Prepared for the Intelligent Transportation Systems Joint Program Office Research and Innovative Technology Administration United States Department of Transportation (USDOT) Federal Highway Administration (FHWA) Federal Transit Administration (FTA)

April 2010

Introduction

Passive interaction between fixed and mobile transportation system entities is rapidly giving way to a new paradigm of connected, interacting entities. This enables both new forms of data exchange and the opportunity to extend the geographic scope, nature, precision and latency of control within the transportation system. This opportunity to transform control of individual mobile or fixed entities as well as the connected system of mobile and fixed entities may have transformational impact on the capability of the transportation system to support individual mobility, system productivity and economic activity, while at the same time reducing environmental impacts and safety risks.

Through its connected vehicle research, the United States Department of Transportation (USDOT) is engaged in assessing applications that realize the full potential of connected vehicles, travelers and infrastructure to enhance current operational practices and transform future surface transportation systems management. Connected vehicle research is a collaborative initiative spanning the Intelligent Transportation Systems Joint Program Office (ITS JPO), Federal Highway Administration (FHWA), the Federal Transit Administration (FTA), and the Federal Motor Carrier Safety Administration (FMCSA).

One foundational element of connected vehicle technology is the Dynamic Mobility Applications Program.  Dynamic Mobility Application Program objectives include:

• Create applications exploiting frequently collected and rapidly disseminated multi-source data drawn from connected travelers, vehicles and infrastructure;
• Develop and assess applications showing potential to improve the nature, accuracy, precision and/or speed of dynamic decision making by both system managers and system users;
• Identify innovative forms of wireless connectivity linking travelers, vehicles and infrastructure supporting these new mobility applications; and
• Demonstrate applications predicted to improve the capability of the transportation system to provide safe, reliable, and secure movement of goods and people.
  

A successful Dynamic Mobility Applications program will lead to the more rapid and cost-effective deployment of interoperable technologies and applications that increase system efficiency and improve individual mobility.  The Dynamic Mobility Applications program will act to promote the highest levels of collaboration and cooperation in the research and development of transformative mobility applications.  Further, the program will seek to facilitate the highest level of free and open competition in the commercialization of mobility applications as well as their integration and maintenance.  The Dynamic Mobility Applications program positions the federal government to take on an appropriate and influential role as a technology steward for the continually evolving integrated transportation system.

One element of this stewardship is identifying and articulating a desired end-state for system operation and performance.  Further, the Dynamic Mobility Applications program will actively invest in open source research and development activities with the over-arching goal of maintaining a feasible evolutionary path from current technologies and practices to reach the desired end-state.  Without a Dynamic Mobility Applications program, the public and private sectors will bear higher costs of uncoordinated, proprietary and duplicative mobility applications research and testing, higher costs for the commercialization and integration of non-interoperable or proprietary technologies and control systems, and slowed progress towards a less desirable and ad hoc sub-optimal end-state.

Vision Statement

The vision of the connected vehicle Dynamic Mobility Applications program is to expedite the development, testing, commercialization, and deployment of innovative mobility applications, fully leveraging both new technologies and federal investment to transform transportation system management, to maximize the productivity of the system and enhance the mobility of individuals within the system.

Purpose

This purpose of this document is to describe the objectives, core concepts and projected outcomes of the connected vehicle Dynamic Mobility Applications Program.  In addition, the document serves to place the program in context with other ongoing or planned federal initiatives, and to provide an overview of planned activities and projected outcomes.

Core Concepts

This section presents a set of core concepts for the connected vehicle Dynamic Mobility Applications program.  These core concepts represent seven key guiding principles in program activities related to achieving the program vision.

#1 -- Leverage Multi-Source Data

The Dynamic Mobility Applications program seeks to fully leverage high-quality, integrated, multi-source data to support multiple applications.  In this regard, the Dynamic Mobility Applications program will coordinate closely with the Data Capture and Management program to identify promising mobility applications that have similar data needs.  Figure 1 illustrates how data from mobile and fixed sources are integrated and managed in a data environment under the Data Capture and Management program.  Data and information from this environment can be systematically extracted and used to support the set of identified applications.

