1. 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 1

2. Sponsor 2

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

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

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 5

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

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 7

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 8

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 9

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 10

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

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

13. Data Collection (cont.) 13

14. Data Collection (cont.) 14

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

16. Data Collection (cont.) 16 QTravel

17. Data Collection (cont.) 17 Sample of data collected from GPS device for I-275 East-Bound Time of DaySection 1 Average Time (mm:ss)Section 2 Average Time (mm:ss) Morning00:4802:42 Afternoon00:5202:19 Evening00:4602:24 West-Bound Time of DaySection 1 Average Time (mm:ss)Section 2 Average Time (mm:ss) Morning02:0201:30 Afternoon02:011:32 Evening1:4901:29

18. Data Collection (cont.) 18

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 19

20. Training (cont.) 20 GPS Traffic Counter

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 21

22. Timeline Task Week 1-234567-8 Methods of evaluation and research Equipment and software training Data collection and analysis Use data to develop deliverables Create and run simulation models Complete deliverables Completed 22LegendComplete Incomplete

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. 23

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

25. Questions? 25