This document summarizes Aidin Massahi's dissertation proposal on using multi-resolution modeling to assess active traffic management strategies on urban streets. The proposal discusses using dynamic traffic assignment simulation models at different levels of resolution (macroscopic, mesoscopic, microscopic) to evaluate strategies like adaptive ramp metering, variable speed limits, and dynamic lane control. The goals are to develop methods to assess impacts on performance measures like mobility, reliability, safety and emissions, and to demonstrate the methods on a real-world case study. The literature review covers previous uses of multi-resolution modeling and different traffic simulation packages to analyze active traffic management.

1. Multi-Resolution Modeling of Active Traffic
Management on Urban Streets
1
By: Aidin Massahi
Major Advisor: Dr. Mohammed Hadi
Committee Members:
Dr. Albert Gan
Dr. Xia Jin
Dr. Hesham Ali
Dr. Yan Xiao
Dr. Zhenmin Chen
Dissertation Proposal Defense
March 28, 2016

2. AGENDA
 INTRODUCTION
 LITERATURE REVIEW
 METHODOLOGY
 RESEARCH TASKS
2

3. INTRODUCTION
3
Background
 ATM providing significant benefits in terms of travel time, travel time reliability,
emission, fuel consumption and safety
 What ATM strategies are the most advantageous
 Multi-resolution model (MRM) is an integrated approach that combines different
modeling levels in the assessment of ATM strategies
 Dissertation develops and uses methods for the use of MRM to support agency decisions
related to ATM strategies deployment on urban streets and comparing the benefits of
these strategies compared to capacity improvements

4. INTRODUCTION
 Recent interests in assessing the benefits of ATM strategies on urban streets
 MRM is simulation-based Dynamic Traffic Assignment (DTA)
 DTA is capable of realistic modeling of traffic flow and driver responses
 DTA model the time-dependent network states
 DTA vehicle trajectories output can be processed to produce more detailed statistics
 The main benefit of ATM is to improve reliability
 Reliability concept requires the assessment of the impacts of variations in demand weather,
congestion, incident, and other events on system performance
 Scenario-based analysis that has been used for reliability assessment will be extended to evaluating
other performance measure including mobility, safety, and environmental impacts
 Estimating performance is to base the performance on analyzing vehicle
trajectories
 Reduce the dimensionality of generated scenarios
 Scenario Generations requires a large number of simulations analyzing by clustering and grouping
analysis patterns into representative patterns
4
Motivation of the Study

5. INTRODUCTION
 Goal: Develop and research methods for assessing the impacts of ATM
strategies on urban streets
 Objective1- Develop methods that utilize combinations of advanced simulation
and DTA models to allow the effective assessments of ATM strategies in terms of
their impacts on mobility, reliability, safety, and environmental performance
measures
 Objective2- Compare the methods developed according to Objective 1 above
with the results obtained from the assessment of ATM strategies using simple
sketch planning procedures to justify the need for the more detailed assessment of
simulation models
 Obective3- Demonstrate the use of the developed methods for assessing the
benefits of implementing ATM strategies in a real-world implementation
5
Research Goal and Objectives

6. LITERATURE REVIEW
6
 Adaptive Ramp Metering
 Adaptive Traffic Signal Control
 Dynamic Junction Control
 Dynamic Lane Reversal / Contraflow Lane Reversal
 Dynamic Lane Use Control
 Dynamic Merge Control
 Dynamic Shoulder Lane
 Variable speed limits(VSL)
 Queue Warning
 Transit Signal Priority
Active Traffic Management (ATM) Strategies

7. LITERATURE REVIEW
7
Multi-Resolution Analyses of Advanced Traffic
Management Strategies
 Sketch Planning
 Macroscopic Simulation
 Mesoscopic Simulation
 Microscopic Simulation

8. LITERATURE REVIEW
8
Multi-Resolution Analyses of Advanced Traffic
Management Strategies
 Sketch Planning
 Florida ITS Evaluation Tool (FITSEVAL)
 Ramp Metering, Incident Management Systems, Highway Advisory Radio (HAR) and Dynamic
Message Signs (DMS), Advanced Travel Information Systems (ATIS), Managed Lane, Signal
Control, Emergency Vehicle Signal Preemption, Smart Work Zone, Road Weather Information
Systems, Transit Vehicle Signal Preemption, Transit Security Systems, Transit Information
Systems and Transit Electronic Payment Systems
 The evaluation methodology implemented in FITSEVAL:
 Postprocessor of demand model
 Running assignment steps
 TOPS-BC
 Highway advisory radio (HAR), dynamic message signs (DMS), pre-trip travel information, ramp
metering systems, incident management systems, signal control, emergency vehicle signal
preemption , ATDM speed harmonization employer based traveler demand management ATDM
hard shoulder running, ATDM high occupancy lanes, road weather management, work zone