Figure 1.  Multi-Source Data Supporting
Mode-Specific and Multi-Modal Applications

These applications may target specific modes (e.g., supporting freight vehicles automated safety checks) or may be multi-modal in nature (e.g., a traveler information service integrating tolling, transit and parking costs for pre-trip planning).  A subset of multi-modal applications, here termed cross-modal applications refers specifically to system management functions coordinating control between modes and jurisdictions.

Of particular importance to the program goal of best leveraging multi-source data is an assessment of the most appropriate methods of wireless connectivity linking vehicles, roadside infrastructure and mobile devices.  A communications infrastructure built on exploiting the capabilities of multiple technologies may provide the most efficient means of supporting a proposed portfolio of mode-specific and multi-modal mobility applications.

#2 -- Develop and Test Mode-Specific and Multi-Modal Applications

In addition to leveraging multi-source data to most cost-effectively develop and support applications, the applications themselves are coordinated to serve multiple end users (Figure 2).  This includes tailoring (with as little duplication of effort as possible) foundational elements like travel time calculation for different users, e.g., system managers, transit or freight fleet operators, or travelers moving among modes.  Applications development and testing will include assessment of multiple competing wireless communications approaches to assess best methods of achieving new forms of connectivity linking vehicles, roadside infrastructure, and mobile devices.

Figure 2. Coordinated Mobility Applications Development

#3 -- Feature Open Source Application Research and Development

The Dynamic Mobility Applications program seeks to promote the highest level of collaboration and preservation of intellectual capital generated from Dynamic Mobility Applications-funded efforts.  A key element in the Dynamic Mobility Applications vision facilitating this collaboration is the use of open source development approaches for all methods, algorithms, and source code developed in the Dynamic Mobility Applications program.  An open approach will also serve to engage partners from academia and industry who may not be directly involved in funded applications development and testing. Supporting an open source development environment for collaborating researchers requires both web-based tools as well as clear rules of engagement to support collaboration among Dynamic Mobility Applications-funded development activities.

#4 -- Encourage Competitive Application Commercialization

Research and development efforts cannot become isolated exercises either unrelated to user needs or without a clear path to eventual commercialization and broad deployment.  As indicated in Figure 3, the Dynamic Mobility Applications program will focus its resources and attention on basic research and development activities.  However, the program will structure these activities to clearly and fairly spur competitive application commercialization. Program research activities will be conducted in open data and open source development environments, as illustrated in Figure 3 as   bridging elements linking research and commercialization. All of the findings, software and algorithms developed as a part of the program will be broadly available as part of the technology transfer element of the program.  This wide provision seeks to engage the broadest range of public sector and private sector organizations.  While modifications to basic algorithms and source code must be returned to the development environment under open source licensing, applications based on software or algorithms developed in the Dynamic Mobility Applications program may be commercialized and marketed.  These activities underscore the Dynamic Mobility Applications program goal to encourage the adaptation and commercialization of applications derived from Dynamic Mobility Applications research efforts.

Figure 3. Cooperative Research and Development Facilitating Competitive Application Commercialization

#5 -- Prioritize Program Resources Based on Expected Impact

Applications developed under the banner of the Dynamic Mobility Applications program must clearly address improved system productivity or user mobility.  Well-defined, quantitative performance measures and a clear strategy for evaluating these impacts must be a part of any candidate application assessment.  Prioritization of program funding will be based on the demonstrated, predicted or expected impact on specific measures developed in the early phase of the program.  Preferred measures will be multi-modal or mode independent in nature.

In addition to potential impact, there must be stakeholder support and desire for these applications. Development of applications will be conducted collaboratively with stakeholders. This includes stakeholder engagement early in the program to identify candidate applications, cooperative development of application showing promising expected impacts with broad stakeholder support, and collaboration with industry partners in commercialization and deployment of proven applications.

A prototype mobility application developed early in the program will focus on the performance measures defined for the program.  This application will take advantage of new or integrated data sources to either enhance traditional measures or create new measures to better capture the full impact of mobility applications. Localized intersection control might routinely assess passenger-weighted intersection throughput against pre-determined target values.  Corridor or system-level controls integrating data from vehicles, travelers and local infrastructure control systems could characterize network-level mobility and productivity.  These routine assessments could be used to fine-tune control settings as well as measure improved mobility and productivity over time.  

