Transcript Slide 1
DynusT
(Dynamic Urban Systems in
Transportation)
Recent Projects
IH corridor improvement (North Carolina,
2003-present)
IH tolling and congestion pricing (ELP, TX2003-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, 2006present)
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
Macro
Meso
Micro
Proposed toll lanes
Analyze
Ingress/Egress
points for weaving
Estimate toll lane
usage and revenue
Macro-Meso-Micro
Integration
Macro
Travel
Demand
Models (TDM)
Micro
e.g.
VISSIM
Visualizing the Model’s Results
- An Example
Applying toll on 495
ramp may improve
traffic on both 495W
and 95S
I-95S AM commuting
traffic impacted by
spillback from 495W
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)
Value of Time: $10/hour
Pricing
LOV 89%
HOV 11%
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
Base Case
12000
Peak Spreading
10000
8000
6000
4000
2000
Tim e
10:30
10:00
9:30
9:00
8:30
8:00
7:30
7:00
6:30
6:00
5:30
0
5:00
# of Vehicles Generated
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
Information strategies
Congestion warning
Mandatory detour
Speed advisory
Pre-trip information
In-vehicle information
Incident
Work zone
Managed lanes
Truck only
Truck restriction
Resource Considerations
Initial TDM import and conversion
100+
Data collection and model calibration
300+
hrs
Scenario analysis and reporting
400+
hrs
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