INTERFACING THE MORPC REGIONAL
MODEL WITH DYNAMIC TRAFFIC
SIMULATION
David Roden (AECOM)
Supin Yoder (FHWA)
Nick Gill and Zhuojun Jiang (MORPC)
Rebekah Anderson and Greg Giaimo (ODOT)
FHWA – TRANSIMS Deployment Project
Agenda
2





Study Overview
Network Conversion and Debugging
Trip and/or Tour Conversion
User Equilibrium Assignment and Convergence
Output Results and Sensitivity Tests
MORPC TRANSIMS Implementation
Purpose of the Study
3

AECOM, MORPC, ODOT, and FHWA are
participating in a study to route and simulate
MORPC’s tour-based demand on a TRANSIMS
network
Create a time-dependent TRANSIMS network
 Route and simulate TP+ trips on the TRANSIMS network
 Route and simulate MORPC tours on the TRANSIMS network
 Feedback travel times from TRANSIMS to the tour model
 Create a time-dependent transit network and tour routing

MORPC TRANSIMS Implementation
Network Conversion Process
4
TP+ Network
Conversion Script
TPPlusNet
Speed-Capacity
Node Data
Link Data
Zone Data
Link Details
Zone Connector Keys
TransimsNet
Signal/Sign Warrants
Synthetic Network
IntControl
ArcNet
Traffic Controls
Network Shapefiles
MORPC TRANSIMS Implementation
TRANSIMS Network
5
MORPC TRANSIMS Implementation
TRANSIMS Coding Concepts
6
MORPC TRANSIMS Implementation
Original/Default TRANSIMS Network
7
MORPC TRANSIMS Implementation
Zone Connector Activity Locations
8
MORPC TRANSIMS Implementation
Freeway Access Problems
Mc Naughten
p
IR 27
0
IR 27
0
mp
m
Ra
Ra
Noe-Bix
by Rd
Rd
IR 270
IR 270
9
Franklin
mp
Ra
m
Ra
p
Main
Main
Main
Main
Main
Main
IR 27
0
Centroid Connector
Mc Naughten
IR 270
IR 270
IR 270
Rd
p
m
Ra p
m
Ra
Loop ramps were added to the TP+ network to improve results
MORPC TRANSIMS Implementation
TRANSIMS Travel Demand Concepts
10


TRANSIMS models individual persons for 24+ hours
Trips between specific activity locations, at specific
times of day, using a specific travel mode and vehicle




Activity locations – street locations / block faces
Time of day (start/end/duration) – seconds
Modes – walk, bike, drive, ride, transit, P&R, K&R, etc.
Convert aggregate trip tables to individual travelers
at specific locations and trip start times


Zones  activity locations within the zone
Daily/time period  second of the day
MORPC TRANSIMS Implementation
Trip Table Conversion Process
11
Subzone Factors
Activity Location
Block Boundaries
Block Data
MORPC HH-Tours
Traffic Counts
Zone Boundaries
MORPC Zone Data
Non-HH Trip Tables
MORPC Diurnals
LocationData
TP+ Scripts
SmoothData
Activity Location
Trip Tables
Diurnal Distributions
ConvertTrips
Trip File
Vehicle File
Household File
Population File
MORPC TRANSIMS Implementation
Diurnal Smoothing Results
12
Trip Start Time
Number of Trip Start Times (15-Minute Increments)
120000
100000
80000
60000
40000
20000
MORPC Provided Start Times
Smoothed Start Times
0
0:00
2:00
4:00
6:00
MORPC TRANSIMS Implementation
8:00
10:00 12:00 14:00
Time of Day
16:00
18:00
20:00
22:00
Activity Location Weights
13



Use subzone socio-economic data to calculate trip
attraction weights by trip purpose and orientation for
each activity location within a TAZ
MORPC/ODOT provided a block data file to
calculate the attraction weights
Inconsistencies between the TAZ and block file
boundaries and socio-economic attributes
necessitated complex data processing
MORPC TRANSIMS Implementation
TAZ – Block Data Integration Issues
14
MORPC TRANSIMS Implementation
MORPC Tours  TRANSIMS Tours
15
Time
5:30
6:00
6:30
7:00
7:30
8:00
8:30
9:00
9:30
10:00
10:30
11:00
11:30
12:00
12:30
13:00
13:30
14:00
14:30
15:00
15:30
16:00
16:30
17:00
17:30
Home
Work Tour
Stop1
Work
MORPC TRANSIMS Implementation
Stop2
Stop1
At Work Sub-Tour
Shop
Stop2
Activities have
locations,
start times
and durations
Trips connect
activities
TRANSIMS Router and Microsimulator
16

