Roadway Geometry and Inventory Trade Study for IntelliDriveSM Applications Applications
EXECUTIVE SUMMARY
PROJECT BACKGROUND AND PURPOSE
The U.S. Department of Transportation (DOT) IntelliDriveSM1 initiative seeks to improve transportation safety and mobility while reducing the environmental impact of surface transportation through the use of networked wireless communication among vehicles, infrastructure, and travelers' personal communication devices. The applications developed for the IntelliDrive initiative will require accurate positioning and temporally current information on roadway geometry and roadway features such as curve locations, number and width of travel lanes, presence and length of auxiliary turn lanes, roadway shoulder and median characteristics, posted speed limits, intersection characteristics, etc.
The purpose of this study is to investigate existing and emerging sources of roadway geometry and inventory data, including both commercial and public databases, as well as technologies and methods for collecting, maintaining, and updating roadway data items. These data sources are evaluated relative to potential near-term (within the next 5 years) IntelliDrive application data needs that were proposed and vetted through representative stakeholder groups. The study also examines the workflow practices and business models of current data providers and their capacity for delivering the roadway geometry and inventory data needed for future IntelliDrive applications.
INTELLIDRIVE DATA NEEDS
An initial list of roadway geometry and inventory data items was developed jointly by U.S. DOT staff and the study team. The list was compiled from data items identified in several earlier research studies, which were then evaluated against a set of potential IntelliDrive applications.
This initial list was vetted among IntelliDrive stakeholder groups to ensure that the specific roadway geometry and inventory data fully addressed the perceived needs of the IntelliDrive community. Stakeholder outreach was conducted through a series of Web meetings held in November 2009. A total of 30 individuals participated in the meetings, with participants representing the following stakeholder groups: State DOTs, county transportation agencies, traffic signal manufacturers, traffic management system integrators, automobile manufacturers, the trucking industry, university transportation research centers, IntelliDrive equipment developers and integrators, and the U.S. DOT.2
Based on stakeholder feedback, a few additional data items were added and used for the remainder of the study. The features and attributes included in the revised list can be grouped into four general categories: roadway geometry, roadway inventory, intersection characteristics, and other geospatial features.
ROADWAY DATA SOURCES
An initial screening was conducted to identify major commercial and public domain developers of roadway network databases covering the United States. In addition to the roadway network databases, the study team identified national, statewide, local highway, and public transit roadway inventory databases that can be linked to a geospatial roadway network. Based on the initial screening, the following roadway data sources were selected for inclusion in the detailed trade study:
- National roadway network databases: ALK Digital Maps™, DeLorme North America Data Set™, Google Maps™, NAVTEQ™ Road Network Database, Tele Atlas® MultiNet®, and the Census Bureau TIGER/Line®.
- National roadway inventory databases: Highway Performance Monitoring System (HPMS), the National Bridge Inventory (NBI), and the Highway-Rail Crossing Inventory (HRCI).
- State roadway inventory databases: California, Florida, Michigan, Virginia, and Washington.
- Local roadway inventory databases: Broward County, FL; Palm Beach County, FL; and TranStar in Houston, TX.
- Public transit operators: Central Florida Regional Transportation Authority (LYNX), Lane Transit District (LTD), Metropolitan Transportation Authority (MTA) New York City Transit (NYCT).
- Innovative data collection firms: Intermap Technologies, Mandli Communications, Inc., Fugro Roadware, and the Federal Highway Administration (FHWA) Digital Highway Measurement System (DHMS).
TRADE STUDY RESULTS
The roadway data sources were analyzed and compared based on the technical characteristics of their databases and the operational and business processes of the data providers. The findings from these analyses are summarized in this section.
Technical Analysis
Coverage
Successful deployment of IntelliDrive applications will require a geospatial roadway network that provides nationwide coverage and includes roadway geometry for all public roads. The investigation of potential roadway data sources found only six geospatial roadway networks that meet these criteria. Five of the networks are proprietary, developed for specific applications by commercial database developers. Only the Census Bureau's TIGER/Line® roadway network is in the public domain.
