3/13/2012
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The collection and archiving of existing and emerging data sources from all modes of transportation.  The data/information needs to be collected and stored for analyzing the effectiveness of strategies and responses generated by a DSS
The transformation of independent data streams into actionable decisions that impact multiple transportation modes across multiple jurisdictions. The actions need to be grounded in pre-arranged response plans for incidents and emergencies attached to contacts, roles and responsibilities.
The ability to impact overall network operations by sending commands/recommendations to individual systems in individual jurisdictions. The recommended actions seek to avoid gaps in response as well as contradictory responses, to produce benefit for total network operations.
While not a central objective, the provision of links to what has been termed passive IDTO will provide for the delivery of a greater quantity and quality of information to increasingly sophisticated system users, impacting their driving decisions The links to the delivery systems and the data that flows to them should be an integral part of the vision for IDTO.
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Transit Operations Decision Support Systems (TODSS)
.  The scan was used to develop the concept definition which identifies the situations and scenarios in which a multi-facility DSS tool could be expected to improve system performance.  The scan also includes lessons learned to date.  Literature research and telephone interviews with selected experienced agency staff contributed to this assessment.
Assessment of Emerging Opportunities for Real-Time, Multimodal Decision Support Systems in Transportation Operations. Concept Definition and Current Practice Report. Science Applications International Corporation, Report No. FHWA
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Tables-based DSS Systems (e.g. Toronto COMPASS, Georgia NaviGAtor, etc.).  These technologies and/or methodologies are data tables with predefined response plan recommendations and require little to no processing, modeling or analysis.  Some may include basic logic to analyze data in the tables while others are purely lookup tables.
Knowledge-Driven DSS, which includes:
Expert System DSS Systems (Caltrans ATMS, KC Scout, St Louis Gateway Guide, etc.).  This DSS requires an expert system engine to generate recommendations for response plans based on a set of pre-defined rules.
Custom Rules-based DSS Systems (ODOT Transport, GDOT NaviGAtor I, PACE TODSS).  Similar to the Expert System DSS, the Custom Rules DSS uses specific rules to determine response plans.  The difference is that the rules are custom built rather than having an expert system engine.
Event Scenario Matrix (Lake County Passage, Michigan ATMS, New Jersey ATMS, etc.).  Planned or unplanned events are identified on the roadway using map coordinates such as latitude/longitude or another plane coordinate systems and users are able to respond to the events using the predefined ITS field devices along the roadway.
Model-Driven DSS which incorporate on-line simulation tool integration (Singapore – Green LInk DEtermination (GLIDE) Traffic Control System, Madrid, Beijing, Milan).
Transit Operations Decision Support Systems (TODSS), Core Requirements Prototype Development Case Study, 2010 FTA-IL-26-7009-2009.1
Data Driven DSS, which is a form of support system that will focus on the provision of internal and sometimes external data to aid in the decision making.  Sometimes this comes in the form of a data warehouse, e.g. a database designed to store data in such a way as to allow for its querying and analysis by users.
Hybrids of the above.
Assessment of Emerging Opportunities for Real-Time, Multimodal Decision Support Systems in Transportation Operations.  Concept Definition and Current Practice Report. Science Applications International Corporation, report No FHWA
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The scan of current practice summarized the state of the current practice and concluded that there are few true “active” real-time multimodal decision support systems in the U.S. that account for all available modes of travel.  The closest systems to this goal are the under development, Integrated Corridor Management (ICM) Systems previously reviewed to be deployed in two locations: Dallas, Texas and San Diego, California.  Even with these latest developments in thinking, there is no uniform commitment to build a true multimodal decision support system.  There are a few cases which integrate two modes to some degree, e.g. incident management routing using both freeway and arterial routes.  One of the more interesting systems studied was the Chicago Metro area’s TODSS that uses external feeds of freeway and arterial data to implement operation rules for the Pace Suburban Bus System.  In some systems surveyed, there was no decision support system, but the elements to support such a system existed.
Most existing decision support systems discovered were associated with freeway management systems – from a lessons learned perspective, these deployments can be extrapolated to future multimodal systems.  Interesting lessons can be drawn from two non-freeway DSS systems reviewed: the Maintenance Decision Support System (IDTO) for winter weather mitigation and the transit-based TODSS referred to above.
