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6 Data about infrastructure are essential to the function of a transportation department and for assessing the mobility of goods and services nationwide. Pedestrian infrastructure data can be considered products in their own right; they are the result of a data collection process. To ensure a high-quality product, inputs to the data collection process should be carefully considered. This literature review begins with an overview of asset management and TPM as an orientation to topics discussed throughout this report. The literature review then highlights current data collection practices and requirements set forth by FHWA and concludes with a review of select pedestrian infrastructure inventory efforts conducted at the state DOT, MPO/RTPO or county level. These inventories provide insight into topics that should be considered when developing, maintaining and using pedestrian infrastructure data in large geographic areas. These programs were selected to represent various geographies, levels of government, sponsoring agencies and intended data uses. Overview of Transportation Infrastructure Data Management As defined by FHWA, asset management is a âstrategic and systematic process of operat- ing, maintaining and improving physical assets, with a focus on engineering and economic analysis . . . that will achieve and sustain a desired state of good repair . . .â Asset management is the application of a transportation performance management (TPM) system. In 2019, NCHRP released Management and Use of Data for Transportation Performance Management: Guide for Practitioners. Described here, this guide provides practitioners an over- view of good data collection and management practices among transportation agencies. Good data management allows agencies to track performance of transportation systems through TPM efficiently. Diagrammed in Figure 1, TPM is a process that: â¢ Measures current transportation system performance. â¢ Sets goals and targets for performance improvement. â¢ Allocates resources and planning work necessary to achieve desired improvement. â¢ Monitors results achieved to adjust plans and programs and update targets as needed. This is a data-driven process that relies on high-quality data collection and management prac- tices for successful TPM. This document was created to provide a framework for guiding trans- portation agencies toward successful TPM, ultimately improving their transportation systems. This data collection and management framework is divided into six steps: 1. Specify & Define Data: First, determine what types of data are needed for TPM based on agency goals and objectives and how the data will be used throughout the process. The C H A P T E R 2 Literature Review
Literature Review 7 necessary data will depend on specific performance measures. Identify the scope of data collec- tion, along with the necessary attributes and level of detail to be collected with regard to the transportation system. 2. Obtain Data: Collect the data necessary to calculate performance measures, provide con- text for performance trends, understand factors that contribute to performance results, set realistic performance targets and identify strategies for improving transportation system performance. 3. Store & Manage Data: Agencies must determine how and where the TPM data are stored. The data storage method depends on a multitude of factors, including the amount of data to be stored, organization data retention policies, sharing needs across agencies or departments, data security needs, and in-agency capacity for storage and management. Data management should include a quality assessment of data collected and development of a strategy for data quality improvements. 4. Share Data: The managing agency should determine an infrastructure for reporting and presenting data collected for TPM. This may include an analysis and selection of various data reporting tools or potentially developing a tool unique to the transportation agency, whether in-house or through a consultant. Data standards such as data dictionaries, standard data coding and file formats should be identified and followed during this stage. Publishing the data involves selecting a data-sharing method and determining internal and external data- sharing policies (publicly available vs. confidential data). 5. Analyze & Use Data: This step transforms data into meaningful analyses with identified trends and helps determine current and future performance of a transportation system using the reporting and analysis tools selected in Step 4 of this process. To effectively analyze and use TPM data, each agency needs to designate and train at least one analyst to review data trends, create visualizations, develop models to predict future performance, and document analysis trends and results. 6. Present & Communicate Data: The final step is to effectively present and communicate results and trends that appear in the TPM data. TPM reports should use text and visuals to clearly and efficiently present results of a transportation systemâs performance and provide clear recommendations for improvement. A full explanation, additional resources for TPM process planning and case studies can be found in Management and Use of Data for Transportation Performance Management: Guide for Practitioners. Figure 1. The Data Management Cycle. Source: Management and Use of Data for Transportation Performance Management: Guide for Practitioners, 2019.