9. LITERATURE REVIEW
9
Multi-Resolution Analyses of Advanced Traffic
Management Strategies
 Macroscopic Models
 Macroscopic models can be used with and without traffic assignment
 Regional Demand Forecasting Models
 Highway Capacity Manual (HCM)- Based Tools
 STREETVAL
 FREEVAL
 HCS
 VISUM
 VISSUM has static assignment and DTA modules
 VISUM traffic model considers spillback
 VISUM has an (ODME) tool based on initial O-D matrices and count data

10. LITERATURE REVIEW
10
Multi-Resolution Analyses
Mesoscopic Models
 DYNASMART
 Demand Inputting Methods:
• Time-variant O-D matrices among origin-destination
• Vehicle loading method, requires inputting the origin and destination of each vehicle zones
 DynusT
 Model shows more realistic representation of traffic flow compared to the original
Dynasmart model
 DTALite
 Working in combination with the Network Explorer for Traffic Analysis (NEXTA)
graphical user interface
 DTALite’s Output data can be visualized using the NEXTA user interface
 Dynameq
 Dynameq is its more detailed simulation models
 Capable to model lane-by-lane traffic
 Simulation model is considered as event-based simulation
 Cube Avenue
 Simulation-based DTA extension of the Cube Voyager demand forecasting environment
 Vehicles are clustered into homogenous “packets” and simulated as they move through
the network

11. LITERATURE REVIEW
11
Multi-Resolution Analyses
Microscopic Models
 CORSIM
 CORSIM does not have DTA model and requires the users to input turning movement counts
 CORSIM and TRANSYT-7F, signal optimization program offered as one combined product
 CORSIM is able to model incidents directly
 Paramics
 Used to model ITS alternatives including variable speed limits (VSL), high occupancy tolling
(HOT), vehicle actuated signals, incident response, HOV lanes, dynamic lane control, route
choice updates, roadside message signs, and car parking signs
 SimTraffic
 Utilized with the Synchro signal optimization tool to optimize signal timings of signalized
facilities
 SimTraffic incorporates a more user-friendly interface that greatly eases network coding
requirements

12. LITERATURE REVIEW
12
Multi-Resolution Analyses
Hybrid Mesoscopic-Microscopic Model
 AIMSUN
 AIMSUN recommended for modeling ITS applications
 Microscopic Simulator Software Development Kit (microSDK), allowing users to
override default behavioral models
 AIMSUN Platform Software Development Kit (platformSDK) can develop new interface
for ITS applications
 TransModeler
 TransModeler is capable to model parts of the network at the microscopic level and parts
of the network at the mesoscopic and/or macroscopic simulation level in the same run
 VISSIM
 VISSIM has a powerful programing extension, allowing modelers to program advanced
managements and pricing strategies
 Utilize link-connector structure allowing for increasing accuracy & flexibility of modeling

13. LITERATURE REVIEW
13
Multi-Resolution Analyses
Hybrid Mesoscopic-Microscopic Model
 AIMSUN
 AIMSUN recommended for modeling ITS applications
 Microscopic Simulator Software Development Kit (microSDK), allowing users to
override default behavioral models
 AIMSUN Platform Software Development Kit (platformSDK) can develop new interface
for ITS applications
 TransModeler
 TransModeler is capable to model parts of the network at the microscopic level and parts
of the network at the mesoscopic and/or macroscopic simulation level in the same run
 VISSIM
 VISSIM has a powerful programing extension, allowing modelers to program advanced
managements and pricing strategies
 Utilize link-connector structure allowing for increasing accuracy & flexibility of modeling