Transit Operations Decision Support Systems (TODSS), Core Evaluation and Update Recommendations, 2010 FTA-IL-26-7009-2009.2
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Key Message: 
Time on Slide:
Suggest Comments:
Tables-based DSS Systems (e.g. Toronto COMPASS, Georgia NaviGAtor, etc.).  These technologies and/or methodologies are data tables with predefined response plan recommendations and require little to no processing, modeling or analysis.  Some may include basic logic to analyze data in the tables while others are purely lookup tables.
Knowledge-Driven DSS, which includes:
Expert System DSS Systems (Caltrans ATMS, KC Scout, St Louis Gateway Guide, etc.).  This DSS requires an expert system engine to generate recommendations for response plans based on a set of pre-defined rules.
Custom Rules-based DSS Systems (ODOT Transport, GDOT NaviGAtor I, PACE TODSS).  Similar to the Expert System DSS, the Custom Rules DSS uses specific rules to determine response plans.  The difference is that the rules are custom built rather than having an expert system engine.
Event Scenario Matrix (Lake County Passage, Michigan ATMS, New Jersey ATMS, etc.).  Planned or unplanned events are identified on the roadway using map coordinates such as latitude/longitude or another plane coordinate systems and users are able to respond to the events using the predefined ITS field devices along the roadway.
Model-Driven DSS which incorporate on-line simulation tool integration (Singapore – Green LInk DEtermination (GLIDE) Traffic Control System, Madrid, Beijing, Milan).
Transit Operations Decision Support Systems (TODSS), Core Requirements Prototype Development Case Study, 2010 FTA-IL-26-7009-2009.1
Data Driven DSS, which is a form of support system that will focus on the provision of internal and sometimes external data to aid in the decision making.  Sometimes this comes in the form of a data warehouse, e.g. a database designed to store data in such a way as to allow for its querying and analysis by users.
Hybrids of the above.
Assessment of Emerging Opportunities for Real-Time, Multimodal Decision Support Systems in Transportation Operations.  Concept Definition and Current Practice Report. Science Applications International Corporation, report No FHWA
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Key Message: 
Time on Slide:
Suggest Comments:
The scan of current practice summarized the state of the current practice and concluded that there are few true “active” real-time multimodal decision support systems in the U.S. that account for all available modes of travel.  The closest systems to this goal are the under development, Integrated Corridor Management (ICM) Systems previously reviewed to be deployed in two locations: Dallas, Texas and San Diego, California.  Even with these latest developments in thinking, there is no uniform commitment to build a true multimodal decision support system.  There are a few cases which integrate two modes to some degree, e.g. incident management routing using both freeway and arterial routes.  One of the more interesting systems studied was the Chicago Metro area’s TODSS that uses external feeds of freeway and arterial data to implement operation rules for the Pace Suburban Bus System.  In some systems surveyed, there was no decision support system, but the elements to support such a system existed.
Most existing decision support systems discovered were associated with freeway management systems – from a lessons learned perspective, these deployments can be extrapolated to future multimodal systems.  Interesting lessons can be drawn from two non-freeway DSS systems reviewed: the Maintenance Decision Support System (IDTO) for winter weather mitigation and the transit-based TODSS referred to above.
Transit Operations Decision Support Systems (TODSS), Core Evaluation and Update Recommendations, 2010 FTA-IL-26-7009-2009.2
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Key Message: 
Time on Slide:
Suggest Comments:
Tables-based DSS Systems (e.g. Toronto COMPASS, Georgia NaviGAtor, etc.).  These technologies and/or methodologies are data tables with predefined response plan recommendations and require little to no processing, modeling or analysis.  Some may include basic logic to analyze data in the tables while others are purely lookup tables.
Knowledge-Driven DSS, which includes:
Expert System DSS Systems (Caltrans ATMS, KC Scout, St Louis Gateway Guide, etc.).  This DSS requires an expert system engine to generate recommendations for response plans based on a set of pre-defined rules.
Custom Rules-based DSS Systems (ODOT Transport, GDOT NaviGAtor I, PACE TODSS).  Similar to the Expert System DSS, the Custom Rules DSS uses specific rules to determine response plans.  The difference is that the rules are custom built rather than having an expert system engine.