Roadway networks developed by State DOTs rarely extend beyond the borders of the State and often include updated information only on higher functional class roads for which the State DOT has administrative or maintenance responsibilities. Local roadway agencies do not typically develop or maintain their own roadway networks. Local agencies that have geographic information system (GIS) capabilities most often use either the State DOT roadway network, the Census TIGER/Line® roadway network, or one of the commercial networks.
The investigation also identified three public roadway inventory databases with nationwide coverage that include some of the listed IntelliDrive data items. Each of the three databases, HPMS, NBI, and HRCI, are compiled and maintained by the U.S. DOT from data submitted by State DOTs in compliance with federally mandated reporting requirements.
Network Connectivity
Several key roadway attributes required for IntelliDrive applications (e.g., locations of intersections, locations of entrance and exit ramps on freeway interchanges, and the identification of overpasses and underpasses) are best represented through the structure of the roadway database itself, using network connectivity. Network connectivity is also a prerequisite for roadway databases used to support vehicle navigation and routing. Of all the geospatial roadway networks investigated in this study, only the five commercial roadway networks provided full network connectivity at the time of the investigation.
Feature Resolution
IntelliDrive stakeholders identified the need for sufficient feature resolution to distinguish between individual travel lanes on a roadway and to provide certain attribute information on a lane-level basis. None of the geospatial roadway networks, public or commercial, provided lane-level feature resolution at the time of this study. Nearly all of them define roadway features as the centerline of the travel way or paved surface. The number of lanes associated with each roadway segment is defined as an attribute of the roadway segment.
Two of the commercial roadway network database developers, NAVTEQ™ and Tele Atlas®, offer enhanced lane information for certain roadway segments at freeway interchanges and at complex urban intersections with dedicated turning lanes. The enhanced lane information does not explicitly represent lanes as separate geospatial features and is not available for all urban areas.
Geospatial Accuracy
Potential IntelliDrive applications require a level of positional accuracy for roadway features and georeferenced attributes of 3.28 ft (1 m) absolute error or better. Current geospatial roadway networks have a positional accuracy ranging from 16.4 to 49.2 ft (5 to 15 m), depending on how and when they were originally constructed. This level of accuracy is sufficient for most public and commercial applications, including vehicle navigation. NAVTEQ™ and Tele Atlas® are improving their roadway network to a geospatial accuracy of 3.28–16.4 ft (1–5 m) absolute error to support potential IntelliDrive applications.
Attributes
Roadway attribute data are usually closely linked to the geospatial roadway network used to display them. The five commercial roadway networks include a significant number of the roadway attributes identified by IntelliDrive stakeholders that are also required for vehicle navigation applications. The Census TIGER/Line® roadway network includes relatively few of the identified IntelliDrive data items.
Except for the data items specified by Federal reporting requirements, roadway inventory data collected and maintained by State DOTs and local roadway agencies vary considerably from one agency to another. There are currently no standards and relatively limited guidance for roadway data collection at the State or local level.
Additional effort would be required to verify the accuracy and timeliness of even those attributes that are compiled for the national inventory databases. Other than consistency checks on attribute domain values little if any of the data submitted by State DOTs to the national inventory databases are independently verified by the U.S. DOT.
Commercial roadway database developers take a much more proactive role in verifying and updating roadway inventory data in their databases. They utilize multiple sources, including ongoing contacts with State and local roadway agencies, feedback from database customers, and in-house field teams to verify and reconcile attribute changes reported from other sources.