14. 14
INCIDENT MANAGEMENT
The main elements of incident management include the incident detection, incident
verification, response selection, incident removal, traffic management, and the
provision of traveler information
Program Improvement Impacts
CHART program,
MD
Detection, verification, and service
patrols
• Incident reduction from 77 minutes to 33 minutes
• Reduced the blockage duration from incidents by 36%. This translates to a reduction in highway user delay time of about 42,000
hours per incident
• 15% to 38% reduction in all secondary crashes; 4% to 30% reduction in rear-end crashes; and 21% to 43% reduction in severe
secondary crashes
Atlanta, GA
NAVIGATOR
system
Detection, verification, and service
patrols
• Reduced 5.775 kg of hydrocarbons (HC), 75.58 kg of carbon monoxide (CO) and 8.059 kg of nitrous oxides NOx per incident
• Reduced incident clearance time by an average of 23 minutes and the incident response time by 30%
• Average time between first report and incident verification was reduced by 74%
• Average time between verification and response initiation reduced by 50%
• Average time between incident verification and clearance of traffic lanes reduced by 38%.
• Maximum time between incident verification and clearance of traffic lanes was reduced by 60%
San Antonio, TX
Tech Program
Incident detection and verification using
CCTV
• Improved the response time by 20 % (21% reduction for major incidents and 19% for minor incidents)
Brooklyn, NY
Detection, verification, and service
patrols
• Reduced the incident clearance average time by 66%
• Reduced the average incident clearance time from 1.5 hours to 31 minutes
Minneapolis, MN Automatic tow truck dispatch program • Decreased the incident response and removal times by 20 minutes (85% improvement)
San Francisco, CA Service patrol implementation
• Reduced average response time from 28.9 minutes to 18.4 minutes (36 percent)
• Reduced clearance time from 9.6 minutes to 8.1 minutes (16 percent)
• Total delay saving per assisted breakdown was 42.4 vehicle-hours
• Total delay savings per assisted accident was 20.3 vehicle-hours per incident
Houston, TX
TrsnsGUide
Service patrol implementation
• Reduced total duration of incident by 16.5 minutes
• Dropped the average incident duration by 30%
Denver, CO Service patrol implementation • Reduced total duration of incident by 10.5 minutes
Pittsburgh, PA Service patrol implementation
• Reduced response time to incidents from 17 to 8.7 minutes
Gresham, OR Service patrol implementation • Shortened the delay-causing incidents by approximately 30% on two lane Highway and 17% on Interstate
Northern, VA • Cell phone in response vehicles
• CAD screens in response vehicles
• GPS location in response vehicles
• Reduced the duration for all incidents by 2 to 5
• Reduced the duration for all incidents 2 to 5 minutes due
• Reduced the duration for all incidents 4 to 7 minutes
The Florida DOT,
District IV, FL
Detection, verification, and service
patrols
• The incident duration is reduced by 18 %
ITS Deployment
Analysis System
(IDAS)
• incident detection & verification
• incident response & management
• Combination detection &
management
• Incident duration reduction of 9%
• Incident duration reduction of 39%
• Incident duration reduction of 51%
• 21 percent of fatalities are shifted to injuries

15. 15
Incident and Incident Management Modeling in The Tools
 CORSIM
 Specific frame to model incident on freeways
 Drop the capacity in the vicinity of a freeway incident (using a rubberneck factor
and the warning sign location)
 AIMSUN and VISSIM
 Specifying stopped bus with bus dwell time
 Set up a red signal at the incident lane
 Used the “Add vehicle” function, within the VISSIM’s COM interface
 TOPS-BC Spreadsheet-Based Tool
1. Travel time reliability improvement
2. Fatality crash reduction
Improvement in travel time reliability is calculated as the reduction in incident-
related delays
 FITSEVAL Tool
Diversion rate is set as a function of the estimated saved delays
21% of fatalities are shifted to injuries
Additional reduction factor of 2.8 % is used to account for IM on accident
Reduction in incident delay is calculated based on queuing analysis
Incident delays on the arterials are 1.25 higher than freeway

16. 16
Adaptive Signal Control
 The adaptive control software adjusts traffic signal splits, offsets, phase lengths, and
in some cases phase sequences to minimize delay and reduce the number of stops
Improvement Location Impacts
Los Angeles, CA
• Decreased travel time by 12.7 percent
• Reduced average stops by 31.0
• lowered average delay by 21.4 percent
Gresham, OR
• Reduced the average travel times by 10 percent
• Saved over 74,000 gallons of fuel every year
Lee's Summit, Mo
• Average travel times decreased on the mainline up 39 percent
• Number of vehicle stops decreased by 17 percent to 95 percent per trip
• Average vehicle speeds improved 5 to 10 mile per hour
• Fuel consumption ranged between 4.5 percent increase and a 21.4
percent decrease
• Changes to pollutants (HC, CO, and NOx) emission varied from a 9
percent increase to a decrease of 50 percent
Two corridors in CO
• Improved weekday travel times 6 to 9 percent
• Increased weekday average speed 7 to 11 percent
• Decreased weekday stopped delay 13 to 15 percent
Oakland County, MI
• Reduced travel time by 7 percent in the morning peak and 8.6 percent
during evening peak periods
• Off peak and non-peak direction travel times were improved by 6.6 to
31.8 percent
New York City, NY • A 10 percent reduction in travel times
Detroit, MI • Total crashes per mile per year decreased by 28.8%