Event Scenario Matrix (Lake County Passage, Michigan ATMS, New Jersey ATMS, etc.).  Planned or unplanned events are identified on the roadway using map coordinates such as latitude/longitude or another plane coordinate systems and users are able to respond to the events using the predefined ITS field devices along the roadway.
Model-Driven DSS which incorporate on-line simulation tool integration (Singapore – Green LInk DEtermination (GLIDE) Traffic Control System, Madrid, Beijing, Milan).
Transit Operations Decision Support Systems (TODSS), Core Requirements Prototype Development Case Study, 2010 FTA-IL-26-7009-2009.1
Data Driven DSS, which is a form of support system that will focus on the provision of internal and sometimes external data to aid in the decision making.  Sometimes this comes in the form of a data warehouse, e.g. a database designed to store data in such a way as to allow for its querying and analysis by users.
Hybrids of the above.
Assessment of Emerging Opportunities for Real-Time, Multimodal Decision Support Systems in Transportation Operations.  Concept Definition and Current Practice Report. Science Applications International Corporation, report No FHWA
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Key Message: 
Time on Slide:
Suggest Comments:
The scan of current practice summarized the state of the current practice and concluded that there are few true “active” real-time multimodal decision support systems in the U.S. that account for all available modes of travel.  The closest systems to this goal are the under development, Integrated Corridor Management (ICM) Systems previously reviewed to be deployed in two locations: Dallas, Texas and San Diego, California.  Even with these latest developments in thinking, there is no uniform commitment to build a true multimodal decision support system.  There are a few cases which integrate two modes to some degree, e.g. incident management routing using both freeway and arterial routes.  One of the more interesting systems studied was the Chicago Metro area’s TODSS that uses external feeds of freeway and arterial data to implement operation rules for the Pace Suburban Bus System.  In some systems surveyed, there was no decision support system, but the elements to support such a system existed.
Most existing decision support systems discovered were associated with freeway management systems – from a lessons learned perspective, these deployments can be extrapolated to future multimodal systems.  Interesting lessons can be drawn from two non-freeway DSS systems reviewed: the Maintenance Decision Support System (IDTO) for winter weather mitigation and the transit-based TODSS referred to above.
Transit Operations Decision Support Systems (TODSS), Core Evaluation and Update Recommendations, 2010 FTA-IL-26-7009-2009.2
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The Concept of Operations (ConOps) is being used to document the intended purpose, goals and objectives and expected capabilities of a Multimodal Decision Support System. The purpose of the ConOps is:
1.To ensure that stakeholder needs and expectations are captured early;
2.To ensure that the implementation is linked to agency(ies) mission(s), goals, and objectives;
3.To identify existing operational environment and operations;
4.To identify where the IDTO could enhance existing operations/plans/functions;
5.To illustrate the future operational environment(s) with the IDTO, i.e. all of the functional parts that will be needed to operate; and,
6.To establish a list of high level operational requirements.
When systems engineering is applied to project development and implementation, the ConOps is normally grounded in a specific environment.  In this case, due to the foundational nature of this study, the ConOps is being developed as a generic application.  This could be viewed as a family of hypothetical systems.  However, to lend reality to the application(s) and fully engage stakeholder discussion and input, the ConOps will be developed around four scenarios that reflect real world conditions but are not based on specific locations.  The scenarios will be used to illustrate the potential variants of the concept.
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The deployment of decision support systems multi-modal or otherwise is currently frequently limited by many factors.  The following are examples that have been encountered:
Limitations in data provided by one or more modes of transportation – typically arterial data is a limiting factor but lack of full integration of field element systems also contributes to the problems, as does partial data for transit systems
Communications network limitations i.e. interfaces are lacking between mode specific systems
Lack of standardization of data flows- implementation of standards such as TMDD and others support the way forward but have yet to be fully deployed
Shortages in properly-trained personnel
Data gaps caused by underfunded system maintenance
Reluctance of certain modal operators to trust the control results of DSS and inability to fine tune to suit their preferences and experience
Inherent limitations of certain transportation modes, e.g. city TMC’s not monitored on a continuous basis, legacy signal systems which cannot be monitored or manipulated automatically, rail and transit information not fully and accurately available in real-time, public safety systems using different protocols.
