Geog 111A-211A Overview Fall 2006
Dec 21, 2015
Geog 111A-211A Overview
Fall 2006
Evolving Paradigm of Modeling and
Simulation
Dynamic Planning Practice
New Research and Technology
Sustainable and Green Visions
The Three Pillars
Note: Modeling and Simulation includes quantitative and qualitative nature
Recall Activity-based Example
Penn State Evacuation Model
• Sajjad Alam, MS, 1996(simplified model of the PennState campus life)
• Application for general planning, circulation plan, emergency operations, and special events
Used Activity Diary to Derive Time of Day Profiles
Personal needs (includes sleep)
Paid work
Education
Eat Meal
Travel
Activity Participation - Students
Activity Participation - Faculty
Activity Participation - Staff
Assembled
• Administrative records
• Building characteristics
• Developed attractiveness indicators (a gravity/distance model)
• A survey of activity participation
• A method to sequence activity participation
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Dynamic Presence on Campus
Combination of These Ideas = Centre SIM
(by J. Kuhnau, J. Eom, and M. Zekkos)• Build a network and facility information from
1997 to 2000• Use business/establishment data• Build and verify zonal system and information
therein• Expand Alam approach to the entire county• Identify major new developments and network
changes in 2000 to 2020• Provide a base model and validate it• No new data collection for Kuhnau – Eom and
Zekkos modify routines using new data
Simplified time of day activity-location-travel
Zone Presence and Travel Demand Output for Time Segment 8:00 – 9:00 AM
Zone Presence and Travel Demand Output for Time Segment 12:00 – 1:00 PM
Zone Presence and Travel Demand Output for Time Segment 4:00 – 5:00 PM
Zone Presence and Travel Demand Output for Time Segment 8:00 – 9:00 PM
More recent with Goods Movements (V/C)(Jinki Eom MS)
Many Models Like CentreSIM
Model Review• Completed a review of 49 activity-based
transportation models• Paradigms implemented (alone or in
combination):– Cellular Automata (TRANSIMS)– Constraint-based (AMOS, BSP, CARLA, FAMOS, FEATHERS)– Computational Process Model (ALBATROSS, SCHEDULER, TASHA)– Data-statistical Distributions (DEMOS, MORPC, ORIENT, TASHA)– Econometric Utility-based (CEMDAP, PCATS, STARCHILD, TASHA)– Framework (SCHEDULER, SMART)– Hazards Risk (COMRADE)– Microsimulation (ALBATROSS, CEMDAP, FAMOS, TRANSIMS)– Operations Research (HAPP)– Psychometric Cognitive (SCHEDULER, GISICAS)
Activity Model Behavioral UnitsDecision Makers
Groups Modeled
Unknown/ Unspecificed
WorkersCollege
StudentsAdults
Partial Households
Entire Households
Unknown/Unspecified
BSPPESASP(16 yrs +)
Individuals
Daily Activity Schedule,
Hayes-Roth & Hayes-Roth,
PCATS, SMART, Vause
Alam-PSEM, AMOS,
CATGW, COBRA
Alam-PSEM, COMRADE
AURORA, DATS/LATP, FEATHERS,
MASTIC, PATRICIA,
SIMAP, Synthetic Daily Activity-
Travel Patterns
Portland Daily Activity
Schedule(16 yrs +), Wen and
Koppelman (married couples)
CARLA, CentreSIM – regional, Ettema et al's (HCG),
GISICAS, HAPP, MORPC, New York "Best Practice", PETRA, RAMBLAS, San Francisco, SCHEDULER, SMASH, STARCHILD,
TRANSIMS
Households ALBATROSS
Adler and Ben-Akiva, CEMDAP, CentreSIM–
Medoid, DEMOS, FAMOS, ILUTE, MERLIN, MIDAS,
PUMA, TASHA
Specified Groups
ILUTE
WorkersKawakami and
Isobe
Homogenous Population Groups
ORIENTVISEM
(10 yrs +)
Model Temporal and Spatial ResolutionsSpatial
Resolution
Temporal Resolution
Unknown/ Unspecificed
None YearBlocks of
TimeHour
5 to 15 Minutes
MinuteSecond or
Continuous
Unknown/Unspecifie
d
BSP, Ettema (HCG), Hayes-
Roth, Kawakami and Isobe,
ORIENT, Wen and Koppelman
Starchild
None Vause, CATGW
Adler and Ben-Akiva, Daily Act.