#6 -- Enhance Analytic Capabilities Related to Mobility Applications

Another key aspect of the program will be to develop analytic tools and processes that accurately predict the impacts associated with mobility applications.  This includes both the capability to assess long-term performance of mobility applications and a capability to use real-time prediction to support improved decision making by travelers, system managers and other transportation system stakeholders.

Improved analytic capabilities will be critical in reducing the cost and time associated with developing new mobility applications.  The program intends to make full use of analytical tools to refine and identify promising applications prior to committing resources for field testing or full deployment.

#7 -- Practice Long-Term Technology Stewardship

Current technologies and real-time data collection can already provide researchers and system operators with significant amounts of data.  On the left side of Figure 4, this state is shown graphically by source – that is, a rough approximation of the extent of typical sources of traveler data (surveys), vehicle data (various probe technologies) and infrastructure data (sensor technologies).

One key question the program should attempt to answer is:  what is the capability of transformative mobility applications supported by a projected end-state data environment and an assumption of complete connectivity?  Based on Figure 4, we might conjecture a set of mobility applications supported in an end state where we capture and manage data from a sample of travelers, nearly all vehicles, and some key subset of the infrastructure. The five-year mobility applications program may not be able to realize applications supported by the end-state data environment, because the resources required to move from the current state to the end-state may be too large.  Further, the precise nature and benefits of the end-state are untested.

Figure 4. Data Supporting Interim and End-State Applications

To explore the potential of moving beyond current applications, however, the program will identify a collection of candidate mobility applications to be assessed in some interim test environments (Figure 4).  Data needs for these candidate mobility applications, together with data needs of other applications drawn from concurrent ITS programs (e.g., safety and environmental applications), will be assessed to develop a corresponding set of interim test environments. Once test environments can be realized, then one or more proof-of-concept applications tests can be conducted.  This assessment of promising applications and required data environments is a key element of the coordination of the Data Capture and Management Program, the Dynamic Mobility Applications Program, and the other applications-development programs.

Consider mobility applications enabled in the end-state data environment presented in Figure 4. We might conjecture that such a data environment might support a notion of freeway management based on the dynamic delivery of predictive travel time and tailored pricing data to individual vehicles operating in concert with discounts for strict or automated adherence to dynamic speed harmonization targets.  Transformative freeway management along these lines requires not only new forms of data, but the ability to communicate prices and speed targets to vehicles rapidly, as well as an analytical capability to rapidly optimize speed and pricing settings to maximize system productivity and mobility.  Further, this transformation must also be examined for potential safety and environmental impacts.

To explore moving in the direction of this transformative state of freeway control, however, the program will identify a collection of interim candidate applications (center of Figure 4), each of which is a prerequisite element in achieving the transformative freeway control system. Consider the current-state data environment presented in Figure 4. Combining vehicle flow data with the variation of segment or trip-level travel times, one might conjecture developing a performance measurement application that characterizes the overall economic productivity generated by a regional transportation system. In Figure 5, this relationship is shown between “Data Environment I” and this productivity-oriented performance measurement application.

Figure 5. Managed Mobility Application Evolution

Other useful applications may also be supported by Data Environment I. For example, one might develop an application that identifies point-to-point travel times for display on a variable message signs (VMS) that implicitly accounts for the impact the provision of the VMS messages will have
on future network flows and performance. In testing of the predictive VMS application, one might find that the application has significantly improved impact if particular traveler behavior data were systematically generated and captured (e.g., a profile of decisions made at diversion points downstream of the VMS).  These interim applications may provide insights on traveler diversion behavior critical to understanding how travelers react to the provision of more detailed and precise traveler information.

