1. DynusT (Dynamic Urban Systems in Transportation)

2. Recent Projects IH corridor improvement (North Carolina, 2003-present)
IH tolling and congestion pricing (ELP, TX present)
IH work zone planning (ELP, TX-2004)
Evacuation operational Planning (HOU, TX, 2007, Baltimore, MD, 2005, Knoxville, TN, 2003)
Downtown improvement (ELP, TX, 2004)
ICM AMS modeling (Bay Area, CA, present)

3. On-going Efforts
Military deployment transportation improvement in Guam (PB, FHWA)
Interstate highway corridor improvement (TTI, TxDOT, ELP MPO)
Value pricing (ORNL, FHWA; SRF, Mn/DOT, TTI, TxDOT)
Evacuation operational planning (UA, ADOT; LSU, LDOT; Noblis, FHWA; Univ. of Toronto)
Integrated Corridor Management modeling (CS, FHWA)
Bay area regional modeling (CS, MTC)
Florida turnpike system traffic and evacuation analysis (FDOT Turnpike)

4. What DynusT Represents?
Regional Operational Planning Capability
Regional - area larger than corridor
Operational - traffic flow dynamics sensitive to signals, road configurations
Planning - short-term impact and long-term equilibrium
Enabled by
Mesoscopic Traffic Simulation
Dynamic Traffic Assignment (DTA)
Micro-meso-micro integration

5. What is Mesoscopic Traffic Simulation?
Not as detailed as microscopic models, but is as capable of high-fidelity traffic simulation of an entire region

6. What is Dynamic Traffic Assignment?
A method to predict/estimate how trip-makers may shift to other routes or departure time in response to:
Congestion
Pricing
Controls
Incidents
Improvements
Understand how individual travel decisions impact an entire region, by
Time of day
Origin-Destination (OD) zones
Transportation modes

7. How Trip-makers Adapt to Congestion

8. Macro-Meso-Micro Integration
Analyze Ingress/Egress points for weaving
Meso
Micro
Macro
Estimate toll lane usage and revenue
Proposed toll lanes

9. Macro-Meso-Micro Integration
Travel Demand Models (TDM)
Micro
e.g. VISSIM

10. Visualizing the Model’s Results - An Example

11. Applying toll on 495 ramp may improve traffic on both 495W and 95S
I-95S AM commuting traffic impacted by spillback from 495W

12. A “What-if” Pricing Scheme
Variable toll on I-95 S to I-495 W ramp
Toll increases with congestion level
Morning peak period (5AM - 11AM)
LOV 89%
HOV 11%
Value of Time: $10/hour
Pricing
Distance based tolls: $0.25 /mile
$2 for through traffic
Peak-period tolls: 7AM - 9AM
Dimensions of impacts
Departure time
Route
Both

13. Peak Spreading Due to Value Pricing
Change of departure time due to pricing

14. A Regional View (DynusT Animation)

15. A Closer View (VISSIM animation)

16. Addressing Diversion
Tolling may cause diversion on alternative routes and/or other transportation modes
Turnkey solution package needed to improve the capacity to which the traffic may be diverted
Signal optimization, information provision, transit operation, peak spreading

17. A Low-Hanging Fruit Strategy – Optimize Signal

18. Other Freeway Operations Scenarios/Strategies
Dynamic message signs
Congestion warning
Mandatory detour
Speed advisory
Information strategies
Pre-trip information
In-vehicle information
Incident
Work zone
Managed lanes
Truck only
Truck restriction

19. Resource Considerations
Initial TDM import and conversion
100+ hrs
Data collection and model calibration
300+ hrs
Scenario analysis and reporting
400+ hrs
Total man-hours
800+
Budget 1, ,500 hours; including learning

20. How to Get Started Capacity building
Training workshop – agency and consultants
Establish baseline and future datasets
Allow months with sufficient budget
Will be a valuable asset for many future applications
Save $$$ for agency in the long-run
Lesson learned from Minneapolis collapse
Plan ahead and get the model built
We are ready to act when needs arise