8 Availability and Use of Pedestrian Infrastructure Data to Support Active Transportation Planning Of particular relevance for this report are Steps 2, 3 and 4 of TPM, shown in Figure 2. Notable lessons considered within this report include how: â¢ Intentional database design is critical to the support of future analysis. â¢ Maintenance of metadata is necessary for long-term usefulness of data products. â¢ The process used to update data should be repeatable. â¢ Data quality should be assessed, managed and balanced with cost. â¢ Existing data standards should be utilized whenever possible. â¢ Official data-sharing policies should be established. Existing Federal Infrastructure Reporting Standards Since 1978, states have been required to report some data annually for all public roadways as part of HPMS, which is âthe official source of data on extent, condition performance, use and operating characteristics of the nationâs highways.â More detailed data are required for road- ways designated as part of the National Highway System, including the number of travel lanes, posted travel speeds, pavement conditions and AADT. According to the HPMS field manual, these data are used for âassessing and reporting highway system performance under FHWAâs strategic planning process. Additionally, the HPMS is used for reporting metrics with respect to targets for established performance measures per 23 CFR 490. Finally, the HPMS data are widely used throughout the transportation community, including other governmental entities, business and industry, institutions of higher learning for transportation research purposes, and the general public.â As shown in Figure 3, HPMS data are collected and compiled from several sources and assembled by the state central office. Data sources are spatially referenced through Figure 2. Framework for improving data utilization for TPM. Source: Management and Use of Data for Transportation Performance Management: Guide for Practitioners, 2019.
Literature Review 9 a linear referencing system (LRS), which is used to describe where certain roadway attributes start and end based on roadway mileposts. At this time, pedestrian infrastructure data are not collected at the same level of detail as roadway information. The ADA does require some data collection on pedestrian infrastructure and mandates that the transition plan be made publicly available, along with a process for filing grievances. Under Title II of ADA of 1990, all state DOTs are required to develop a transition plan for all buildings and roadways within the stateâs jurisdiction, which is intended to achieve the following: â¢ Identify physical obstacles that limit the accessibility of facilities to individuals with disabilities. â¢ Describe the methods to be used to make the facilities accessible. â¢ Provide a schedule for making the access modifications. â¢ Identify the public officials responsible for implementation of the transition plan. Data on ADA accessibility often are collected as part of a state DOTâs self-assessment program and typically include the location of infrastructure, such as crosswalks and truncated domes. Due to limited funding availability, ADA self-assessment data often are collected via targeted efforts (e.g., infrastructure around roadway crossings). These targeted efforts generally provide insufficient data for some purposes (e.g., connectivity analysis and related physical assessment of networks). One common framework that could be used to define pedestrian infrastructure data standards at the federal level is MIRE 2.0. The MIRE Fundamental Data Elements (FDE) framework is intended to facilitate collection and reporting of safety data as mandated by the Figure 3. Suggested HPMS processing cycle. Source: HPMS Data Collection Field Manual, 2016.
10 Availability and Use of Pedestrian Infrastructure Data to Support Active Transportation Planning Fixing Americaâs Surface Transportation (FAST) Act and Moving Ahead for Progress in the 21st Century Act (MAP-21). MIRE is a listing of roadway and traffic elements and accom- panying data dictionary. While pedestrian infrastructure elements are included in the data dictionary, reporting on these elements currently is not required. Many of the required MIRE FDE elements are consistent with mandated HPMS elements. Select Inventories Reviewed As part of the effort, the following and relevant documents or inventories were reviewed. The years noted below are associated with the most recently published document reviewed for each state: â¢ Colorado Department of Transportation (CDOT): ADA Transition Plan, 2017. Describes Coloradoâs ADA transition plan. â¢ Florida Department of Transportation (FDOT): Transportation Data and Analytics Office Handbooks, 2017. Describes the data collection methods used in Florida. â¢ New Jersey Department of Transportation (NJDOT): New Jersey County Road Sidewalk Inventory, 2007. Describes methods used for sidewalk inventory. â¢ New York State Department of Transportation (NYSDOT): Sidewalks and Curb Ramps on the New York State-Owned Highway System, 2013. Describes methods used for sidewalk and curb ramp inventory. â¢ North Carolina Department of Transportation (NCDOT): Pedestrian and Bicycle Informa- tion Network (PBIN) Project, 2019. Describes the ongoing pedestrian infrastructure data collection project. â¢ Washington Department of Transportation (WSDOT): Sidewalk Data in King Countyâs Urban Growth Boundary, 2013. Provides details about methods and data collected for King County by WSDOT and partners. â¢ Delaware Valley Regional Planning Commission (DVRPC): Pedestrian Facilities Inventory, 2019. Describes DVRPCâs ongoing pedestrian inventory effort. This chapter presents a peer review of state and regional efforts to develop pedestrian infra- structure databases. This review intends to summarize current state and regional practices related to data collection, processing, storage, sharing and maintenance. Information from this literature review was used to inform the state of practice survey described in the next chapter. The following topics are discussed in the remainder of this section: â¢ Pedestrian network facility definition â¢ Pedestrian network attribute collection â¢ Data collection, management, sharing and responsible parties â¢ Data consistency â¢ Data maintenance and update strategy â¢ Program funding Pedestrian Network Facility Definition The reviewed pedestrian infrastructure inventories described in Table 1 vary greatly in the type and number of features collected, likely due to the goals and intended use of the inventory, as well as resources available to complete the database. Therefore, it is important to discuss how each state or region defined the facilities for inclusion in each inventory. Some inventories include pedestrian infrastructure on all roads in an area, while others only cover state or county roads. Inventories also include various levels of pedestrian infrastructure. Some consist strictly of sidewalks, while others may include side paths and other pedestrian-related amenities, such as curb ramps or pedestrian pushbuttons.
