Examples of Advanced Transportation Projects
The Federal Role and the Future of ITS
Acknowledgments
Bibliography
Click here for the chapter home page.
Stephen J. Bespalko, John H. Ganter, and Marsha D. Van Meter
In his chapter, "Common Policy Concerns," Stephen Lukasik
points out:
Thus, while traffic and vehicles are a central concern of ITS, information is the central concern of the NII. The overlap of ITS and NII arises because traffic, in and of itself, constitutes a form of information, and information of a wide variety is needed by travelers. As its name implies, ITS is a set of transportation systems, whereas the NII refers to an information system infrastructure within which those transportation systems operate.
To take this idea a step further, ITS systems as well as systems designers require a wide variety of information to make their projects powerful and effective. This chapter begins by discussing specific examples of how the current information components of transportation systems are insufficient for advanced applications, such as ITS. The projects discussed in this chapter demonstrate that transportation technology can be hampered by lack of adequate spatial data.
Spatial data is an essential component of transportation infrastructure.
Currently, however, it falls outside the scope of either the NII
or the ITS. Given that all of the systems examined here are either
impossible to deploy without better spatial data, or have been
designed to compensate for a lack of spatial data, it is clear
that the designers are doing the best they can with the technology
and information at their disposal. If ITS goals are to be achieved,
there is a need for a strong federal role in developing a national
system for gathering and maintaining up-to-date geospatial data.
[Back to Outline]
Transportation research and development at Sandia National Laboratories has been primarily technical in nature, involving computation, high-volume spatial data management, and communications as applied to the management of vehicle fleets carrying special cargoes. Recently, it has included a project to design and prototype a "next-generation" Geographic Information System (GIS) that can manage both historical and new data sources and forms. The intent of this project is to provide the information technology needed to support the spatial data infrastructure that advanced transportation projects require.
Briefly, a Geographic Information System is a relational database manager specialized for handling spatial data. In a Relational Database Management System (RDBMS), information is stored in tables that are linked in an intuitive way. GIS products tend to be an additional layer "on top" of a commercial RDBMS. The GIS then provides applications programmers with operations useful for analysis on the spatial data stored in the underlying RDBMS. One example would be the ability to define basic graphic entities common in spatial analysis and to manage the storage and retrieval of these entities, which are referred to as points, lines, and polygons. Another example would be the ability to compute the areas of geographic features stored as polygons.
Two issues presented here are the need for vastly improved digital maps, or "representations" of the surface transportation infrastructure, and the relative abilities of public and private entities to create and maintain such representations. These issues are illustrated with examples of current and anticipated advanced transportation projects that would benefit from, or clearly require, considerably better data than is currently available from public entities, which are usually state departments of transportation.
Defining "improved data" is central to the arguments presented here. The current body of spatial data used for transportation applications is for the most part, digitized (or computerized) two-dimensional maps. At typical scales, buildings are represented by dots, squares, or occasionally groups of lines. Roads are typically represented by a single line or possibly polygons. The roads are then differentiated with various attributes such as state or federal designations, direction, or road type. From these data, simple maps can be generated that display the attributes with symbology such as color, shape, and pattern.
Sandia's work to implement a prototype of the next-generation computer system to manage spatial information indicates that this two-dimensional digital map metaphor is inadequate for many applications. More specifically, applications, including those defined by the ITS program, could be greatly improved with a three-dimensional, object-oriented model.
Because today's GIS systems grew from attempts at automating maps, current GIS data models begin with one or more two-dimensional coordinates. Abstract map elements like buildings or roads are constructed by adding descriptive attributes such as color or line thickness to sets coordinates. Programming these systems is awkward and error-prone because users are primarily interested in manipulating these abstract entities. The ability to define abstract objects such as roads would benefit the programs by permitting them to manipulate complex geographic features, thus making the programs more robust and easier to write.
For example, transportation applications programmers would benefit greatly from the ability to define an object called a "road." This object could include many properties useful to transportation systems designers. One of these properties is how the road is rendered on a two-dimensional map at a particular scale; another includes the detailed path the road follows on the surface of the earth. Most of the advantages of Sandia's intended design follow from either the inclusion of the third dimension of data, or from the object orientation of the software we will use to program the system.