Now consider the end-state data environment presented in Figure 5. We might conjecture that such a data environment might support transformational notions of transportation system management. For example, one might propose operating a freeway system with dynamic optimized speed and flow targets for each lane.  To meet these targets, the system manager might consider lane-level pricing strategies with discounts for automated adherence to the changing optimal speed targets tailored by vehicle weight. In order to maximize overall economic productivity from the system, pricing policy may favor high-occupancy vehicles or transit vehicles with large passenger counts. Likewise, heavy vehicles might be provided with incentives to travel on particular lanes to improve flow and productivity. Dynamically grouping vehicles by size and weight may also reduce fuel consumption by reducing individual heavy vehicle wind resistance. Since the management system is highly complex and changes dynamically, roadway users of all types (from multi-modal travelers to transit agencies to shippers) would require frequently updated, highly accurate lane pricing and target speed data tailored to individual vehicles.  This form of freeway management may have significant benefits in improving mobility and system productivity without increasing roadway right of way.

In order to justify the investment to achieve this new state, we may use a range of analytical tools to show that managing freeway networks in this manner doubles the peak period productivity of the system (by eliminating breakdown) and transforms individual mobility by nearly eliminating the difference between planned and actual trip times.

Introducing new forms of control may not necessarily increase the centralization of control systems.  Some applications, for example transit signal priority, may be best deployed as a decentralized, locally optimized application.  Such a local application might combine precise predictions of pedestrian and vehicular location over time in an intersection with transit passenger count and schedule adherence data from transit vehicles approaching the intersection.  Considering these data, a local automated decision to adapt signal control to accommodate a specific transit vehicle might be made.  The altered signal plan is then communicated using two-way connectivity between the infrastructure and vehicles, including not only transit vehicles but all vehicles approaching the intersection. This example illustrates that new forms of control may exploit both new data and improved connectivity within the system.  However, the example also illustrates a consideration of an appropriate level of control and how systems that combine local, corridor and network-level controls perform.  In many cases, decentralized but coordinated systems can be cost-effective alternatives to centralized systems.

Program Phasing and Projected Outcomes

There is a clear federal role in leading a program to facilitate cost-effective and coordinated research on a variety of data-driven mobility applications of national interest.  Federal investment in this area will focus on conducting foundational research and development efforts, both on mobility applications themselves as well as analytical tools used to predict or estimate mobility impacts.  These research efforts are unlikely to be conducted without federal investment, and the costs and technical risks present a significant barrier to private investment and application development. One clear tenet of the program is to broadly share federally-funded foundational research.  These activities will be shared with the academic community and other partners to spur additional innovation.  Further, the program must engage the private sector to see new applications rapidly commercialized and readied for broad deployment.

Relationship to Other Connected Vehicle Research Program Areas

In addition to engaging these external stakeholders, the Dynamic Mobility Applications program must also coordinate with ongoing and planned connected vehicle program areas.

Data Capture and Management: The Dynamic Mobility Applications program will require strong coordination with the Data Capture and Management program.  The two programs must complement each other, as applications without data cannot function and data collected without an application has no purpose.  Program plans and roadmaps must consider this linkage in planning the development of test environments and the prioritization of applications and their attendant data needs.  To the extent that the two programs can identify promising applications with similar data environments, there will be significant leveraging of federal investment.

AERIS:  The AERIS program seeks to develop applications that will significantly reduce environmental impacts of mobility.  There will likely be some overlap between the two programs in terms of foundational elements needed to support applications.  For example, an application that predicts vehicular arrival time in an intersection tailored for vehicle weight and roadway surface conditions may be valuable for both transit signal priority applications as well as in-vehicle applications seeking to reduce fuel consumption approaching a predicted stop prior to the intersection.

Active Traffic Management (ATM):  The ATM program is a mode-specific research initiative at the Federal Highway Administration seeking to combine advanced lane management techniques with an overall strategy influencing demand management and route choice.  It is likely that mobility applications developed in the Dynamic Mobility Applications program can support the ATM vision, both in the provision of transformative control at the lane-level and the integration of data for system-level performance.

Smart Roadside/Border Crossing E-Screening: These two mode-specific freight research initiatives also offer opportunities for collaboration with the Dynamic Mobility Applications program.  The Border Crossing E-Screening effort will examine the use of wireless technologies to speed freight processing at border crossings.  Smart Roadside applications will enable targeted safety inspections to both improve safety compliance and speed freight movement.