Lack of stakeholder organization and awareness – the Integrated Corridor Management Pilot programs expose the need and extent of cooperation needed
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The deployment of decision support systems multi-modal or otherwise is currently frequently limited by many factors.  The following are examples that have been encountered:
Limitations in data provided by one or more modes of transportation – typically arterial data is a limiting factor but lack of full integration of field element systems also contributes to the problems, as does partial data for transit systems
Communications network limitations i.e. interfaces are lacking between mode specific systems
Lack of standardization of data flows- implementation of standards such as TMDD and others support the way forward but have yet to be fully deployed
Shortages in properly-trained personnel
Data gaps caused by underfunded system maintenance
Reluctance of certain modal operators to trust the control results of DSS and inability to fine tune to suit their preferences and experience
Inherent limitations of certain transportation modes, e.g. city TMC’s not monitored on a continuous basis, legacy signal systems which cannot be monitored or manipulated automatically, rail and transit information not fully and accurately available in real-time, public safety systems using different protocols.
Lack of stakeholder organization and awareness – the Integrated Corridor Management Pilot programs expose the need and extent of cooperation needed
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Automated incident detection, assessment, forecasting, traveler information and audits.  This capability would be used to influence service patrol operations, the installation of automated surveillance equipment and traffic control strategies.
Decision support tools that can provide the capability of rapidly evaluating the impact of alternative incident response measures including diversion routes.  This tool is likely to include a suite of faster-than-real-time simulation techniques that will permit the modeling of the impact of the impact of the incident response alternatives.
Provide data needed to automatically modify ramp metering rates and traffic signal timing in the presence of an incident.
Software that records Transportation Operations Center (TOC) operator’s actions during incidents for subsequent evaluation and use in response to similar incidents.
The audit reference in this context refers to performance measures
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Automated incident detection, assessment, forecasting, traveler information and audits.  This capability would be used to influence service patrol operations, the installation of automated surveillance equipment and traffic control strategies.
Decision support tools that can provide the capability of rapidly evaluating the impact of alternative incident response measures including diversion routes.  This tool is likely to include a suite of faster-than-real-time simulation techniques that will permit the modeling of the impact of the impact of the incident response alternatives.
Provide data needed to automatically modify ramp metering rates and traffic signal timing in the presence of an incident.
Software that records Transportation Operations Center (TOC) operator’s actions during incidents for subsequent evaluation and use in response to similar incidents.
The audit reference in this context refers to performance measures
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Key Message: 
Time on Slide:
Suggest Comments:
Automated incident detection, assessment, forecasting, traveler information and audits.  This capability would be used to influence service patrol operations, the installation of automated surveillance equipment and traffic control strategies.
Decision support tools that can provide the capability of rapidly evaluating the impact of alternative incident response measures including diversion routes.  This tool is likely to include a suite of faster-than-real-time simulation techniques that will permit the modeling of the impact of the impact of the incident response alternatives.
Provide data needed to automatically modify ramp metering rates and traffic signal timing in the presence of an incident.
Software that records Transportation Operations Center (TOC) operator’s actions during incidents for subsequent evaluation and use in response to similar incidents.
The audit reference in this context refers to performance measures
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In order to implement true real-time IDTO, the following changes must occur.  Note that these changes represent those that typically would be needed, but all of these items may not necessarily be required in all deployment locations or scenarios.
Establish Information Sharing System - Independent agency systems would need to begin freely exchanging information among one another, in real time, following standard data exchange methodologies, e.g. following NTCIP C2C guidelines, TMDD, etc.  The information exchange should allow for recommendation of decision support responses to agency systems, potentially including the direct control of field traffic management assets.
Implementation of a Region-wide Communications Network - To collect sufficient data and to enable the regional transportation network, a relatively high-bandwidth communications network is a prerequisite. The network may be provided by the Internet, a common carrier or be agency-owned infrastructure, but is necessary to move data and imagery between management centers.  The Internet is increasingly becoming the network of choice for many transportation applications.
Create Multimodal Historical Database - Containing road condition data, regional ITS configuration data, response plan information etc.  Most regions have legacy data repositories in existing freeway, arterial and transit management systems.  Integrating different data sets and formats is a technical challenge that must be overcome to effectively implement a multi-modal DSS.