Three-dimensional data models represent driveable areas as thin articulated surfaces. Such linear surfaces would be coaxial and branching. For instance, two side-by-side "ribbons" would represent two lanes, and at some point additional lane(s) or ribbons would branch off. Other ribbons would run above or below to represent bridges, underpasses, etc. So by "three-dimensional object-oriented representation" we mean a representation that is neither a single surface nor a volume, but one that is suited to the unique geometries (shapes) and topologies (connections) of transportation infrastructure.
Who will design, construct, and maintain these new data representations? Many of the state Departments of Transportation (DOTs) and regional organizations (county and city governments, metropolitan planning organizations [MPOs]) are far behind other organizations (both public and private) with respect to being part of the "information revolution." Paradoxically, entities that build and maintain infrastructure for their constituents are the logical "owners" of representations, but often the least able to take on this responsibility due to fiscal limitations and short-term political pressures. Bringing these organizations into the ITS realm as both promoters and users of this advanced technology is therefore critical to the overall success of the advanced transportation program in general.
This raises important policy issues. Foremost, whose interest is being served by investing in technology (e.g., increasingly elaborate spatial referencing schemes) that will clearly be suboptimal in the near future? Too often, transportation systems designers go out of their way to use low-accuracy data because it is easy and cheap to acquire. Instead, it is possible to build ITS and other advanced transportation systems with the same basic CAD data used for designing the roads.
The remainder of this chapter will be divided into four sections.
The first section will cover some of the background of how the
spatial data evolved into the current technology. The second section
will explain the data requirements of the typical state DOT in
more detail; this will be the basis of subsequent discussion of
the alternatives for promoting the state DOT participation in
advanced transportation initiatives. We will also describe the
recent Pooled Fund Study, which was the method used by the states
to create a common technical strategy for adopting the federally
mandated ISTEA systems. Although considerably less ambitious than
the advanced transportation projects described in this chapter,
the Pooled Fund Study is a good example of how federal transportation
policy can be used to stimulate significant technological change
at the state level. Third, we will describe several advanced transportation
projects, paying particular attention to data requirements. The
last section discusses the implications of these new technologies
for the advanced transportation projects. We will conclude by
considering the opportunities for federal policy intervention
to influence the introduction of new ITS technologies. [Back to Outline]
Background: Transportation Geospatial Data at
Local and State Levels
Geographic Information Systems for Transportation
(GIS-T)
State DOTs have varied histories, which helps to explain the very different spatial information systems that have evolved in each. Because information systems (IS) is a relatively new discipline with few formal methods, particular systems almost always reflect the personalities of those who have founded and developed them. Thus, state DOTs and similar regional organizations have different hardware, software, data formats, data structures, spatial references, etc., sometimes within the same agencies.
Nonetheless, most state agencies utilize data management systems specialized for managing spatial data, a technology known as ìgeographic information systems for transportation" (GIS-T). GIST supports specific applications such as corridor planning, property valuation and condemnation, environmental impact analysis, and a variety of permitting. GIS-T systems are also used for regional transportation planning, where census data are used to develop growth projections and predictions of commuter traffic.
To understand the flow of information within a typical state agency (and ultimately why the states will have a difficult time supplying the data needed for advanced transportation systems), let us consider the information used to design and build a road. First, planners use GIS-T to determine the rough outline of the road corridor. Next, they use it to supply rough outlines to computer-aided design (CAD) systems in the engineer's office. CAD then creates detailed, multidimensional models in which volumes of cut-and-fill, pitches of drains to carry off rainwater, and similar minutiae are designed and tested 'before any concrete is poured.
At this point the "flow" of data and information begins to divide and disintegrate as drawings and plans are lost or rendered useless; this is because deviations from these plans are mandated by information discovered during construction. The GIS-T and CAD systems are now used to produce large paper plans that are carried into the trailers where construction is overseen. When construction begins, plans are marked up and modified. Later, "as-built" drawings, which are themselves often lost as they become construction afterthoughts, are created to capture the final configuration for future maintenance efforts. The roadway goes into operation with a loose or non-existent connection to its past design (where underground utility lines run, what concrete batches went where) and its future (traffic volume counts for lanes).
GIS-T thus tends to be employed as a short-term operational tool, rather than a long-term, cradle-to-grave management system. It is typically comprised of data of varying scales, collection methods, and lineages. "Metadata" (data describing data) that quantify and track the collection over time seldom exist. The highway begins to age like a car whose owner's manual and service log have been discarded. Just as unfortunate, the very information that is lost would enable many of the advanced transportation projects discussed later in this chapter.