Multi-Modal Integrated Payment Systems: This research effort considers a range of institutional, technical and operational issues regarding the development of a multi-modal, open architecture payment system.  This includes not only integrated transit fare collection but also dynamic road-user charges for non-transit vehicles.  Establishing a common platform for payment systems will be a key foundational element for mobility applications that consider financial incentives to efficiently distribute travel demand geographically across facilities and modes and temporally throughout the day.

Road Weather Management. The FHWA Road Weather Management has ongoing weather-related data capture and applications development efforts. For example, the Clarus initiative is a six-year effort to develop and demonstrate an integrated surface transportation weather observation data management system.  These ongoing efforts, along with upcoming planned initiatives, can be utilized to integrate the consideration of weather conditions into prospective mobility applications.

Other Connected Vehicle  Program Activities:  The Dynamic Mobility Applications Program will have strong connections with other connected vehicle program activities. For example, the Michigan Development Test Environment is likely to be a key test environment for selected applications.  The connected vehicle Systems Engineering effort will update the connected vehicle system architecture to accommodate new communications technologies and a range of in-vehicle devices.  These findings will influence the level of connectivity between entities within the test environments and the types of applications tested within the program.

Integrated Corridor Management (ICM):  The USDOT will be supporting two deployments of Integrated Corridor Management systems as a part of the demonstration phase of the ICM program.  The Dynamic Mobility Applications program can benefit from lessons learned in the ICM program on a number of issues, including integrating multi-source data, decision support systems, analytical methods, traveler information applications development and performance measurement.

Figure 6. Dynamic Mobility Applications High-Level Program Phasing Plan

Program Phasing

A high-level plan for the phasing of the Dynamic Mobility Applications program is shown in Figure 6. This figure shows the three primary phases of the program over time along the x-axis and program activity tracks along the y-axis.

The program begins with a Foundational Analysis phase lasting roughly 18 months.  In this phase, program activities will focus on identifying candidate applications and their associated data and communication needs.  A key point of coordination with the Data Capture and Management program will come at the end of this process when data needs will be mapped against potential data environments. At the same time these candidate applications are being considered, the program will deploy an open source development environment and prototype an open source application.  The prototype will serve as an example of how the open source development process is intended to operate during the course of the program.   The prototype application will include complete documentation, including a concept of operations, requirements, algorithmic documentation, and source code.  The foundational phase provides the opportunity to determine and refine the set the rules of engagement for open source development.  Another key element of the foundational phase is the determination of performance measures for the program that will assist in application development prioritization and to guide tool development in Phase 2.  Finally, the phase includes a near-term demonstration of applications leveraging multi-source data.
 
Phase 2 (Research, Development and Testing) begins with a refinement of the program plan based on the outputs and outcomes of the Foundational Analysis phase.  Prior to launching into any field testing, there is a decision point where the program must justify that the identified data environments and their supported applications are both relevant to the broader connected vehicle research program and that substantive research can be feasibly conducted within the phase.  In addition, before testing begins, wireless communication needs for connecting travelers, vehicles and infrastructure must also be clearly identified. In Figure 6, these elements of the Phase 2 decision gate are shown as three critical questions:

• “Do the candidate applications show enough promise to be tested?”
• “Do these applications address key performance measures?”
• “Do we understand the communications requirements of these applications?

If these questions can be satisfactorily answered, then Phase 2 proof-of-concept testing and tool development can be initiated. In this phase, promising applications will be tested using simulated or real test beds.  Some applications may be ready for field testing, while others will require additional development before field testing. In either case, the use of simulated test beds will be critical since it is unlikely that high levels of market penetration (e.g., 80% of vehicles) within a realistic operating environment will be equipped to support testing.  These simulated environments will assist in the assessment of whether or not specific applications can be expected to perform well in early deployment stages.  This phase is also a test for the open source development concepts pioneered in the foundational analysis phase.  The program will seek to engage public and private sector partners to develop additional applications beyond the scope of this effort or to seek innovations related to applications under development.   This phase also has a strong focus on the development of modeling tools and other analytic capabilities for the assessment of predicted benefits from wider application deployment.