Enable/Create Common Operating Picture (COP) - To effectively implement IDTO, the ability of multiple agencies to see data from individual modal management systems on a common geo-referenced visual display (large screen wall, desktop workstation, mobile device) is desired.  The COP can be tailored to the needs of the transportation system manager to only show data layers needed for effective decision support.
Visualization Platform - In order to effectively evaluate IDTO recommendations, a method of visualizing transportation network conditions, response plans and generated actions is preferred.
True System Interoperability - Interoperability will be a key element in the regional integration of Decision Support Systems.  Two key standards for both collecting data and sending control commands are the Transportation Management Data Dictionary, Version 3.0 and J2735.  These standards will be implemented in the Dallas and San Diego Integrated Corridor Management Systems, which are expected to be leaders in the development of newer generation DSS systems.  Also to be taken into account for interoperability will be the NTCIP device communications standards.
Improved Logistical Support - As with any other ITS technology, DSS implementation must be carried out using solid system engineering principles with due attention paid to logistical support requirements. These include proper documentation, operator selection and training, an Operations and Maintenance Plan and ongoing configuration management, both at the system and operational levels.
On-line Modeling Capabilities - To enhance the capability to analyze strategies, perform complex data calculation in real-time and in certain cases enable predictive capabilities.  On-line modeling tools can be an effective way to perform such functions and in turn are desired for IDTO deployments, although not necessary strictly required.
Predictive Tools - The new genre of intelligent transportation management looks toward managing by anticipation rather than reaction, i.e., attempting to predict adverse or negative conditions and then preventing them from occurring or at least lessening their effects.  For these reasons, implementation of real-time or faster than real-time predictive tools are desired for IDTO to continuously provide anticipated network conditions up to 60 minutes in advance.
Develop a Workflow Engine - The IDTO requires a workflow engine that replicates modal management workflows.  The workflow engine is envisaged as the tracking and sequencing mechanism for what happens when recommended actions are issued.  It will track recommendations and feedback into the recommendation process, e.g. freeway ramp signal timings may have been changed but a city has not responded by making requested arterial timing changes leading to serious queues.  The engine will be designed to follow the sequence of events and present modifications.
Create Centralized Rules-Based DSS Engine - At the nucleus of the IDTO is a rules-based IDTO engine that links or uses many of the components outlined above.  This engine is envisioned to be an interactive, software-based system that extracts useful information from a combination of modal data sources and knowledge bases (operational rules) and converts these into actions and/or recommendations that influence performance of the transportation network, based on specific rules entered into the engine database.
Create/Train Multimodal Operators – A training program is needed for existing system operators or new “Multimodal Operators” on how to manage systems across systems and jurisdictions taking all modes into account
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Key Message: 
Time on Slide:
Suggest Comments:
In order to implement true real-time IDTO, the following changes must occur.  Note that these changes represent those that typically would be needed, but all of these items may not necessarily be required in all deployment locations or scenarios.
Establish Information Sharing System - Independent agency systems would need to begin freely exchanging information among one another, in real time, following standard data exchange methodologies, e.g. following NTCIP C2C guidelines, TMDD, etc.  The information exchange should allow for recommendation of decision support responses to agency systems, potentially including the direct control of field traffic management assets.
Implementation of a Region-wide Communications Network - To collect sufficient data and to enable the regional transportation network, a relatively high-bandwidth communications network is a prerequisite. The network may be provided by the Internet, a common carrier or be agency-owned infrastructure, but is necessary to move data and imagery between management centers.  The Internet is increasingly becoming the network of choice for many transportation applications.
Create Multimodal Historical Database - Containing road condition data, regional ITS configuration data, response plan information etc.  Most regions have legacy data repositories in existing freeway, arterial and transit management systems.  Integrating different data sets and formats is a technical challenge that must be overcome to effectively implement a multi-modal DSS.
Enable/Create Common Operating Picture (COP) - To effectively implement IDTO, the ability of multiple agencies to see data from individual modal management systems on a common geo-referenced visual display (large screen wall, desktop workstation, mobile device) is desired.  The COP can be tailored to the needs of the transportation system manager to only show data layers needed for effective decision support.
Visualization Platform - In order to effectively evaluate IDTO recommendations, a method of visualizing transportation network conditions, response plans and generated actions is preferred.