Engineers use high-quality data to design highways. However, most
subsequent business applications tend to use the least amount
of data possible (and often degrade existing data) to achieve
short-term goals. When viewed from a global or enterprise perspective,
or from the standpoint of implementing ITS, this is clearly a
costly and technically unnecessary approach. [Back to Outline]
The maintenance and operational groups in state DOTs have become adept at using the low-resolution, and usually inaccurate, data that are made available to them. In fact, most if not all of the state DOTs have developed methods that reduce their information requirements to one -dimensional data. This is done through a method called linear referencing.
In linear referencing, the locations of features are established in "odometer space" relative to some starting point. An example would be: "The lane extends from 8.2 miles to 8.7 miles west along Rt. 7, based on a starting point at Rt. 7 and Rt. 4.', As this example suggests, an intersection is a typical starting point, but problems can arise with consistency and ambiguity; e.g. which side of an intersection is the starting point, determining consistent names for intersections, etc. Even if milepost or other markers are installed, a change in the highway can invalidate the system.
Linear referencing alone will not serve more sophisticated transportation systems such as those defined for ITS. In addition, individual states probably will not benefit fully, at least in the short term, from more powerful location referencing systems (such as GPS) if they continue to focus on linear referencing. Therefore, it is doubtful that the states will see much immediate direct benefit from the introduction of new representational and transportation technologies. They will have to want to adopt more sophisticated methods and technologies for other reasons.
In some cases individual departments in state DOT operations groups
have developed referencing systems to suit their purposes. For
example, the Florida state DOT has a project underway to combine
its current 14 linear referencing methods into a single generalized
method. Although this project will definitely improve this DOT's
ability to share data between the various groups in the department,
it will do very little to prepare it for the requirements of advanced
transportation projects. Other technologies such as GPS will,
in the very near future, be capable of providing the same information
derived from linear referencing systems but at less cost and with
significantly greater accuracy. Further, since GPS data is part
of a global coordinate system-that is, the locations are in relation
to distance from the center of the earth-the data from one locality
can easily be combined with GPS data from another. [Back to Outline]
Examples of Advanced Transportation Projects
Below are several examples of advanced transportation projects. In each case, the two-dimensional data currently being used is suboptimal, and better designs can be achieved through use of three-dimensional data.
Analyzing projects destined for the short term (1-2 years out),
medium term (540 years), and long term (20-30 years out) will
dispel the perception that the introduction of high-resolution,
three-dimensional data is only advantageous for projects planned
for deployment in future decades. In each example the application
of three-dimensional data improves or enables the respective technology.
[Back to Outline]
Short Term: The GIS-T/ISTEA Pooled Fund Study
The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) is the most recent response to the challenges of providing efficient, safe, and environmentally sensitive transportation. Among its many new initiatives, the ISTEA emphasizes the need for intermodal connectivity, establishes new requirements for cooperative transportation planning decision making, and explicitly recognizes the need for formal systems to manage pavements, bridges, highway congestion, highway safety, public transportation facilities and equipment, intermodal facilities, and to monitor highway traffic. These new policies define the requirements for a new generation of information technologies supporting transportation management decision making. The Congress and the U.S. Department of Transportation intend that these technologies are integrated, synergistic, and comprehensive.
The Pooled Fund Study represents the first national cooperative effort in the transportation industry to address the management and monitoring systems as well as the statewide and metropolitan transportation planning requirements of the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA). The Study was initiated in November 1993 through the Alliance for Transportation Research and under the leadership of the New Mexico State Highway and Transportation Department. Sandia National Laboratories, an Alliance partner, and Geographic Paradigm Computing, Inc., are providing technical leadership for the project. This Study demonstrates how the federal government can promote the assimilation of new technology into the fifty separate state DOTs (although its future is in question given the current thinking on unfunded federal mandates).
A principal goal of the Pooled Fund Study's design team is an integrated information and systems structure. The design is also intended to be extensible as new requirements are identified, and could engender a new mode of state DOT organization and efficiency. If achieved, it would be a radical departure from current practices, including the institution of a cradle-to-grave approach to infrastructure and the associated information management.
A key component of the integrated systems design is the inclusion of a general linear referencing system intended to serve as a de facto standard. If adopted, the system would enable all state DOTs to maintain one set of linearly referenced data with a formal method of "transforming" one system into another. The methodology is to maintain an underlying "reference system", or method of maintaining spatial coordinate data representing the location of all elements in the transportation infrastructure, that is of sufficient generality and spatial resolution to "map" one coordinate system to another.