Sch., PESASP,
SCHEDULER, SMART
MIDAS, DEMOS
CARLA, COBRA,
Synthetic Daily Activity-Travel
Patterns
HAPPCentreSIM - medoid
COMRADE, DATS/LATP
Region MERLIN
Zones AMOS PATRICIA
NYMTC, PCATS, PETRA, Portland, SFCTA
VISEM, CentreSIM - regional
TASHAMASTIC,
RAMBLASFAMOS
Sub-zones MORPC ALBATROSS,
AURORA. FEATHERS
Points SMASH Alam
PSEMSIMAP GISICAS
CEMDAP, ILUTE, PUMA, TRANSIMS
Evolving Paradigm of Modeling and
Simulation
Dynamic Planning Practice
New Research and Technology
Sustainable and Green Visions
Dynamic Planning Practice
• Dynamic thinking = time and change are intrinsic in the thought processes underlying planning activities.
• Strategic planning = set targets and find paths to achieve these targets
• Ecological thinking = we consider the overall anthropogenic system and nature
• Performance based planning = measurable targets and continuous evaluation
• Coherent modeling = we need information and guidance to plan, design, operate, manage, and maintain transportation systems
Dynamic Planning Components
• Inventory – envision as a dynamic map of entities and functions
• Strategy measurement and evaluation – targets and ways to make assessments
• Forecasting and Backcasting – travel from present to future and back
Inventory Issues
• Multiple levels
• Errors and error tolerance (policies, models, databases)
• Updates and cycles
• Merging data and information among different scales
Strategy measurement and evaluation
• Strategic Planning – set a target and the path to reach it – the usual vision, mission, goals, objectives, targets, measures, and update cycles
• Performance Based Planning – in essence means if you meet a goal you get funding continuation; otherwise…
A Federal Example• Federal Program Assessment Rating Tool (PART)• For individual programs from homeland security to education,
employment, and training. • Tailored analysis to each program (airport improvement, highway
planning and construction, fixed guideway modernization capital investments, and the federal transit formula grants and research).
• Yearly update and evaluation. • Uses 25 questions divided into sections to analyze:
– a) purpose and design of a program; – b) strategic planning and an agency’s ability to define outcome-oriented
yearly and longer term goals; – c) management and quality assurance; and – d) ability of a program to report accurately and consistently outcomes. – Tailored analysis yields summaries that receive a rating from 0 to 100
(0-49 is ineffective, 50-69 is adequate, 70-84 is moderately effective, and 84-100 is effective).
A State Example (MN)
Another State Example (CA)
PennPlan Moves! Pennsylvania Statewide Long Range
Transportation Plan
2000-2025
Moves Themes/Statewide Goals Matrix
GOALS
PUBLIC INPUT - MOVES THEMES
1. Promote safety of the transportation system. X
2. Improve the environment. X X
3. Retain jobs and expand economic opportunites. X X X
4. Make transportation decisions that support land use planningobjectives.
X X
5. Maintain, upgrade, and improve the transportation system. X X X X X
6. Inform and involve the public and improve customer service. X X
7. Advance regional and corridor-based planning. X X X
8. Develop transportation alternatives and manage demand. X X X X X
9. Promote smooth and easy connections between transportationalternatives.
X X X X
10. Ensure accessibility and mobility for everyone. X X X X
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PENNSYLVANIA STATEWIDE LONG RANGE TRANSPORTATION PLAN OBJECTIVES
Objective Performance Measure Target
16. Coordinate the development of a statewidemass transit strategic plan.
Development of a plan that includes both short-term(1 to 5 years) and long-term (6 to 25 years)objectives.