Data Format and Size
Roadway geometry and inventory data to support IntelliDrive applications must be stored in a format that can be read and utilized by a vehicle's on-board processors and that can be efficiently updated and transmitted for specific geographic areas and attributes. Nearly all of the public domain geospatial roadway networks are stored and distributed in one or more standard commercial GIS formats. These formats are reasonably effective for exchanging entire databases, but additional processing is required to transmit and integrate geographic subsets into a geospatial roadway network. Roadway attribute data that are linked to a geospatial roadway network using a linear referencing system (LRS) require even more processing because both the attribute data and any updates to the LRS must be transmitted and integrated into the geospatial roadway network.
At least two of the commercial roadway network developers store their roadway geometry and attribute data using multiple formats, including Geographic Data File (GDF)—a geographic data format that has become the de facto international exchange standard for navigation databases. While this ultimately may not be the most efficient format for storing or transmitting roadway data needed for IntelliDrive applications, it has at least proven to be an operationally practical format for in-vehicle roadway navigation databases.
Methods and Frequency of Updating
IntelliDrive applications will require that updates to roadway attributes critical to vehicle safety (e.g., bridge height, weight clearances, one-way street designations, turn prohibitions) are transmitted and incorporated into the vehicle roadway database soon after they are implemented.
None of the existing geospatial roadway networks or roadway inventory databases investigated in this study are updated and disseminated anywhere close to real time. The national inventory databases receive updates from State DOTs on an annual basis, but some of the data items reported by the States are based on periodic inspections or data collection activities that take place on 2-, 3-, or even 4-year cycles.
Commercial roadway databases obtain updates on a continual basis from multiple sources. Data updates are verified, reconciled, and incorporated into a master internal roadway database. At least three of the commercial roadway database developers create new versions of their master internal database on a weekly basis. Updated versions of the master roadway database are published at regular intervals ranging from as frequently as once a month to every 6 months, depending on the perceived requirements of the database customers.
Maintenance and Operations Analysis
Data Collection and Updating Technologies
Roadway geometry and inventory data collection sources use similar technologies for collecting and updating their databases. The primary methods currently used by both commercial roadway database developers and State DOTs include airborne orthoimagery and roadway data collection vehicles equipped with a differential Global Positioning System (GPS) recorder synchronized with various data capture technologies such as video cameras, pavement measurement equipment, and increasingly, mobile light detection and ranging (LIDAR).
Emerging data collection technologies, including airborne interferometric synthetic aperture radar (IFSAR) imagery and mobile LIDAR, can significantly increase the positional accuracy and resolution of roadway features and measured attributes. IFSAR imagery could be used to produce a geospatial roadway centerline database with measurements of curvature and grade at
a consistent accuracy level of 3.28–9.84 ft (1–3 m) nationwide. Mobile LIDAR can be used to obtain even higher positional accuracy measurements (0.328–3.28 ft (0.1–1 m)) of roadway attributes and features relative to the roadway data collection vehicle.
While nearly all of the roadway inventory data identified by IntelliDrive stakeholders could be captured using current data collection technology, the level of effort and associated costs to process videolog or LIDAR imagery in order to identify, locate, and measure specific roadway features typically forces State DOTs to prioritize what roadway features they extract and measure, as well as what road segments they collect data on. As improvements in automated feature extraction and measurement techniques reduce the costs of data processing, State DOTs may be more able and willing to maintain additional roadway attribute data.
Work Flow Processes
Roadway data to support IntelliDrive applications need to come from stable, reliable data sources with well-defined processes for data collection, storage, updating, quality control, and dissemination. In general, these work flow processes are more clearly defined and better integrated among the commercial roadway database developers than among public agency sources. The reason for this is that the roadway database is a marketable product that represents a primary source of income for commercial database developers. The better the product, the higher the market share and greater the revenue. For public agencies, data collection is conducted either to respond to a statutory requirement or to support specific internal applications.
