DynusT (Dynamic Urban Systems in Transportation)

Recent Projects

IH corridor improvement (North Carolina, 2003-present)

IH tolling and congestion pricing (ELP, TX-2003-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, 2006-present)

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)

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

What is Mesoscopic Traffic Simulation? Not as detailed as microscopic models,

but is as capable of high-fidelity traffic simulation of an entire region

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

How Trip-makers Adapt to Congestion

Macro-Meso-Micro Integration

Analyze Ingress/Egress

points for weaving

Meso MicroMacro

Estimate toll lane usage and revenue

Proposed toll lanes

Macro-Meso-Micro Integration

Macro Travel

Demand Models (TDM)

Micro e.g. VISSIM

Visualizing the Model’s Results

- An Example

I-95S AM commuting traffic impacted by

spillback from 495W

Applying toll on 495 ramp may improve

traffic on both 495W and 95S

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

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

0

2000

4000

6000

8000

10000

12000

5:00

5:30

6:00

6:30

7:00

7:30

8:00

8:30

9:00

9:30

10:0

0

10:3

0

Time

# o

f V

ehic

les

Gen

erat

ed

Base Case

Peak Spreading

A Regional View (DynusT Animation)

A Closer View (VISSIM animation)

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

A Low-Hanging Fruit Strategy – Optimize Signal

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

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 1,000 - 1,500 hours; including learning

How to Get Started

Capacity building Training workshop – agency and consultants

Establish baseline and future datasets Allow 12-18 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