17. 17
Time of Day Signal Control Retiming
 Signal timing strategies try to minimize stops, delays, fuel consumption and air
pollution emissions and maximize the traffic progression through the system
Improvement Location Impacts
Syracuse, NY
• Reduced the number of stops by 15.7 percent, travel time by 16.7 percent, and delay by 18.8 percent
• 13.8 percent decline in fuel consumption
• A 13 percent reduction in vehicle emissions and noise pollution
• Decreased vehicular delay by 14 to 19 percent
• Reduced total stops by 11 to 16 percent
• Improved average speed by 7 to 17 percent
Oakland County, MI
• Reductions between 1.7 and 2.5 percent in Carbon monoxide
• 1.9 to 3.5 percent in Nitrogen oxide
• 2.7 to 4.2 percent reduction in hydrocarbon
Texas Traffic Light Synchronization program
• Reduced delays by 23 percent
• lowered travel time by 14 percent
• Reduced fuel consumption by 9.1 percent
U.S. Route 1, St. Augustine, FL
• Reduced delay by 36 percent
• Lowered travel time by 10 percent
• Annual fuel savings of 26,000 gallons
State Route 26, Gainesville, FL
• Reduced the average delay by 94 percent
• Saved 3,300 gallons in fuel consumption annually
Burlington, Canada
• Travel time was shortened by 7 percent
• Fuel consumption was decreased by 6 percent
Montgomery County, MD
• lowered delay by 13 percent
• Reduced fuel consumption by 2 percent
FETSIM Program, California
• Deceased delay by 15 percent
• Fuel consumption by 8.6 percent
Lee County, FL
• A 23 percent annual reduction in travel delays, causing $15,300,000 in travel time savings
• $2,000,000 per year in fuel savings
• Reduced vehicle emissions by 19 percent, resulting in an equivalent to $124,000 environmental benefits
Tysons Corner, VA • A 9 percent reduction in fuel consumption
Southwestern Pennsylvania Commission's (SPC)
Regional Traffic Signal System
• Average travel times were shortened by 6 percent
• Average stops lowered by 6 percent
• Average signal delay decreased by 16 percent
US-31, Kokomo, IN
• Saved 16,322 hours of travel time
• Reduced 982 tons of CO2

18. 18
Impact of Signal Timing Strategies During Incident
 New signal planning can increase the roadway capacity during arterial incidents and
diversion due to freeway incidents
 Give priority to specific movements in order to minimize the overall delay
 Increase or decrease the throughput of traffic at certain intersections by increasing
or decreasing the green times for those movements
 Modifying signal timing can be combined with traveler information that guide
motorists to alternative routes
Improvement Location Impacts
CHART program, MD
• Total delay time reduction of 30 million vehicle-hours
• A total fuel consumption reduction of 5 million gallons
Fargo, ND
• Improve travel times by 18 percent
• Increase speeds by 21 percent
Detroit, MI • Reduced delay by 60 to 70 percent for the affected paths

19. Weather-Response Signal Control
 Atmospheric events can decrease the efficiency of traffic signals
 Adverse weather can reduce visibility and pavement friction
 Readjusting signal timing plans is expected to mitigate delays due to severe
weather effects
 Signal adjustment would consider the increasing headways between vehicles in
inclement weather
19
Improvement Location Impacts
Minneapolis, MN
• A 8 % reduction of signal delay for each vehicle
• A 6 % reduction in average stops
Ogden, UT
• Reduced the cumulative travel time by 4.3 percent
• 11.2 percent reduction in the cumulative stop time
• Travel times of cross-street improved by 3 percent
• Overall cross-street stopped times decreased by 14.5 percent
Charlotte, NC
• Reduction in rear-end conflicts of approximately 22 percent for
moderate volume levels
• Reduction in rear-end conflicts of approximately43 percent for high
volume levels

