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Project 5: Ramp Metering Control in Freeway System

Project 5: Ramp Metering Control in Freeway System. Team Members: Faculty Mentor: Isaac Quaye Dr. Heng Wei Junior GRA: Emma Hand Karteek K. Allam Sophomore Jared Sagaga Junior. 2. Sponsor. 3. What are Ramp Meters?.

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Project 5: Ramp Metering Control in Freeway System

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  1. Project 5: Ramp Metering Control in Freeway System Team Members: Faculty Mentor: Isaac Quaye Dr. Heng Wei JuniorGRA: Emma Hand Karteek K. Allam Sophomore Jared Sagaga Junior

  2. 2 Sponsor

  3. 3 What are Ramp Meters? • Traffic controls that regulate traffic flow entering a highway (Source: Reference 6)

  4. 4 Uses of Ramp Meters • Reduce congestion • Improve throughput • Reduce travel time • Improved travel time reliability • Ensuring safety of vehicles (Source: Reference 6)

  5. 5 Types of Ramp Metering • Fixed time • Pre-timed meter cycle based off of past data • Responsive • Meter cycles vary depending on changes in traffic conditions • Isolated • Coordinated

  6. 6 Meters Across the US Seattle: 232 Minn-St. Paul: 444 Portland: 110 Milwaukee: 122 Ohio: 34 New York: 75 Chicago: 117 Salt Lake City: 23 Denver: 46 N. Virginia: 26 LA: 1478 Phoenix: 122 Arlington: 5 Implemented - Responsive In Progress - Responsive In Progress - Fixed

  7. 7 Networking • Received information from Mn/DOT, WSDOT, ODOT • Mn/DOT uses traffic responsive • WSDOT uses traffic responsive with fuzzy logic algorithm • ODOT uses fixed timings

  8. 8 Scope of Study • Conducting research on the study site (I-275) by gathering data using traffic counter and GPS device • Criteria • Elevated locations nearby for placing the camcorder to capture the traffic • Location should be busier in the peak hours than the normal flow of freeway • Analyzing traffic during the peak hours • Investigating and observing both a single and two lane ramp implementation

  9. 9 Goals • Analysis of data collected • Investigate • Effectiveness of ramp implementation • One or two lane ramp metering • Successfully run simulations on VISSIM • Present and complete deliverables

  10. 10 Tasks • Utilizing the GPS software (QTravel) and traffic counting software (PetraPro) • Processing of data collected from GPS and traffic counting device • Generate VISSIM network model using processed data • Analyze results

  11. Methodology 11 Study Site One Lane Ramp VISSIM Results Data Collection Two Lane Ramp

  12. 12 Data Collection Study Site I-275 Reed Hartman Highway Legend Mosteller Road East-Bound Sections West-Bound Sections

  13. 13 Data Collection (cont.)

  14. 14 Data Collection (cont.)

  15. 15 Data Collection (cont.) (Source: Reference 7) (Source: Reference 8)

  16. 16 Data Collection (cont.) QTravel

  17. 17 Data Collection (cont.) Sample of data collected from GPS device for I-275

  18. 18 Data Collection (cont.)

  19. 19 Training • Using GPS device and software • Collecting data with GPS device and extracting it for analysis using the software (QTravel) • Using Traffic Counting device • To count traffic flow from camera recordings • Count and record the types of vehicles

  20. 20 Training (cont.) GPS Traffic Counter

  21. 21 Progress • Post-Processing data collected • Analyzing the data collected with the GPS and traffic counting device • Intro to VISSIM • Overview on the function of VISSIM • Preliminary training on VISSIM’s interface

  22. 22 Timeline Legend Complete Incomplete

  23. 23 References • Zongzhong, T., Nadeem, A. C., Messer, C. J., Chu, C. (2004). “Ramp Metering Algorithms and Approaches for Texas,” Transportation Technical Report No. FHWA/TX-05/0-4629-1, Texas Transportation Institute, The Texas A&M University System, College Station, Texas. • Yu, G., Recker, W., Chu, L. (2009). “Integrated Ramp Metering Design and Evaluation Platform with Paramics,” California PATH Research Report No. UCB-ITS-PRR-2009-10, Institution of Transportation Studies, University of California, Berkley, California. • Kang, S., Gillen, D. (1999). “Assessing the Benefits and Costs of Intelligent Transportation Systems: Ramp Meters,” California PATH Research Report No. UCB-ITS-PRR-99-19, Institution of Transportation Studies, University of California, Berkley, California. • Arizona Department of Transportation. (2003). Ramp Meter Design, Operations, and Maintenance Guidelines. • Papamichail I., and Papageorgiou, M. (2008). “Traffic-Responsive Linked Ramp-Metering Control,” IEEE Transactions on Intelligent Transportation Systems, Vol. 9, No. 1, n.p.

  24. 24 References (cont.) • Federal Highway Administration, USDOT (2013). “FHWA Localized Bottleneck Program.” <http://ops.fhwa.dot.gov/bn/resources/case_studies/madison_wi.htm> (Accessed 6/9/2014) • Maps, Google (2014). <https://www.google.com/maps/search/homewood+suites+near+Hilton+Cincinnati,+OH/@39.2885017,-84.399993,83m/data=!3m1!1e3?hl=en> (Accessed 6/30/2014). • Maps, Google (2012). <https://www.google.com/maps/@39.288408,-84.399636,3a,75y,243.6h,66.31t/data=!3m4!1e1!3m2!1si7sOFQJVai_eF3v7k8u_LQ!2e0> (Accessed 6/30/2014).

  25. 25 Questions?

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