Toward a Consistent and Robust Integrated
Multi-Resolution Modeling Approach for
Traffic Analysis
Jeff Shelton, TTI
Yi-Chang Chiu, Univ. of Arizona
TRB – Transportation Planning Conference
Houston, TX
May 17-21, 2009
Transportation Operations Group
Outline
 Introduction
– Mesoscopic
– Microscopic
 Multi-Resolution Modeling
– Concept
– Conversion Process
– Modeling Issues
 Case Study
 Applications
Transportation Operations Group
Outline
 Introduction
– Mesoscopic
– Microscopic
 Multi-Resolution Modeling
– Concept
– Conversion Process
– Modeling Issues
 Case Study
 Applications
Transportation Operations Group
Introduction
 Integrating mesoscopic dynamic traffic assignment
(DTA) and microscopic traffic simulation and
assignment models can be advantageous for regionwide operational planning projects
– DTA – region-wide estimation of traffic redistribution
– Microscopic – local operational analysis
 The integration synergizes the strengths of both
models.
 Challenges remain in model translation and interface
 Modeling issues to be addressed
– Consistency
– Situation in which feedback is needed
Transportation Operations Group
Simulation-Based Dynamic Traffic
Assignment (SBDTA)
 Address issues that may fall beyond the reach of both:
– Microscopic models: (dynamic but small-scale) typically used by
traffic engineers for project traffic studies
– Macroscopic models: (large-scale but static) typically used by
transportation planners for long-range planning
– SBDTA – dynamic and large-scale
 The scenarios of interest may result in shifts of network
or corridor-wide traffic flow patterns.
– Significant change to roadway configuration
– Certain corridor management strategies
Transportation Operations Group
Mesoscopic Dynamic Traffic
Assignment
 DynusT v2.0
– Free version available for
DYNASMART-P users
 Dynamic simulation and
assignment tool for regional
operational planning analysis
 Equilibrium-based Dynamic
Traffic Assignment
– Assigned paths are based on
experienced (actual) travel time
 Applications
– Assess impacts of ITS technologies
– Work zone planning and traffic
management
– Evaluate HOV/HOT lanes
– Congestion pricing
– Special event/emergency
evacuation
Transportation Operations Group
Microscopic
 VISSIM 5.1
 A driver-behavior-based
simulation tool capable of
performing multiple
applications including
– Analyzing complex intersections
– Border crossings inspection
booths
– Managed lanes
– University campus settings
 Fined-grained analysis
– Vehicle interactions
– Individual lane analysis
 Simulate multiple modes of
transportation simultaneously
3-D graphics
Transportation Operations Group
Outline
 Introduction
– Mesoscopic
– Microscopic
 Multi-Resolution Modeling
– Concept
– Conversion Process
– Modeling Issues
 Case Study
 Applications
Transportation Operations Group
Concept
 What is multi-resolution modeling?
– Integrating mesoscopic and microscopic models for the
purpose of achieving a specific goal
» Analyze network at both the system-wide and localized
levels
 Why is multi-resolution modeling so important?
– Mesoscopic & microscopic models are not mutually exclusive
– They are complimentary to one another and can accomplish
optimal modeling capabilities.
– Retain the best characteristics of both
» Realistic representation of regional traffic
» Detailed interactions
Transportation Operations Group
Concept
Sub-area
Cut
Mesoscopic
Model
Model Conversion
Process
Integration
Tool
Microscopic
Model
Transportation Operations Group
Concept
DynusT
SubArea
VISUM
VISSIM
Transportation Operations Group
Multi-Resolution Modeling Framework
Field Data
Regional
Travel
Demand
Model
Initial
Network
Conversion
(DynusT)
Calibration
•Speed Profile
•OD
•Traffic Model
Sub-Area Cut
Yes
Detailed Analysis
No
DVC
VISSIM
Calibration
Rerun
DTA
Network
Modification
Transportation Operations Group
DTA Model Preparation
 Convert the GIS layer of the Travel Demand Model to
Mesoscopic format.