True System Interoperability - Interoperability will be a key element in the regional integration of Decision Support Systems.  Two key standards for both collecting data and sending control commands are the Transportation Management Data Dictionary, Version 3.0 and J2735.  These standards will be implemented in the Dallas and San Diego Integrated Corridor Management Systems, which are expected to be leaders in the development of newer generation DSS systems.  Also to be taken into account for interoperability will be the NTCIP device communications standards.
Improved Logistical Support - As with any other ITS technology, DSS implementation must be carried out using solid system engineering principles with due attention paid to logistical support requirements. These include proper documentation, operator selection and training, an Operations and Maintenance Plan and ongoing configuration management, both at the system and operational levels.
On-line Modeling Capabilities - To enhance the capability to analyze strategies, perform complex data calculation in real-time and in certain cases enable predictive capabilities.  On-line modeling tools can be an effective way to perform such functions and in turn are desired for IDTO deployments, although not necessary strictly required.
Predictive Tools - The new genre of intelligent transportation management looks toward managing by anticipation rather than reaction, i.e., attempting to predict adverse or negative conditions and then preventing them from occurring or at least lessening their effects.  For these reasons, implementation of real-time or faster than real-time predictive tools are desired for IDTO to continuously provide anticipated network conditions up to 60 minutes in advance.
Develop a Workflow Engine - The IDTO requires a workflow engine that replicates modal management workflows.  The workflow engine is envisaged as the tracking and sequencing mechanism for what happens when recommended actions are issued.  It will track recommendations and feedback into the recommendation process, e.g. freeway ramp signal timings may have been changed but a city has not responded by making requested arterial timing changes leading to serious queues.  The engine will be designed to follow the sequence of events and present modifications.
Create Centralized Rules-Based DSS Engine - At the nucleus of the IDTO is a rules-based IDTO engine that links or uses many of the components outlined above.  This engine is envisioned to be an interactive, software-based system that extracts useful information from a combination of modal data sources and knowledge bases (operational rules) and converts these into actions and/or recommendations that influence performance of the transportation network, based on specific rules entered into the engine database.
Create/Train Multimodal Operators – A training program is needed for existing system operators or new “Multimodal Operators” on how to manage systems across systems and jurisdictions taking all modes into account
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Key Message: 
Time on Slide:
Suggest Comments:
In order to implement true real-time IDTO, the following changes must occur.  Note that these changes represent those that typically would be needed, but all of these items may not necessarily be required in all deployment locations or scenarios.
Establish Information Sharing System - Independent agency systems would need to begin freely exchanging information among one another, in real time, following standard data exchange methodologies, e.g. following NTCIP C2C guidelines, TMDD, etc.  The information exchange should allow for recommendation of decision support responses to agency systems, potentially including the direct control of field traffic management assets.
Implementation of a Region-wide Communications Network - To collect sufficient data and to enable the regional transportation network, a relatively high-bandwidth communications network is a prerequisite. The network may be provided by the Internet, a common carrier or be agency-owned infrastructure, but is necessary to move data and imagery between management centers.  The Internet is increasingly becoming the network of choice for many transportation applications.
Create Multimodal Historical Database - Containing road condition data, regional ITS configuration data, response plan information etc.  Most regions have legacy data repositories in existing freeway, arterial and transit management systems.  Integrating different data sets and formats is a technical challenge that must be overcome to effectively implement a multi-modal DSS.
Enable/Create Common Operating Picture (COP) - To effectively implement IDTO, the ability of multiple agencies to see data from individual modal management systems on a common geo-referenced visual display (large screen wall, desktop workstation, mobile device) is desired.  The COP can be tailored to the needs of the transportation system manager to only show data layers needed for effective decision support.
Visualization Platform - In order to effectively evaluate IDTO recommendations, a method of visualizing transportation network conditions, response plans and generated actions is preferred.
True System Interoperability - Interoperability will be a key element in the regional integration of Decision Support Systems.  Two key standards for both collecting data and sending control commands are the Transportation Management Data Dictionary, Version 3.0 and J2735.  These standards will be implemented in the Dallas and San Diego Integrated Corridor Management Systems, which are expected to be leaders in the development of newer generation DSS systems.  Also to be taken into account for interoperability will be the NTCIP device communications standards.