If the results of the Phase 2 effort are encouraging enough to spark interest from deployment partners (drawn from both public and private sector) then the most promising applications will be considered for pilot deployment in Phase 3.  Figure 6 shows the Phase 3 decision gate dependent on the following question:

• “Are there clear and compelling arguments for deployment with significant benefits?”

In Phase 3, the program seeks to demonstrate applications showing significant promise in proof-of-concept testing.  These focused multi-modal demonstrations will integrate new applications into ongoing operational practice.  This phase has a strong focus on evaluation, with emphasis on utilizing the improved analytical tools to demonstrate productivity and mobility benefits.

The program is based on six basic tracks or activity areas. Stakeholder Interaction seeks to engage private and public sector partners to guide program activities.  Applications Development (Track 2) consists of three sub-tracks in Research and Development (Track 2A), Policy and Institutional Issues (Track 2B) and Standards (Track 2C).  Track 3 (Testing) entails planning and execution of both Phase 2 proof-of-concept testing and any additional testing required as a part of Phase 3.   Track 4 (Deployments) include both the near-term demonstrations planned in Phase 1 as well as pilot deployments conducted in Phase 3.  Track 5 covers performance measurement and program evaluation.  Outreach (Track 6) activities share the findings and products of the program with stakeholders and the public.

Summary of Projected Outcomes

A successful connected vehicle Dynamic Mobility Applications Program will be characterized by a number of outcomes, some related to the success of the program in developing new applications and attracting partners, others related to improvements in productivity and mobility related to the deployment of new applications.

• Multiple Applications Developed Leveraging Multi-source Data. The program successfully identifies and develops multiple mobility applications that combine new forms of data in real-time.  These applications demonstrate substantial promise in the improvement of system productivity and traveler mobility, as defined by a set of unambiguous performance measures.  Multiple organizations and partners are involved in applications development. Some of these participants are part of program-funded efforts, while others participate with funding from other sources to leverage the data, tools and development environment made available by the Dynamic Mobility Applications program. 
  
• Research Spurs Commercialization. Transparent mobility applications research and development efforts prompt private sector interest in commercializing these new applications and speed their deployment.  Careful treatment of intellectual property rights and collaborative development in an open source applications development environment chart a clear course for non-proprietary commercialization of applications.  Multiple commercialization efforts are underway, shortening the time from development to deployment for key mobility applications.
    
• Applications Enable Transformational Change. Tested and deployed applications demonstrate significant mobility and productivity benefit.  These benefits are evident in the field and supported by analysis from enhanced modeling and simulation tools.  These applications exploit new data sources and vehicle-traveler-infrastructure connectivity to provide cost-effective mobility solutions for individuals.  These individual mobility benefits manifest themselves at the system level in markedly increased system productivity.  As an increasing number of travelers and vehicles adopt new technologies, applications become more and more effective over time.  This natural evolution is underscored by an appropriate deployment of infrastructure-based controls to supplement and take advantage of increasing participation.

Next Steps

Key near-term steps in the development of the connected vehicle Dynamic Mobility Applications program include the continued refinement of the core concepts of the program.  This document is one part of a broader vision that will include a program charter and other materials that relate the objectives of the program as well as define roles and responsibilities for prospective program partners and stakeholders.  Further, this vision must be paired with a practical set of logically connected projects and program activities that provide a path to realizing the goals of the program.

To be successful, the Dynamic Mobility Applications program requires a high degree of coordination with other ITS programs.  This is not a one-time engagement but the beginning of an ongoing collaboration to refine data needs and structure relevant and feasible data environment development efforts. The success of the program also requires active interaction with stakeholders outside of the portfolio of federal research and development efforts.  To this end, the program must take advantage of opportunities in workshops or other venues to engage these stakeholders and motivate their participation and collaboration.

One key near-term step in the program is to go beyond just the refinement of program goals and program plans or collaboration with key stakeholders and federal programs.  In order to demonstrate the intent and promise of the Dynamic Mobility Applications program, a near-term objective will be to deploy an open source development environment and complete a prototype application.  This combination will demonstrate for prospective partners the advantages and responsibilities of working in collaboration with program initiatives.