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

Sponsor 2

Outline 3 Introduction Scope of study, goals and tasks Training Data Collection Methodology Results Timeline

National Statistics Average time spent on highway (NHTSA 2009) –Student: 1.3 hours/day –Working: 1.5 hours/day –36 hours/year in traffic 4 Source: NHTSA

National Statistics (cont.) 32,885 people died in motor vehicle traffic crashes in 2010 (NHTSA) –5,419,000 total crashes on highway, 29% caused injury or were fatal 33% crashes occur on freeway stretch with bridges or interchanges (2011) $871 BILLION in economic loss and societal harm 5

RampMeters What can fix this? Source: Reference 10 6

What are Ramp Meters? 7 Traffic controls that regulate traffic flow entering a highway Source: Reference 6

Why Ramp Meters? Reduces congestion Improves throughput (up to 62%) –Decreases time spent staring at brake lights Reduces travel time (20-61%) Improves travel time reliability Ensures the safety of vehicles (5-43% decrease in accidents) 8

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 9

Metering Signal Arterial 10 Signal Controller Ramp Metering System

Meters Across the US Seattle: 232 Oregon: 150 California: 3471 Phoenix: 233 Salt Lake City: 23 Denver: 54 Texas: 115 Minn-St. Paul: 444 Wisconsin: 80 Chicago: 117 New York: 75 N. Virginia: 26 Implemented - Responsive In Progress - Responsive 11 In Progress - Fixed Ohio: 34 Atlanta: 170 Wisconsin: 38 Washington D.C.: 24 Florida: 22 St. Louis: 1

Scope of Study Conducted research on the study site (East-Bound I-275) by gathering data using traffic counter and GPS travel data logger 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 Investigated both a one and two lane ramp implementation in VISSIM 12

Goals Gain background knowledge and training for research project Collect and process data from GPS data logger and traffic counter Investigate –Effectiveness of one and two lane ramp implementation Successfully run simulations in VISSIM Present completed deliverables 13

Tasks Equipment and software training Utilized GPS software (QTravel) Generated VISSIM network model using processed data Analysis of simulation results Assembled research findings 14

Training GPS and traffic counting QTravel –Extracted data collected from field trips VISSIM Software –Simulation set up –Data input and analysis –Calibration and validation 15

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

Data Collection (cont.) 17

Data Collection (cont.) 18 Sample Data 9/16/2013EB On-rampEmma EB On-rampJared EB FreewayIsaac EB FreewayJared /17/2013EB FreewayIsaac EB FreewayEmma WB FreewayJared /18/2013EB FreewayIsaac WB On-rampEmma EB FreewayIsaac DateVideo NameLocation Student CollectedCars TrucksTotal List of Videos Completed

Data Collection (cont.) 19 QTravel

Methodology 20 VISSIM Training Simulation Setup Run Simulation Results One Lane Ramp Two Lane Ramp Validation Calibration Study Site Data Collection

Simulation 21 Network Model

Calibration and Validation Calibration –Desired speeds –Routing decisions –Driving behavior Validation –Speed (+ 10%) –Travel Time (+ 15%) –Volume 22

Calibration and Validation (cont.) 23 Travel Time SimulationTravel Time (sec)ActualAccepted Result Time (sec)CarsTrucksTime (sec)PercentageRange (sec) % Mean SpeedActualAccepted Result CarsTrucks Speed (mph)PercentageRange % PASS Speed

Results 24 SimulationTravel Time (sec)Number of Vehicles Time (sec)CarsTrucksCarsTrucks SimulationTravel Time (sec)Number of Vehicles Time (sec)CarsTrucksCarsTrucks One Lane On-Ramp Without Ramp Meter One Lane On-Ramp With Ramp Meter

Results (cont.) 25 SimulationTravel Time (sec)Number of Vehicles Time (sec)CarsTrucksCarsTrucks SimulationTravel Time (sec)Number of Vehicles Time (sec)CarsTrucksCarsTrucks Two Lane On-Ramp Without Ramp Meter Two Lane On-Ramp With Ramp Meter

Results (cont.) 26

Results (cont.) 27 Decrease in standard deviation MZ = Merge Zone NMZ = Non-Merge Zone

Results (cont.) 28 Increase in Speed MZ = Merge Zone NMZ = Non-Merge Zone

Results (cont.) 29

Conclusion 30 No significant change in overall speed and travel time Significant change in sectional average speed and speed variation Ramp meters are more effective on two-lane on-ramps in increasing safety

Timeline Task Week 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 31LegendComplete

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/ , 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 , 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. 32

References (cont.) Federal Highway Administration, USDOT (2013). “FHWA Localized Bottleneck Program.” (Accessed 6/9/2014) Maps, Google (2014). (Accessed ,83m/data=!3m1!1e3?hl=en Maps, Google (2012). (Accessed ,3a,75y,243.6h,66.31t/data=!3m4!1e1!3m2!1si7sOFQJVai_eF3v7k8u_LQ!2e Freeways_and_Highwayshttp:// Freeways_and_Highways

Questions 34