While the study has been successful in demonstrating coordinated information management and integration, the two-dimensional data to which these processes have been applied is insufficient to achieve the studies technical objectives. Without going into the mathematical details here, the goal of arbitrary transformation between coordinate systems is, in general, impossible using two-dimensional data. Although the transformations are possible within reasonable approximation in most cases, the errors introduced into the data by ignoring elevation are not always negligible.
With current two-dimensional systems, the error can be accommodated to a certain degree by using techniques that "adjust" the data where errors are judged to be too large. An alternative is to simply store the data needed to provide the ability to maintain an arbitrary level of accuracy or precision with calculations involving spatial data. Analysis underway at Sandia indicates that only a minimal amount of data is required to analytically eliminate errors created by coordinate transformation. The modern relational database management systems (RDBMSs) and even more current object-oriented databases (OODBMSs) appear capable of dealing with the additional data needed to solve this problem.
A second area where three-dimensional data will help achieve the goals of the Pooled Fund Study is in providing cradle-to-grave transportation management. As stated earlier, the information flow required for a road's design, construction, and maintenance currently goes through several transformations. The engineers already utilize highly detailed three-dimensional data in CAD systems, which are then discarded when the construction phase is completed. Given the emerging transportation applications where these data would be useful, it would be highly appropriate for the data to be stored and maintained in the system. Various applications could view this data in an appropriate format. In this way the degradation of road design information described above would be reduced or eliminated.
The problem with maintaining this data in a three-dimensional
format is that virtually none of the state DOT business applications
(at least those in areas other than engineering) are capable of
benefiting from it in the short term. The consumers of the data
largely will be outside of the state DOTs, and in some cases clients
will not exist for years or even decades. Because data are so
expensive to recollect, it is unlikely that data will be collected
in the first place unless an immediate requirement for it is identified.
Unless the state DOTs shift to longer-term thinking, it is unlikely
that the data will ever be available for potential advanced transportation
projects. [Back to Outline]
Intelligent Transportation Systems will use technology to reengineer
our transportation infrastructure into one that maximizes safety
and efficiency and minimizes harmful environmental effects. There
are 29 ITS user services defining the six main systems in advanced
transportation: Advanced Traffic Management Systems (ATMS); Advanced
Traveler Information Systems (ATIS); Advanced Vehicle Control
Systems (AVCS); Commercial Vehicle Operations (CVO); Automatic
Vehicle Location (AVL); and Automatic Vehicle Identification (AVI).
These 29 ITS user services will monitor and control traffic on
highways and streets, giving travelers specific routes to follow,
supplementing drivers with autopiloting, improving the efficiency
of commercial vehicle deliveries, and eliminating the need for
weigh stations and toll collectors. Several of the these systems'
components are dependent upon geospatial data. For instance, route
guidance, vision enhancement, and automated vehicle operation
are some of the user services in which current two-dimensional
geospatial data is clearly inadequate for the design and deployment
of safe, robust technology. Each example is described in more
detail below.
Route Guidance. Route guidance will provide users of private and commercial vehicles, as well as pedestrians, with real-time transportation information. The service will display a suggested route to help a user reach a specific destination, taking into account traffic conditions such as congestion and road closures. Information about roadway networks and transit schedules will be available in the early implementation stages.
Current route guidance applications use planar technology, which is unable to identify changes in elevation. This is sometimes a problem, especially near bridges and complex intersections like cloverleaves where the computer interprets the coincident road segments as being on one plane (i.e., having connections where none exist). For example, the current GIS technology may mislead the user by asserting that the bridge and the road beneath it are, in fact, an intersection. It is possible to manually circumvent this problem, but it is not always effective with more complex bridges and intersections or with large urban areas. By using the third dimension, the data model now incorporates an elevation coordinate and is able to discriminate between the non-planar or overlapping road segments. This system will distinguish the bridge and road as two separate objects.
Route guidance technology also will benefit from spatial data
that are organized in an object-oriented manner. Current GIS programs
have great difficulty when encountering different modes of transportation.
Because all elements of the transportation system are represented
by the same points, lines, and polygons it is very difficult to
represent the difference between modes like railroad tracks, streets,
bicycle paths, and subway routes. A route guidance system, like
current planning models based on GIS data, frequently makes the
error of routing a car onto a railroad track and pedestrians down
a subway route. Today, this is corrected by manually tagging the
different modes with database attributes that can be translated
into humanly readable symbology such as color, line width, and
graphical patterns. With object-oriented technology it is much
easier and significantly less error-prone to identify the routes
as being strictly for trains, people, etc.