Plan completed by Dec. 31, 2001.
17. Increase urban and rural transitsystems' ridership.
Percentage increase in transit ridership, using 1997as the base year.
Ridership increased by:2003: 9% 2010: 16% 2020: 26%
18. Reduce dependence on single-occupancyvehicles.
Increase in vehicle occupancy rate (VOR). VOR increased by:2003: 5% 2010: 10% 2020: 20%
19. Eliminate at-grade crossings of freightlines by state-owned roads within strategic railcorridors.
Number of at-grade crossings of freight lines by state-owned roads within strategic rail corridors.
Such crossings eliminated by July 31, 2015.
20. Develop a statewide, passenger-rail needsassessment.
Completion of the assessment. Assessment completed by 2002.
21. Support the creation and expansion ofintermodal rail freight facilities that connect tothe National Highway System (NHS).
Access to NHS by intermodal rail freight facilites. Satisfactory access of all intermodal railfreight facilities to the NHS achieved by Dec.31, 2010.
22. Promote telecommuting as an alternativeto traditional work travel.
Increase in telecommuting as reported in nationalcensuses, with 2000 census as the base.
Telecommuting increased by:2010: 15% 2020: 22%
23. Connect all public-use airports to statetraffic routes or high-access transit systems.
Percent of public-use airports connected to statetraffic routes or high-access transit systems.
Public-use airports connected by:2003: 50%2008: 55%2013: 60%2018: 65%
24. Fully utilize the Pennsylvania InfrastructureBank's loan program as an innovativefinancing tool for transportation projectsthrough 2025.
Number of loans closed.
Positive cash balance through 2025.
Average of 6 loans per year closed through2025.
25. Maintain Pennsylvania's historical share ofthe annual federal transportation budget.
Pennsylvania's annual percentage share of the federaltransportation budget.
Annual share of 4.5 percent or highermaintained through 2025.
26. Reduce the number of state-maintainedroad miles.
Total turned-back miles. 100 road miles turned back annually.
Some Interesting questions• What types of consistency do we need among geographic scales
for planning and operations actions to perform evaluations?• Are there policy requirements for coordination among planning
activities to ensure consistency? • Are there suitable methods to coordinate smaller projects in
broader contexts (either of policy assessment or geographical area)?
• Do we have all the tools required to perform measurement of impacts and program evaluation at the newly defined assessment cycles?
• Which planning activity is better matched with which evaluation method?
• Are we excluding the randomized controlled experiments when we could perform them?
Dynamic Planning Components:Forecasting & Backcasting
• Forecasting = use the inventory and an evolutionary engine to create predictions of what will happen in the future
• Backcasting = envision a future and then work your way to the present and find out what needs to happen to make that vision reality
• Backcasting is not a simple reversal of time for forecasting – we cannot just reverse our dunamic models (non-linear in time)
An example of backcasting
Quist J. and P. J. Vergragt (2004) Backcasting for Industrial Transformations and System Innovations Towards Sustainability: Relevance for Government? In K. Jacob, M. Binder and A. Wieczorek (ds.) Governace for industrial Transformation. Proceedings of the 2003 Berlin Conference on the Human Dimensions of Global Environmental Chnage, Envirionmental Policy Research Centre: ber;i. Pp 409-437
• Forecasting is done by building scenarios• Microsimulation and synthetic population generation are
becoming popular• Activity-based approaches and inclusion of other
modeling facets (cars, houses, telecoms, human interactions) are happening
• BUT is backcasting and tool making for strategic planning happening?
• Any tools about performance based planning?