Improved Logistical Support - As with any other ITS technology, DSS implementation must be carried out using solid system engineering principles with due attention paid to logistical support requirements. These include proper documentation, operator selection and training, an Operations and Maintenance Plan and ongoing configuration management, both at the system and operational levels.
On-line Modeling Capabilities - To enhance the capability to analyze strategies, perform complex data calculation in real-time and in certain cases enable predictive capabilities.  On-line modeling tools can be an effective way to perform such functions and in turn are desired for IDTO deployments, although not necessary strictly required.
Predictive Tools - The new genre of intelligent transportation management looks toward managing by anticipation rather than reaction, i.e., attempting to predict adverse or negative conditions and then preventing them from occurring or at least lessening their effects.  For these reasons, implementation of real-time or faster than real-time predictive tools are desired for IDTO to continuously provide anticipated network conditions up to 60 minutes in advance.
Develop a Workflow Engine - The IDTO requires a workflow engine that replicates modal management workflows.  The workflow engine is envisaged as the tracking and sequencing mechanism for what happens when recommended actions are issued.  It will track recommendations and feedback into the recommendation process, e.g. freeway ramp signal timings may have been changed but a city has not responded by making requested arterial timing changes leading to serious queues.  The engine will be designed to follow the sequence of events and present modifications.
Create Centralized Rules-Based DSS Engine - At the nucleus of the IDTO is a rules-based IDTO engine that links or uses many of the components outlined above.  This engine is envisioned to be an interactive, software-based system that extracts useful information from a combination of modal data sources and knowledge bases (operational rules) and converts these into actions and/or recommendations that influence performance of the transportation network, based on specific rules entered into the engine database.
Create/Train Multimodal Operators – A training program is needed for existing system operators or new “Multimodal Operators” on how to manage systems across systems and jurisdictions taking all modes into account
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There are still two remaining questions to answer:
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There are still two remaining questions to answer:
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There are still two remaining questions to answer:
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Diagram System Information:  Subsystems and information flow worksheets will help to define inputs and outputs needed by IDTO… this will pay directly into the roles and responsibilities.  Suggest doing the diagram input/outputs first in the groups. 
Transactions Set Diagrams:  Consider order of events and if certain transactions must occur before others.. If so, document that on this diagram.
Roles and Responsibilities:  There has been some discussion about whether we need one chart for “roles and responsibilities for IDTO or one for each scenario”.  Today as we work through the breakout groups while we more clearly define roles of different agencies we hope to also consider shortcomings in the current system that a DSS could improve and identify constraints that a DSS has to work around.
Gaps and Comments What subsystems, communications/data/information flows, role and responsibilities currently ARE MISSING in order for a IDTO to function to exist.  what 
Changes to Needs:
Do this last… Using the needs worksheet, document any changes to the needs identified.
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Recommend that they use yellow post it pads to add subsystems and information flows until they complete discussions and are sure they want to add the subsystem.  Once the group agrees to add it – the facilitator or assistant should add it with a marker.
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Key Message:  Introduce Scenario #1
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Scenario #1: Overall System Diagram: Single transit provider operating multiple modes with the same on-board systems and data communications systems; If a trip cannot be met on public transportation, it is sent to a private mode.  Assumptions: CAD/AVL and on-board systems; Data and voice communications; New or modified Scheduling System; New or modified Customer Messaging System
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Scenario #1: Overall System Diagram: Single transit operator; multi-modal; trip denials sent to private mode.  Assumptions: CAD/AVL and on-board systems; Data and voice communications; New or modified Scheduling System; New or modified Customer Messaging System
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Scenario #2: Overall System Diagram with multiple providers operating in a multimodal environment; if a trip can’t be made on public transportation, it is sent to private mode; Different providers may use a different CAD/AVL system.  Assumptions:  CAD/AVL and on-board equipment; interface necessary for location data and messaging to vehicles.
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((( how to “neutralize” messages back to different CAD/AVL systems)))
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Assumptions:  Vehicles have on-board systems including CAD/AVL; Mobile Data Terminals; Data Communications (Voice for back up);  Vehicle operates anywhere (demand response, or cab service)  Shared ride or not?
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Key Message:  Transition into Scenario 3
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