Among State DOTs, collection of specific roadway data items has historically been compartmentalized, with each operating division collecting the data that it needs for its own internal applications. The result has been an assortment of "legacy" databases scattered throughout the agency, using different data formats, storage media, data collection and updating procedures, quality control standards, and location referencing methods. While many State DOTs have tried to develop enterprise data repositories to facilitate data sharing across organizational units (using geographic location as the common identifier for roadway features and attributes), the success of these efforts has been mixed. State DOTs generally have been successful in developing a statewide geospatial roadway network and one or more LRS methods to enable them to link different legacy databases to the roadway network. However, few State DOTs have successfully implemented agency-wide data collection standards.
National inventory databases such as HPMS represent a compilation of data items submitted by individual State DOTs and are subject to a standard data reporting format. U.S. DOT staff conduct consistency checks to ensure that attributes' values are within acceptable domain ranges and that summary statistics are reasonable. The U.S. DOT does not conduct independent verification of attributes reported by State DOTs for specific road segments.
All of the commercial roadway database developers have established work flow procedures for collecting, verifying, updating, and disseminating the data items included in their roadway network databases. Each of the commercial developers employs a staff of GIS technicians to input, verify, and edit geospatial and attribute data that they receive from various primary sources. These sources include publicly obtained roadway vector and orthoimagery, updates from State DOTs and local roadway agencies, error reports from database users, and other user-generated content, such as GPS vehicle tracks. The new data are checked, verified, and reconciled against other data sources and incorporated into the master roadway network database on a continual basis. Periodically, a copy of the master roadway network is published as a new version of the commercial database.
Business Models
There is a clear dichotomy between public and commercial data sources with respect to the primary customers for whom the roadway data are collected. Public agencies, particularly State DOTs and local roadway maintenance agencies, collect roadway data either to meet federally mandated reporting requirements or to support internal business needs for roadway construction, maintenance, or operations. Data collected by State and local agencies in response to Federal reporting requirements is typically not utilized directly by the State or local agency for its own business needs.
Federal roadway data inventories are designed primarily to collect and preserve statistical information on the condition and performance of nationally significant roadway infrastructure components. These inventories rely almost exclusively on State DOTs for data accuracy and quality control. Federal agencies conduct little or no independent verification of the accuracy of individual data items reported by the States.
For commercial roadway database developers, the roadway data are either the primary product or an integral part of the product or service that the commercial developer is selling. The content and quality (i.e., geospatial accuracy, frequency of updates) of the data are tailored to meet the perceived needs of the target market. These target markets may include specific niche customers or services unrelated to potential IntelliDrive applications, in which case the data provider is unlikely to add new roadway inventory data.
However, at least two of the commercial roadway database developers, NAVTEQ™ and Tele Atlas®, have stated that IntelliDrive represents a promising new market area and have already begun making enhancements to their current roadway data products in anticipation of future IntelliDrive requirements.
CONCLUSIONS AND RECOMMENDATIONS
Research Needs
The study identified several roadway geometry or inventory data items that were not being collected extensively enough to be useful for nationwide IntelliDrive applications. This suggests that one or more research efforts could be undertaken to investigate the feasibility and practicality of collecting specific data items using existing or emerging technologies and new methods for data integration and standardization across multiple data sources. Some examples of specific research studies include:
- Evaluating the feasibility of using IFSAR technology for collecting roadway geometry nationwide.
- Evaluating the feasibility and cost of using mobile LIDAR to collect selected roadway geometry and inventory data.
- Coordinating IntelliDrive roadway data research with safety research activities currently underway through the Strategic Highway Research Program 2 (SHRP2).
Institutional and Regulatory Options
The U.S. DOT could implement one or more of the following options to help increase and/or focus roadway data collection among State and local roadway management agencies to better support IntelliDrive data needs:
- Allow and facilitate State DOTs to submit additional road inventory data for HPMS.
- Encourage data collection on rural roads under FHWA's rural safety program.
- Monitor and participate in ongoing national roadway data sharing initiatives.
- Consider availability of local roadway data as a selection criterion for future IntelliDrive demonstration grants.
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