Traffic Study for Deerfoot Trail, Calgary Arora - ARORA_Traffic St… · Traffic Study for Deerfoot...
Transcript of Traffic Study for Deerfoot Trail, Calgary Arora - ARORA_Traffic St… · Traffic Study for Deerfoot...
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Traffic Study for Deerfoot Trail, Calgary
Capacity Drop, Hysteresis, MFD and METANET Model for Deerfoot Trail
Karan AroraUCID: 10141627Email ID: [email protected]
Transportation Engineering Department,Schulich School of Engineering
Supervised by:Dr. Lina Kattan, Associate Professor, Urban Alliance Professor in Transportation Systems OptimizationCivil Engineering, University of CalgaryEmail ID: [email protected]
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Biography
Karan Arora joined University of Calgary in 2015.
He pursued his Bachelors in Civil Engineering, majored in Transportation Engineering and Business Management, from Indian Institute of Technology (IIT) Roorkee, India. He has a work experience of 1 year as a Graduate Highway Engineer with Systra MVA Consulting (France) Pvt. Ltd., New Delhi.
Currently, his research focuses on studying the impact of Intelligent Transportation System (ITS) – including Variable Speed Limit and Ramp Metering Design on various freeways and arterials in the city of Calgary.
Karan AroraMasters of ScienceTransportation Engineering GroupSchulich School of EngineeringUniversity of CalgaryEmail: [email protected],https://ca.linkedin.com/in/karora2Contact Number: +1-4034782862
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Traffic Congestion
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Introduction
To accommodate increasing traffic demand, constructing new highways and adding lanes is not always the best option:
Through proper management of existing transportation system, traffic condition can be improved to a very great extent .
For example, freeways traffic can be made more smoother with the help of Ramp Metering, Variable speed limit design, etc.
Traffic management for one expressway can never be applied to other expressways. Every expressways and urban traffic have there unique characteristics of traffic movement
Category of Area 4 Lanes Highway 6 Lanes Highway
Rural & Suburban Area
$4-$6 million per mile
$8-$10 million permile
Urban Area ~$7 million per mile
~$11 million per mile
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Greenshield’s theory Van Aerde Car-Following Model
Basic Theoretical Model Practically the diagrams usually deviates
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Deerfoot Data
Freeway section of the Queen Elizabeth II Highway (Highway 2) in Calgary, Alberta, Canada
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Deerfoot Study
To examine the congestion phenomenon this study focuses on:
Macroscopic Studyi) Capacity dropii) Hysteresisiii) Macroscopic Fundamental Diagram iv) METANET Model
- Variable Speed Limit(VSL)- Ramp Metering(RM)
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Capacity Drop
Uncongested
Congested
Capacity Drop
Existence of Capacity Drop at Bottleneck Locations
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Hysteresis Phenomenon
• Existence of Hysteresis Loops at Bottleneck locations• Hysteresis disappears in case of aggregate data
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Macroscopic Fundamental Diagram(MFD)
Flow-Density Curve(Aggregated)
Weekdays Average Weekends Average
Scatter almost disappear after aggregating the data from different detectors
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METANET MODELi-1 i i+1
(Flow-Density Equation)
(Conservation of Vehicles)
(Desired Speed)
(Speed-Dynamics Equation)Relaxation, Convectionand Anticipation
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Optimization Problem
Objective Function(Least Square Optimization Problem)Minimize the error term:
Parameters to Calibrate(with Lower and Upper Bound)
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Solving Technique
MATLAB “fminsearchbnd”A tool to optimize unconstrained non linear functionsUses Derivative free method
fminsearchbnd
Error Function
Converge
Passes vector Calculated error
No
Optimum Solution
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Calibration Results
Symbol Name Value
κ Density offset 104.4357 veh/km/lane
ηlow Anticipation increasing density 99.9996 km2/h
ηhigh Anticipation decreasing density 20.0029 km2/h
τ Fundamental diagram parameter 86.368 s
Vf,m Free flow speed 105 km/h
φm Speed changing response time 0.539
ρcr,m Critical density 239.994 veh/km/lane
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Results
Uncongested Flow Congested Flow
*The Deerfoot Data here belongs to VISSIM Model(Calibrated in such a way that the simulation run represent real time model)
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Uncongested Flow Congested Flow
*The Deerfoot Data here belongs to VISSIM Model(Calibrated in such a way that the simulation run represent real time model)
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Flow-Density Diagram for Uncongested and Congested Flow
*The Deerfoot Data here belongs to VISSIM Model(Calibrated in such a way that the simulation run represent real time model)
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Conclusion & Future Work
Study performed an analysis of:
i) Capacity Drop
ii) Hysteresis
iii) Macroscopic/microscopic Calibration, of Deerfoot Traffic
Future Studyi) Further detailed study of Capacity Drop, Hysteresisii)Creating Dynamic network using the concept of game theoryiii)Impact of Variable Speed Limit Design(VSL)iv)Impact of Ramp Metering(RM)
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References
Papageorgiou, Jean-marc Blosseville and Hadj Salem (1990). Macroscopic Modelling Of Traffic Flow on the Bouldevard Periphgrique in Paris. Transportation Research Part B.
Calibration of METANET Model for Real-Time Coordinated and Integrated Highway Trac Control using Genetic Algorithm: Tehran Case Study, MahnazAghamohaqeqi et. al. CICI 2012
Derivation of Van Aerde traffic stream model and studying the effect of Ramp Metering; By Karan Arora, Saeid Saidi, Bidoura Khondaker & Lina KattanVOL 1, ISSUE 2, SEP-2015, International Journal of Advanced Research in Engineering (ISSN 2412 4362 Online)http://researchplusjournals.com/index.php/journals/archive/international-journal-of-advanced-research-in-engineering-issn-2412-4362-online/1/2
Geroliminis, N., Daganzo, C.F., 2007. Macroscopic modeling of traffic in cities. In: TRB 86th Annual Meeting, # 07-0413, Washington, DC
ENCI 703/ENEL641 Lecture Notes UofC by Dr. Lina Kattan, Google images
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Thank You !
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