Router builds a unique path for each trip
Between origin and destination activity locations (link-offset)
 Starting at a specific second of the day
 Using a specified travel mode and vehicle
 Based on network travel times in15-minute increments


Microsimulator moves vehicles between link-lane-cells
on a second-by-second basis
Cells are 6 meters long
 Vehicles move 0, 1, 2, 3, 4, 5, or 6 cells each second


Speeds = 0, 13.5, 27.0, 40.5, 54.0, 67.5 or 81.0 mph
MORPC TRANSIMS Implementation
Microsimulator Feedback Loops
17
Trips / Tours
Router
Network
Travel Paths
Yes
Yes
Change?
Change?
Microsimulator
Bottlenecks
MORPC TRANSIMS Implementation
Travel Times
No
Stop
Convergence Statistics
18

Convergence is defined using multiple statistics

Simulation stability and network performance



Number and location of “lost” vehicles by time of day
Difference between the average link delay and the Microsimulator
link delay – vehicle hours of travel by link and time of day
User Equilibrium – no traveler can improve their travel time
(impedance) by changing paths


Difference between the simulated path and the minimum impedance
path for each traveler – vehicle hours of travel by trip
The percentage of travelers with significant differences
MORPC TRANSIMS Implementation
Lost Vehicle Problems
19
Iteration 1
MORPC TRANSIMS Implementation
Iteration 25
Trip-Model Convergence Statistics
0.008
0
0.007
-1
0.006
-2
Link VHT Gap
Trip Time Gap
Relative Gap
0.005
-3
Time Difference (Avg)
0.004
-4
0.003
-5
0.002
-6
0.001
-7
0
-8
1
3
5
7
9
11
13
Iteration
MORPC TRANSIMS Implementation
15
17
19
21
23
25
Time Difference (Minutes)
20
Trip Gap by Time of Day
21
0.008
2
3
0.007
4
5
6
0.006
7
8
9
Trip Time Gap
0.005
10
11
0.004
12
13
14
0.003
15
16
17
0.002
18
19
0.001
20
21
22
0.000
23
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Departure Hour
MORPC TRANSIMS Implementation
15
16
17
18
19
20
21
22
23
24
24
25
Link VHT Gap by Time of Day
22
0.20
1
2
0.18
3
4
5
0.16
6
7
0.14
Link VHT Gap
8
9
0.12
10
11
0.10
12
13
14
0.08
15
16
0.06
17
18
0.04
19
20
0.02
21
22
23
0.00
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Time of Day
MORPC TRANSIMS Implementation
15
16
17
18
19
20
21
22
23
24
24
25
ATR 601: I-70 at Brice Rd.
23
7000
Station 601 (East) - Link 2179
6000
Hourly Volume
5000
4000
3000
2000
1000
Tour
Trip
Observed
0
1
2
3
4
5
6
7
MORPC TRANSIMS Implementation
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
Total Volume: All Stations
24
120000
Total Volume - All Stations
100000
Volume
80000
60000
40000
20000
Tour
Trip
Observed
0
1
2
3
4
5
6
7
MORPC TRANSIMS Implementation
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
Operational Impact Test
25



Used the turning movement volumes from the
simulation to update the signal timing plans for all
signals in the region
Applied Progression to calculate signal offsets
Applied Router-Microsimulator to convergence
MORPC TRANSIMS Implementation
Signal Timing and Progression
26
Aggregate Wait Time Problems
MORPC TRANSIMS Implementation
Signal Progression Corridors
Daily Cycle Failures – Original
27
MORPC TRANSIMS Implementation
Daily Cycle Failures – Operational Test
28
MORPC TRANSIMS Implementation
Next Steps
29




Implement global iterations between the tour-model
and the network simulation
Perform sensitivity tests and future forecasts
Refine operational details in downtown to provide
demand data for a VISSIM subarea analysis
Upgrade the model to TRANSIMS Version 5 Studio
and Visualizer
MORPC TRANSIMS Implementation