20. LITERATURE REVIEW
20
Incorporation Travel Time Reliability
 Travel time reliability evaluation is critical to the assessment of ATDM strategies
 Travel time Reliability Indices
 Source of Travel Time Unreliability
I. Supply side
Incidents
 Work Zones
 Weather
 Traffic Control
Management Dynamic Pricing
Variation In Individual Driving Behaviors
II. Demand side
Special Events
Day-to-day Variation In Individual Behaviors
Unfamiliar Users
Reliability Performance
Metric
Definition Project Using Measure
Buffer Index
Buffer Index The difference between the 95th percentile travel time and the average travel time,
normalized by the average travel time
L03, L08
Failure/On-Time
Performance
Percentage of trips with travel times less than
 1.1 x median travel time
 1.25 x median travel time
Or percentage of trips with speed less than 50, 45, 40 or 35 mph
L03, L08
95th Percentile PTI
95th percentile of the TTI distribution (95th percentile travel time divided by the free-flow
travel time)
L03, L08
80th Percentile TTI
80th percentile of the TTI distribution (80th percentile travel time divided by the free-flow
travel time)
L03, L08
Skew Statistics
The ratio of 90th percentile travel time minus the median travel time divided by the median
travel time minus the 10th travel time percentile
L03
Misery Index The average of the highest 5% of travel times divided by the free-flow travel time L03
Standard Deviation Usual statistical definition L08

21. LITERATURE REVIEW
21
Incorporating Reliability into Operations Modeling Tools
 Scenario Manager : Capture exogenous unreliability sources
I. Scenario Specification
 Defining the spatial and temporal boundaries for which travel time
variability is examined
 Time-of-day selection for the scenario time horizon Determining
the analysis approach
 Selecting scenario components of interest
II. scenario generation
 Scenario generation aims to determine the occurrence of incidents
 Simulation Tools:
Model endogenous sources of demand unreliability
Vehicle Trajectory Processor:
Extracts reliability information from the simulation output
 Presents both O–D-level and path-level travel time statistics such as
average and standard deviation

22. METHODOLOGY
22
Utilized Framework

23. METHODOLOGY
23
Data Sources and Tools
 Speed, volume count, occupancy measurements, as well as associated
derived measures such as queue length and travel time estimates
 Partial origin-destination and travel time data
 Travel time and origin-destination data
 Incident data such as incident frequency, temporal, spatial and intensity
 Weather data
 Signal control data
 ATM parameters

24. METHODOLOGY
24
Network preparation for Multiresolution Analyses
 Step 1- Subarea network and demand matrix extraction
 Step 2-Importing the extracted network and the demand into NeXTA
 Step 3-Network Modification
 Step 4-Demand Estimation

25. METHODOLOGY
25
Developing a Methodology to Assess the Impacts of
ATM Strategies
 Simulation Platform
 Scenario manager and trajectory procedure models will interface with DTAlite
to produce the varies types of performance measures for each ATM strategies
 Synchro/SimTraffic tool will be used to optimized the signal controls and to
allow the emulation of different signal timing strategies
 SimTraffic microscopic simulation will be used as need it to simulate more
detail specific facilities in the network

26. METHODOLOGY
26
Development and Implementation Scenario Manager
 scenario specification
Define scenario components
I. Travel demand variation between days
II. External event (Incident, Weather)
III. Implemented ATM strategies
Determine analysis approach
I. Day-to-day variation (clustering analysis)
II. Weather (grouping analysis based on HCM2010 approach)
III. Incident (clustering analysis based on frequency, duration, lane blockage)
Defining the spatial and temporal boundaries
I. Determine incident locations on weekdays
Time-of-day selection for the scenario time horizon
I. Morning peak period

27. METHODOLOGY
27
Development and Implementation Scenario Manager
 Scenario Generation
 A k-mean clustering analysis will be used to group the real-world
demands between days into different traffic patterns
 Rain intensity classes
I. No Rain and Light Rain (precipitation rate<0.1 inch/hr)
II. Medium Rain (0.1 inch/hr <precipitation rate<0.25 inch/hr)
III. Heavy Rain (precipitation rate>0.25 inch/hr)
 Incident will consider the location, attributes, and duration of the incidents

28. METHODOLOGY
28
Trajectory Processor
 Allow analyzing the DTAlite simulation results
 ATM strategies and bundles under different demand/incident and weather
condition will be assessed
 Network-level
 O–D level
 Path level
 Outputs analysis simulation results
 Mobility
 Reliability
 Safety
 Sustainability

29. RESEARCH TASKS
 Review Additional Literature
 Data Collection Processing, Network Preparation and Calibration
 Scenarios’ Implementations and Simulation
 Performance Measures Estimation
 Draft Dissertation Preparation and Submission
 Final Dissertation Defense, Revision, and Submission
29
Schedule for Research Tasks

30. 30
THANK YOU
QUESTIONS