. T. M., van Nunen E., van de Wouw N., and Nijmeijer H. Design and Experimental Evaluation of Cooperative Adaptive Cruise Control. Proc., 14th International IEEE Conference on Intelligent Transportation Systems, Washington, D.C., IEEE, New York, 2011.
7. Shladover S. E. Literature Review on Recent International Activity in Cooperative Vehicle-Highway Automation Systems. Publication FHWA-HRT-13-025. FHWA, U.S. Department of Transportation, 2012.
8. Recent International Activity in Cooperative Vehicle-Highway Automation Systems. Publication FHWA-HRT-12-033. FHWA, U.S. Department of Transportation, 2012.
9. Shladover S. E., Nowakowski C., Cody D., Bu F., O'Connell J., Spring J., Dickey S., and Nelson D. Effects of Cooperative Adaptive Cruise Control on Traffic Flow: Testing Drivers’ Choices of Following Distances. Publication UCB-ITS-PRR-2009-23. California Partners for Advanced Transit and Highways Program, Institute of Transportation Studies, University of California, Berkeley, 2009.
10. Nowakowski C., O'Connell J., Shladover S. E., and Cody D. Cooperative Adaptive Cruise Control: Driver Acceptance of Following Gap Settings Less than One Second. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 54, No. 24, 2010, pp. 2033–2037.
11. Nowakowski C., Shladover S. E., Cody D., Bu F., O'Connell J., Spring J., Dickey S., and Nelson D. Cooperative Adaptive Cruise Control: Testing Drivers’ Choices of Following Distances. Publication UCB-ITS-PRR-2011-01. California Partners for Advanced Transit and Highways, Institute of Transportation Studies, University of California, Berkeley, 2011.
12. Park B. B., Malakorn K., and Lee J. Quantifying Benefits of Cooperative Adaptive Cruise Control Toward Sustainable Transportation System. Virginia Department of Transportation and Research and Innovative Technology Administration, U.S. Department of Transportation, 2011.
13. Metz N., Schlichter H., and Schellenberg H. Positive Effects of a Traffic Control System on Fuel Consumption and Exhaust Emission on the German A9 Autobahn. International Journal of Vehicle Design, Vol. 18, No. 3-4, 1997, pp. 354–367.
14. Lee C., Hellinga B., and Saccomanno F. Evaluation of Variable Speed Limits to Improve Traffic Safety. Transportation Research Part C: Emerging Technologies, Vol. 14, No. 3, 2006, pp. 213–228.
15. Waller S. T., Ng M., Ferguson E., Nezamuddin N., and Sun D. Speed Harmonization and Peak-Period Shoulder Use to Manage Urban Freeway Congestion. Report FHWA/TX-10/0-5913-1. University of Texas at Austin, 2009.
16. Kwon E., Brannan D., Shouman K., Isackson C., and Arseneau B. Development and Field Evaluation of Variable Advisory Speed Limit System for Work Zones. In Transportation Research Record: Journal of the Transportation Research Board, No. 2015, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 12–18.
17. Bertini R. L., Boice S., and Bogenberger K. Dynamics of Variable Speed Limit System Surrounding Bottleneck on German Autobahn. In Transportation Research Record: Journal of the Transportation Research Board, No. 1978, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 149–159.
18. Chang G.-L., Park S. Y., and Paracha J. Intelligent Transportation System Field Demonstration: Integration of Variable Speed Limit Control and Travel Time Estimation for a Recurrently Congested Highway. In Transportation Research Record: Journal of the Transportation Research Board, No. 2243, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 55–66.
19. Fudala N. J., and Fontaine M. D. Interaction Between System Design and Operations of Variable Speed Limit Systems in Work Zones. In Transportation Research Record: Journal of the Transportation Research Board, No. 2169, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 1–10.
20. Kang K.-P., Chang G.-L., and Zou N. Optimal Dynamic Speed-Limit Control for Highway Work Zone Operations. In Transportation Research Record: Journal of the Transportation Research Board, No. 1877, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 77–84.
21. Lee J., Dailey D. J., Bared J. G., and Park B. Simulation-Based Evaluations of Real-Time Variable Speed Limit for Freeway Recurring Traffic Congestion. Presented at 92nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2013.
22. Ahn K., Rakha H., Trani A., and Van Aerde M. Estimating Vehicle Fuel Consumption and Emissions Based on Instantaneous Speed and Acceleration Levels. Journal of Transportation Engineering, Vol. 128, No. 2, 2002, pp. 182–190.
23. Rakha H., Ahn K., and Trani A. Development of VT-Micro Model for Estimating Hot Stabilized Light Duty Vehicle and Truck Emissions. Transportation Research Part D: Transport and Environment, Vol. 9, No. 1, 2004, pp. 49–74.
24. Van Aerde M. and Associates QUEENSOD Rel. 2.10 User's Guide: Estimating Origin Destination Traffic Demands from Link Flows. M. Van Aerde and Associates, Kingston, Ontario, Canada, 2002.
25. Rakha H., and Gao Y. Calibration of Steady-State Car-Following Models Using Macroscopic Loop Detector Data. Report VT-2008-01. Virginia Polytechnic Institute and State University, Blacksburg, 2010.
26. New DOT Research Shows Drivers Support Connected Vehicle Technology, Appreciate Potential Safety Benefits. NHTSA, U.S. Department of Transportation. http://www.nhtsa.gov/About+NHTSA/Press+Releases/New+DOT+Research+Shows+Drivers+Support+Connected+Vehicle+Technology,+Appreciate+Potential+Safety+Benefits. Accessed Oct. 22, 2013.
27. Ahn K., and Rakha H. The Effects of Route Choice Decisions on Vehicle Energy Consumption and Emissions. Transportation Research Part D: Transport and Environment, Vol. 13, No. 3, 2008, p. 17.
28. Ahn K., Rakha H. A., and Park S. Ecodrive Application: Algorithmic Development and Preliminary Testing. In Transportation Research Record: Journal of the Transportation Research Board, No. 2341, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 1–11.
29. Wang Y. B., Papageorgiou M., and Messmer A. Real-Time Freeway Traffic State Estimation Based on Extended Kalman Filter: Adaptive Capabilities and Real Data Testing. Transportation Research Part A: Policy and Practice, Vol. 42, No. 10, 2008, pp. 1340–1358.
30. Chen H., Rakha H., and Sadek S. Real-Time Freeway Traffic State Prediction: A Particle Filter Approach. Presented at 14th International IEEE Conference on Intelligent Transportation Systems, Washington, D.C., 2011.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: January 1, 2014
Issue published: January 2014

Rights and permissions

© 2014 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

Kyoungho Ahn
Center for Sustainable Mobility, Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061.
Hesham A. Rakha
Charles E. Via, Jr., Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, 3500 Transportation Research Plaza, Blacksburg, VA 24061.

Notes

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 29

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 4

  1. Are work zones and connected automated vehicles ready for a harmonious...
    Go to citation Crossref Google Scholar
  2. COVID-19 pandemic impacts on traffic system delay, fuel consumption an...
    Go to citation Crossref Google Scholar
  3. Safety Assessment of Ecodriving Vehicles on Following Traffic
    Go to citation Crossref Google Scholar
  4. Intelligent Transportation Systems and Greenhouse Gas Reductions
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/ePub

View PDF/ePub