Project 5: Ramp Metering Control in Freeway SystemTeam Members: Faculty Mentor:Isaac Quaye Dr. Heng WeiJunior GRA: Emma Hand Karteek K. Allam SophomoreJared SagagaJunior*

Sponsor2

What are Ramp Meters?3Traffic controls that regulate traffic flow entering a highway

(Source: Reference 6)

Uses of Ramp MetersReduce congestionImprove throughputReduce travel timeImproved travel time reliabilityEnsuring safety of vehicles

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(Source: Reference 6)

Types of Ramp MeteringFixed timePre-timed meter cycle based off of past data ResponsiveMeter cycles vary depending on changes in traffic conditionsIsolatedCoordinated

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

NetworkingReceived information from Mn/DOT, WSDOT, ODOT

Mn/DOT uses traffic responsive

WSDOT uses traffic responsive with fuzzy logic algorithm

ODOT uses fixed timings

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Scope of StudyConducting research on the study site (I-275) by gathering data using traffic counter and GPS deviceCriteria Elevated locations nearby for placing the camcorder to capture the trafficLocation should be busier in the peak hours than the normal flow of freewayAnalyzing traffic during the peak hoursInvestigating and observing both a single and two lane ramp implementation*

GoalsAnalysis of data collected InvestigateEffectiveness of ramp implementationOne or two lane ramp metering Successfully run simulations on VISSIMPresent and complete deliverables

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TasksUtilizing 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 results10

Methodology11

Study SiteData CollectionOne Lane RampTwo Lane RampVISSIMResults

12Data CollectionStudy SiteLegendEast-Bound Sections

West-Bound Sections

Data Collection (cont.)13

Data Collection (cont.)14

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

Data Collection (cont.)16QTravel

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

East-BoundTime of DaySection 1 Average Time (mm:ss)Section 2 Average Time (mm:ss)Morning00:4802:42Afternoon00:5202:19Evening 00:4602:24

West-BoundTime of DaySection 1 Average Time (mm:ss)Section 2 Average Time (mm:ss)Morning02:0201:30Afternoon02:011:32Evening1:4901:29

Data Collection (cont.)18

TrainingUsing GPS device and softwareCollecting 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 vehicles19

Training (cont.)20GPS Traffic Counter

ProgressPost-Processing data collected Analyzing the data collected with the GPS and traffic counting device Intro to VISSIM Overview on the function of VISSIMPreliminary training on VISSIMs interface

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Timeline*

TaskWeek1-234567-8Methods of evaluation and researchEquipment and software trainingData collection and analysisUse data to develop deliverablesCreate and run simulation modelsComplete deliverablesCompleted

ReferencesZongzhong, 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 TransportationSystems: 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.*

References (cont.)Federal Highway Administration, USDOT (2013). FHWA Localized Bottleneck Program. (Accessed 6/9/2014) Maps, Google (2014). (Accessed 6/30/2014).Maps, Google (2012). (Accessed 6/30/2014).24

Questions?*

Photo source: http://ops.fhwa.dot.gov/bn/resources/case_studies/madison_wi.htmReduce traffic volumes on highway by spreading out queues of vehiclesReduce frequent traffic congestion/increases speed and travel timeReduce accidents such as side swipe and rear end collisionsTravel times are reliable because of less congestionThroughput volume of traffic on roadwayWant volume to increase because allows more vehicles to move uninterrupted Give pause between each pointSafety as rate of vehicles let onto freeway decreased, longer period of time for which motorists can see pockets in mainline traffic and merge with less side swipe collisions.Photo source: http://ops.fhwa.dot.gov/bn/resources/case_studies/madison_wi.htm

Metering cycle total time duration of red and green lights

Fixed time meter cycle is time it takes for meter to change from red to green and back to red. Traffic conditions around ramp observed in the past are averaged to decide length of meter cycle. Assumes traffic patterns are the same or similar from day to day.

Responsive sensors are set up on ramp and main freeway line around ramp. Meter rates change according to data on traffic conditions that sensors collect. Busier traffic means the red light will last longer, larger gaps in freeway traffic call for longer periods of green light. Two types, isolated and coordinated. Explain what meter rate is, and that will define sensors in next slide

Coordinated also senses arterialsIsolated doesnt sense arterialsWashington 126 ramp meters. This number was recorded in 2002.Minnesota 444 ramp meters. Current recording. They use traffic responsive software.Ohio 34 ramp meters. Current recording. ODOT uses fixed timings on the majority of its ramp meters.

Map showcasing the status of coordinated ramp-metering system implementations in the United States.Diagram source: Implementation and Operational Guidelines on Coordinated Ramp Metering Systems by Zong Z. TianReceived information from transportation and operations engineers.Fuzzy (WSDOT) - The algorithm takes real-time traffic data and computes how many cars to release per a minute so as to minimize congestion. The real time traffic data is collected by a loop of wire in the roadway which senses when cars pass over it (called an inductance loop).1. Traffic flow mainly from freeway mainline and on-ramp 2. Observing the traffic flow during certain hours of the day, mainly peak hours.3. Seeing which one would be most efficient and effective in combination with a ramp metering in place4. Using VISSIM to run multiple simulations of possible real-world situations 5. Location should be busier in the peak hours than the normal flow of freeway.

Chose study site because loop detector already installed, can verify collected dataRamp metering algorithms are basically a set of instructions created in order to guide the meter system in determining the length of its cycleThere are lots of algorithms, but will only be focusing on Isolated ALINEA if time permitsShowing all of these other algorithms to show that there are many limitations for responsive metering. All of these algorithms have been proposed to deal with these limitations.System (box and sensors) called ATR (automatic traffic recorder) 626Mile markers 45 and 47 at exit 46 SharonvilleLoop detector station