Some Interesting questions
Evolving Paradigm of Modeling and
Simulation
Dynamic Planning Practice
New Research and Technology
Sustainable and Green Visions
Sustainable and Green Visions
• Many of the travel behavior and operations models in conferences (TRB, IATBR) are motivated by these visions – decrease anthropogenic footprint on earth
• Also motivated by funds and mandates in legislation – see conformity
• Implies -> an ecosystem approach to analysis -> multiple scales and domains!
• Dedicate less time in this presentation
Policy examplesType of tool Brief description
Congestion pricing and toll collection programs A premium is charged to travelers that wish to travel during the most congested periods
Emission control, vehicle miles traveled, and other fee programs (including carbon taxes and trading)
Programs that shift taxation from traditional sources towards pollutant emissions and natural- resource depletion agents
Intelligent Transportation Systems (ITS) Use of telecommunications and information technology to manage, control, and provide information about the transportation system to travelers and managers.
Accelerated retirement of vehicles programs Programs to eliminate high emitting and older technology vehicles
Telecommunications to substitute/complement travel
The employment of telecommunications to substitute-complement-enhance travel
Land use growth and management programs Legislation that controls for the growth of cities in sustainable paths
Land use design and attention to neighborhood design for non-motorized travel
Similar to the previous but with attention paid to individual neighborhoods
Note: many more in a paper I will provide later
Ultimately We Want to Build Better Models for Assessment
PROPOLIS Example
Evolving Paradigm of Modeling and
Simulation
Dynamic Planning Practice
New Research and Technology
Sustainable and Green Visions
New Research and Technologies
• Tremendous progress in past 20 years in three areas:– Theory Building – Modeling and Simulation – Enabling Technologies
Theory Building
• Many competing paradigms
• Dynamics (change, time, agent evolution)
• Interactions considered in detail– Human-machine– Human-environment– Human-human
Modeling & Simulation
• Many options
• Micro-everything and aggregate up to whatever we need
• Evolutionary algorithms
• Econometrics/Statistics (e.g., latent variables)
• Soft Computing (e.g., data mining)
Last two can be considered a technology
Enabling Technologies
• Stochastic microsimulation • Production systems • Geographic information systems • Adaptive data collection techniques (think of
interactive computer experiments)• Dataloggers (GPS+Mobile
phone+envirosensors+who knows what else?)• Note: Computational capacity and speed are
already considered to keep galloping
Eiji Hato (U of Tokyo)Survey Methods
Behavioral Context Addressable Loggers in A Shell
Another Example
• RESEARCH UNIT ON SPATIAL COGNITION AND CHOICE
Wearable Device that allows to travel in unfamiliar environments
Uses GPS to track an individual moving through the real world, recording their trip as a trace in a spatial database (digital map) carried in a wearable computer. GIS functionalities calculate shortest paths between current location (fixed by the GPS) and a given destination (keyboarded or spoken). A choice of interfaces include spatial language, virtual beacons, an auditory virtual environment, or Talking Signs
The Evolving Paradigm and Some Questions
Requirements
• Policies dictate to create and test increasingly more sophisticated policy assessment instruments
• Account for direct and indirect effects of behavior, • Define procedures for behavioral change, and • Provide finer resolution in the four dimensions of
geographic space, time, social space, and jurisdictions.
• Dynamic planning needs:– Examination of trends, cycles, transitory and permanent impacts, – Invert the time progression and develop paths that lead to
visions about the future. • Model developments are becoming increasingly urgent.
Some examples of what is next ?
• More experimental settings needed for performance measurement– Is there a way we could develop guidelines for experimental and quasi-
experimental procedures to guide us in data collection?• Issues of scale in time and space – what is the right scale?• Coordination of model components – how?
• Error tolerance and their mapping to strategy evaluations • Lack models designed to be used in scenario building exercises
such as backcasting and related assessments. – Combine qualitative research methods with quantitaive techniques in
evaluations.– Invert time in current models and see what happens?
• In new research and technology - > – Consider perceptions of time and space. – Distinguish different time dimensions -> tempo, duration, and clock time – Human interaction
Thank you
• Questions?