 Disaggregate 24-hour matrix based upon car & truck
–
–
–
–
–
–
–
Home to work
Work to home
Home to private
Private to home
Thru
External Local
Non-home based external local
 Multiply each matrix by corresponding hourly factor
Transportation Operations Group
DTA Model Preparation
Multiply each
matrix by
hourly factor
H-W
W-H
H-P
P-H
THRU
EXLO
NHBEXLO
Summation of matrices gives you directional
1-hour matrix
Transportation Operations Group
DTA Model Preparation
24 - one hour matrices
Transportation Operations Group
Calibration
 Traffic flow model
– Traffic simulation in
DynusT is based upon the
Anisotropic Mesoscopic
Simulation (AMS) model
– Moves vehicles based upon
speed-density (v-k)
relationship
– v-k relationship is derived
from Greenshields
equation
Transportation Operations Group
Calibration
– Minimize the deviation
between simulated and
actual screen line counts &
speed profile
– Iterative process
– Program solves linearized
quadratic minimization
problem
– Results in updated OD
matrices
Estimated TimeDependent OD
Matrices
Traffic Assignment/
Simulation
Assignment Results
Linear Optimization
Model
Update Demand
 Time-Dependent OD
Traffic Network
Traffic Flow Model
Intersection Controls
Results
Optimized Affected,
Time-Dependent OD
Pairs
Transportation Operations Group
Conversion Process
 Sub-area cut
– Remove unneeded sections
of network
– Renumbering of new
zones, nodes and links
– Retains paths and flows
that travel through the
sub-area
Transportation Operations Group
Conversion Process
 DynusT-VISSIM Converter
– Developed by researchers
from TTI and UA
– Converts roadway network
to VISUM network
– Retains network geometry
– Converts all timedependent paths and flows
– Creates separate
transportation systems
(car, truck)
Transportation Operations Group
Conversion Process
 Microscopic model
– Calibrate VISSIM model to
reflect realistic roadway
conditions
– Perform detailed “finegrained” analyses
» Speed profile for
individual lanes
» Lane-changing
behaviors
» Vehicle interactions at
merge areas
– Create 3-D graphics for
presentations
Transportation Operations Group
Modeling Issues
 Consistency
– Network
» Lane configuration
» Geometric design
– Paths and flow
» Verify same origin/destination paths
» Verify number of vehicles generated
– Speed profile
» Perform field data collection to determine speed and
vehicle counts
» Obtain v-k curve from simulation output
» Calibrate models with field data
Transportation Operations Group
Modeling Issues
40
35
30
Speed (mph)
25
Observed
20
Calibrated
15
10
5
0
0
20
40
60
80
100
120
140
160
Density (veh/mi)
Transportation Operations Group
Modeling Issues
Field Data
Regional
Travel
Demand
Model
Initial
Network
Conversion
(DynusT)
Calibration
•Speed Profile
•OD
•Traffic Model
Sub-Area Cut
Yes
Detailed Analysis
No
DVC
VISSIM
Calibration
Rerun
DTA
Network
Modification
When Feedback is Necessary
Transportation Operations Group
Outline
 Introduction
– Mesoscopic
– Microscopic
 Multi-Resolution Modeling
– Concept
– Conversion Process
– Modeling Issues
 Case Study
 Applications
Transportation Operations Group
Case Study
City Council
proposes ordinance
to restrict trucks
from using left lane
on I-10 corridor
How does the ordinance
affect the freeway and
surrounding arterials?
Transportation Operations Group
Case Study
Which type of
model do I use?
Transportation Operations Group
Case Study
 Truck restricted lanes
– A case study to analyze the effectiveness of restricting trucks
from left-most fast lane on freeway
– 22-mile corridor of I-10 in El Paso, TX
– Analyze a.m. peak, p.m. peak, & mid-day
– Determine benefits
» Speed on left-most lane
» Acceleration/Deceleration patterns
» Vehicle interactions at merge areas
– DynusT estimates region-wide truck trajectories (route and
flows)
– VISSIM models detailed IH-10 truck lane operations given truck
trajectories
Transportation Operations Group
Model Development
106 Origin/Destination links
- 1895 Transportation
Routes created
Operations Group
Model Development
GPS unit was used to input freeway grading
information
Transportation Operations Group
Model Development
Field data collection-freeway speed profile
(PM peak hour)
Transportation Operations Group
Model Development
Data provided by TxDOT Automatic TrafficTransportation
RecorderOperations
Stations
Group
Model Development
Transportation Operations Group
Case Study
I -10 EB @ Sunland Park
(7-11 am)
65
64
63
62
61
60
59
58
57
56
1.5
Acceleration (ft/s2)
Speed (mph)
I-10 EB @ Sunland Park
(7-11 am)
1
0.5
0
-0.5
-1
-1.5
0
3600
7200
10800
14400
0
3600
7200
Restricted
Speed
14400
Time (sec)
Time (sec)
Base
10800
Base
Restricted
Accel/Decel
Transportation Operations Group
Case Study
I-10 EB @ Paisano
(3-7 pm)
I-10 EB @ Paisano
(3-7 pm)
Acceleration (ft/s2)
Speed (mph)
80
60
40
20
0
0
3600
7200
10800
14400
2
1.5
1
0.5
0
-0.5
-1
0
3600
7200
Time (sec)
Base
Restricted
Speed
10800
14400
Time (sec)
Base
Restricted
Accel/Decel
Transportation Operations Group
Case Study
I-10 WB @ Paisano
Left Lane (3-7 pm)
I-10 WB @ Paisano
Right Lane (3-7 pm)
80
Speed (mph)
Speed (mph)
80
60
40
20
0
60
40
20
0
0
3600
7200
10800
14400
0
3600
7200
Time (sec)
Base
10800
14400
Time (sec)
Restricted
Base
Restricted
Speed – Left vs. Right Lane
Transportation Operations Group
Outline
 Introduction
– Mesoscopic
– Microscopic
 Multi-Resolution Modeling
– Concept
– Conversion Process
– Modeling Issues
 Case Study
 Applications
Transportation Operations Group
Applications
 Managed lanes
–
–
–
–
Truck restricted lanes
HOV lanes
HOT lanes
Time-dependent variable
pricing
Transportation Operations Group
Applications
 Geometric design
alternatives
– Freeway direct connect
» Various design
configurations
– Ramp reconfiguration
» Braided ramps
» “X” ramps
Transportation Operations Group
Applications
 Traffic impact studies
– New retail shopping centers
» Driveways
» Pedestrian crossings
– University campus planning
» Integrating various modes
of transportation (e.g.
student, faculty, staff,
pedestrians, transit)
» New parking facilities
» Campus core closure
– Traffic calming
Transportation Operations Group
Questions ?
Transportation Operations Group