Vision Enhancement. Vision enhancement, or the projection of information on vehicle speed, direction, proximity of other vehicles, and roadside information, would be a desirable service during adverse weather conditions, and possibly while driving on congested urban freeways. Current prototypes of vision enhancement systems utilize low-power radar and object-recognition technology to provide information to the driver. The drawback of these designs, however, is that the quality of the information available to the driver is likely dependent on the traffic conditions. For example, because all of the information is deduced in real-time by the object-recognition system, if there are too many vehicles around the driver's car the information about the vehicle path will be questionable.
A potentially stronger vision enhancement technology would incorporate
a three-dimensional model of the road. Assuming that the currently
expensive technologies for sensing vehicle orientation could be
fused with this road model, the vision enhancement could become
independent of the traffic conditions. In this new scheme there
would be a constant projection of the road on the windshield (a
"heads-up display"). This projection would let the driver
view the road and other important information such as road signs
that are difficult to see in the best of circumstances on busy
freeways. In addition, this new technology could aid a driver
to accurately distinguish turns and elevation differences. [Back to Outline]
Automatic Piloting. Various alternatives exist for automatic piloting of vehicles. The less ambitious plans call for "platooning," or coordinated driving of cars to increase throughput on urban freeways, while the long-term goal of complete autopiloting is probably attainable in the 30-40-year horizon. Ultimately, a rider could simply indicate a desired location and the vehicle would drive there. In either case, however, there are benefits derived from the availability of the high-resolution geospatial data described here.
Current designs call for the auto-piloted or platooned vehicles to have dedicated highway lanes strictly for their use. These vehicles would then be controlled by magnetic nails implanted into the pavement about every 100 feet. The vehicle would turn a specific direction when polarity, as detected from the nails, changed.
Control systems based on this design reduce the piloting problem to two components: a two-dimensional lateral control problem, and a one-dimensional longitudinal speed-control system problem. Further, current designs also depend on the assumption that the special lanes would only be used on divided highways like interstates, where the designer can make many simplifying assumptions about the topography that will be encountered. The interstate systems have well-specified and standardized designs for most characteristics of the road, including maximum pavement grades, lane widths, and turn radii. The advantage of this construction from an ITS designer's point of view is simplicity. In practice, it is unclear how well these systems will work.
The magnetic nails give only approximate information about what to expect in the way of directional changes in the road. The main problem is that the telemetry derived from the nails is discrete; information is only available several times per second. Humans, by comparison, are able to use a continuous stream of information to judge when and how much to change the direction of the vehicle. At best, systems based on the magnetic nail designs will be reliable, but probably are not going to be able to achieve the smoothness of a human driver.
Here again, a three-dimensional data source would lead to a much stronger design. The magnetic nails can be used to determine speed with a very high degree of accuracy, and location with a fair degree of accuracy. The three-dimensional model would be used for refining the location data and for very precise preview calculations-in other words, 10 predict when changes in the road direction will occur. A system with these components would be able to achieve the smoothness of a human driver. Further, with the three-dimensional spatial data, it may be possible to operate these vehicles on more complex roads, rather than just interstate highways.
Robust geospatial representations, based on three-dimensional
data and unconstrained by linear referencing systems, would be
enabling for many applications in the transportation arena. Cradle-to-grave
management systems that collect and preserve data throughout the
lifespan of physical infrastructure could be created. User services
like those discussed above, which depend on an omniscient view
of locations, destinations, and moving objects, would become possible.
[Back to Outline]
The Federal Role and the Future of ITS
The alternative to the largely unregulated ITS, which is focused on the surface mode of transportation, is the highly regulated aviation industry. The agency responsible for oversight of commercial aviation is the Federal Aviation Administration (FAA) .The FAA has long been heralded for the unprecedented safety of the nation's air transportation system. On the other hand, the FAA has also been widely criticized for being a cumbersome bureaucracy. The most recent example of this criticism comes from the FAA's being perhaps a decade behind in updating the air traffic control (ATC) computers. This complaint is well-justified. No commercial enterprise would survive a decade of delay in upgrading its fundamental information technology. In fact, most of the calls for privatization stem from the FAA's inability or unwillingness to upgrade its computer system.
