1. Simulation-Based Equilibrium Assignment: Insights and Future Challenges
Michael Mahut, Michael Florian and Nicolas Tremblay
INRO
Montreal, Canada
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

2. Agenda Overview of DTA Bakersfield Project Calibration approach
Advances in assignment methodology
Conclusions
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

3. Types of DTA models microsimulation microsimulation high fidelity
car following
gap acceptance
lane changing
high fidelity
fluid / CTM
low fidelity
volume-delay & constraints
one-pass
iterative
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

4. Equilibrium DTA 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

5. Agenda Overview of DTA Bakersfield Project Calibration approach
Advances in assignment methodology
Conclusions
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

6. Network 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

7. Calibration Data Data provided Other potential data
2005 turning movement counts (16 major intersections)
2005 Route 99 car and truck counts
2006 AM & PM qualitative queuing observations
Other potential data
speed measurements
travel time probes
Counts from Kern COG – AM and PM 15-minute movement counts for cars only on arterials
Caltrans District 6 collected car&truck link flows on ramps and 1 freeway count cars only
when counts taken?
single visual queuing observations AM and PM
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

8. Network 1 mile 1 km 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

9. Link Flows 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

10. Relative Gaps
This is a typical convergence plot (1 graph for each departure interval):
Stabilizes naturally at a certain value of rel-gap
Avg at 70 iterations is 5.0%: quite typical
NOTE: good convergence does not necessarily mean good results!
you would not say that a static model is superior to a dynamic model because it gets better convergence: lower convergence is a necessary result of the higher level of reality in the model;
this also holds true also for the various types of DTA: the ones with more approximate representation of traffic would be expected to get better convergence!
The real question is: how good are the results??
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

11. Calibration Results predicted flows counts interval slope R2
4:15-4: %
4:30-4: %
4:45-5: %
5:00-5: %
5:15-5: %
5:30-5: %
interval slope R2
7:15-7: %
7:30-7: %
7:45-8: %
8:00-8: %
8:15-8: %
8:30-8: %
predicted flows
skip first & last intervals
counts often show variability
Dynameq results have little variability
counts
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

12. Queues 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

13. Performance Demand Trips RAM CPU  Speed-up
4x30-minute matrices, 2 classes
Trips
61000 (car) (truck)
RAM
80 MB
CPU  Speed-up
per iteration: 66 sec  110x
full DTA: 77 min  1.6x
Partitions and zone groups
Zone groups
Simplify the use of zonal data
Used for zone subset specification
Used for submatrix specification
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

14. Agenda Overview of DTA Bakersfield Project Calibration approach
Advances in assignment methodology
Conclusions
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

15. Link Flows 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

16. Select Link 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

17. Path Flows 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

18. Agenda Overview of DTA Bakersfield Project Calibration approach
Advances in assignment methodology
Conclusions
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

19. MSA Improvements general observation (1) dynamic reset
MSA can be slow in removing flow from unattractive paths
(1) dynamic reset
Step-size increases with increasing departure interval
(2) quasi-gradient
Path-flow adjustment by O-D based on quasi-gradient
Step size applied to total displaced flow (O-D)
MSA can be very slow in removing flow from paths – can be a problem is unattractive paths are identified in the early iterations.
Two improvements:
Dynameq step-size adjustment
Hybrid quasi-gradient / MSA approach
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

20. MSA 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

21. Gradient + Reset 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

22. Agenda Overview of DTA Bakersfield Project Calibration methodology
Advances in methodology
Conclusions
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

23. Conclusions Micro-simulation based DTA (Dynameq) Calibration
can be applied to medium-sized networks and calibrated with reasonable effort
Calibration
demand side (path and O-D) causes: quickly identified using Select Link and Path Analysis tools
Consistency (“Reproduce-ability”)
Changes to demand or supply lead to reasonable (commensurate) changes to model outputs
Equilibrium property is critical!
11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida

24. 11th TRB Planning Applications Conference
May 6-9, Daytona Beach, Florida