In spite of the FAA's inefficiency, however, the advantage of its highly centralized authority is that Americans' trust in the commercial aviation carriers is extremely high. The rules and regulations established by the FAA covering aviation technology and airline operations are clearly in the best interest of the flying public. While only a tiny fraction of the traveling public understands the complex operations of a modern jetliner, most Americans never give a second thought to boarding a plane operated by a commercial carrier.
Thus, while it is true that certain parts of the FAA's own operations could likely be better operated by private companies-the administration of the air traffic control system is the most visible example of this-the balance between public and private interests is the key to maintaining safety while achieving efficiency. It is unlikely that the oversight function, which is the keystone of the public's trust, could be relinquished without serious degradation of public confidence in the system.
Two areas for expanded federal activity in ITS are coordinating state activities, and defining and measuring program success. A key weakness in the overall structure of both the NII and the ITS is the lack of measurable technical goals. Without quantified targets it will be difficult to allocate resources to either project. Although there are fairly concrete and specific goals for protocols, software, and hardware interfaces, there is a lack of direction with respect to measuring the public benefit derived from these complicated and expensive systems. Thus, the possibility exists for the project to be a technical success but not publicly accepted-or worse yet, a commercial success but missing obvious opportunities to serve the public good. Even if all of the other technical issues are surmounted, how will it be possible to bring individual states, who are often happy using out-of-date technologies such as linear referencing, into the information revolution? It may well be impossible to implement many of the more advanced ITS features until a time when there is a federal legislative mechanism for propagating a common set of technologies to the states.
The 10 "stakeholder implications" (see Table 1)-the design goals that were used to gain approval for the program-from the early IVHS documents (e.g., U.S. Department of Transportation and IVHS America, 1994) need to be continually re-examined. Are these goals being met? Although it may be difficult to clearly quantify the degree that ITS serves the public good in such areas as equity, institutional empowerment, and privacy, the effort still needs to be made. The public interest must be protected by establishing a technical direction, then periodically assessing the results to assure that we are equitably benefiting from our investment.
One cause of uncertainty about the goals of both the NII and the
ITS is an apprehension about mandating a strong federal role in
either project. This uncertainty is a major threat to both projects.
Federal authorities have a broader vision than essentially all
of the
Table 1 IVHS Stakeholder Implications
| Deployment: | Impact on the rate of IVHS deployment |
| Equity: | Effect on the distribution of benefits and costs |
| Financing: | Impact on financing deployment, operations and maintenance |
| Institutions: | Impact on institutions and organizations |
| Market: | Effect on the development of an IVHS market |
| Operations & Maintenance: | Impact of operating and maintaining IVHS |
| Policy & Regulation: | Effect on implementing current and setting future policies and regulations |
| Privacy: | Effect on the privacy of individuals and organizations |
| Safety: | Impact on transportation system safety |
| Standards: | Effect on current and future standardization efforts. |
Source: U.S. Department of Transportation and IVHS
America (1994).
participants in these high-technology projects, and certainly the need for substantially improved spatial data is one example of where vision is needed to provide this missing component of the transportation infrastructure. It is vitally important that the federal agencies involved in high-tech initiatives do not rescind their roles as visionaries. Would we have an interstate, or more accurately, a national highway system if our government had not taken a lead role in the 1950s? Similarly, government participation will likely determine the ultimate success of both the ITS and the NII, as well as other high-technology initiatives that are yet to come.
Suitable policy must be implemented to ensure that the goals of the ITS do not, in the long run, hinder advances that are currently infeasible but well within the realm of possibility; these technologies include Route Guidance, vision enhancement, and automatic piloting. There will be considerable pressure, not from the public, but from private investors, to limit investment (or R&D) to get products to market in as short a period as possible. This will clearly limit the complexity and power of products and services coming from the ITS community. In addition, care should be taken to ensure that the consensus designs that emerge for the ITS standards do not preclude the introduction of future ITS applications.
Treating three-dimensional spatial data as part of the transportation
infrastructure and the importance of a third party to establish
the safety and effectiveness of transportation technology were
presented as two examples of the need for strong federal leadership
in the development of advanced transportation projects. Although
the technical advances in NII and ITS are impressive, they still
require a careful, wise, and comprehensive design and planning
process if society is to benefit from them. In order for our ultimate
goals-a safe, efficient, and environmentally sound transportation
system-to be attained, it is essential that policy lead technology
rather than the other way around. [Back to Outline]
This work was supported by the United States Department of Energy
under Contract DE-AC04-94AL85000. We also acknowledge Ray Byrnes
for his insights on ITS technologies. [Back to Outline]
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