Literature Review 11 Pedestrian Network Attribute Collection Each inventory includes different features and characteristics related to pedestrian infra- structure, described in detail in Table 2. The inventories range from simple sidewalk location with few descriptive characteristics, to a robust dataset with multiple sidewalk attributes, as well as additional pedestrian infrastructure such as crosswalks, curb ramps and signals. Most commonly, the inventories include sidewalk location with some characteristics, such as width, buffer presence and curb ramp location. Data Collection, Management, Sharing and Responsible Parties A discussion of the data collection, management, sharing and responsibilities practiced by state and regional agencies can inform best practices for future pedestrian infrastructure inven- tories and maintenance of existing databases. Practices for each topic are summarized by location in Table 3. In general, current practices for collection, management, sharing and responsibilities vary by location, likely due to varied goals and resources across the locations. Some trends can be identified for each of the subjects as follows: â¢ Collection â Many states and regions use existing GIS data, aerial imagery and other computer- based methods to collect data on pedestrian infrastructure. Few agencies reference fieldwork as a common data collection method. Location How facilities aredefined Colorado Curb ramps and pedestrian pushbuttons were listed as pedestrian infrastructure; however, no further definition of these facilities was provided. Florida Both sidewalks and shared paths are considered pedestrian infrastructure. Shared paths are defined as an asphalt-paved way within the highway right of way that is at least 10 feet wide. It also is separated from the shoulder or back of curb by a barrier or an open space at least 5 feet wide. Sidewalk width and separation also are captured. Within this dataset, a sidewalk barrier is considered a physical barrier that separates motorized vehicle lanes from sidewalks or shared paths. New Jersey The datasets include the following facilities on county roads in New Jersey: paths (sidewalks, shared-use and worn), bicycle lanes and routes, shoulders, crosswalks, curb ramps, pedestrian/bicycle-related signage, and pedestrian provisions at intersections â such as pushbuttons and pedestrian signal heads. No further definition of facilities was provided. New York The inventory includes all existing sidewalks and curb ramps on all state-owned roads. No further definition of facilities was provided. North Carolina The PBIN includes existing and proposed bicycle and pedestrian facilities. This can be in the form of lines for linear facilities, such as sidewalks or bike lanes, or points for other amenities, such as bike parking or crosswalks. No further definition of facilities was provided. Washington (King County) Sidewalks are the only feature included in these data. The following rules were used to identify sidewalks: â¢ Made of concrete (gravel, dirt paths and wide shoulders are explicitly excluded from this definition) â¢ Elevated â¢ Separated from the roadway by curbstone â¢ Within approximately 20 feet of the street segment. DVRPC This inventory includes information about existing sidewalks, curb ramps and crosswalks in the greater Philadelphia region along all public roadways. Table 1. Summary of pedestrian facility definition by select agencies.
12 Availability and Use of Pedestrian Infrastructure Data to Support Active Transportation Planning Location Features of data collected Colorado Curb ramps â Six characteristics collected for each location: â¢ Running slope â¢ Cross slope â¢ Curb ramp width â¢ Curb ramp joints and grade breaks (flush vs. not flush) â¢ Turning space area â¢ Clear space requirement. Pedestrian pushbuttons â Seven characteristics collected for each location: â¢ Distance from crosswalk line to pedestrian pushbutton â¢ Distance from edge of curb, shoulder or pavement to pedestrian pushbutton â¢ Evaluation of footing around pedestrian pushbutton (level vs. not level) â¢ Cross slope adjacent to level area â¢ Side reach â¢ Height of pedestrian pushbutton â¢ Wheelchair access from curb ramp to pedestrian pushbutton. Florida Sidewalk barrier code â Type of barrier is recorded: â¢ 0 â No barrier â¢ 1 â On-street parking lane (with or without meters) â¢ 2 â Trees, planters, utility poles, etc. (less than 60 feet apart) â¢ 3 â Both 1 and 2 â¢ 4 â Guardrail/traffic railing barrier/swale. Shared-path width and separation: Path width (feet) and separation distance (feet) and direction are recorded. Sidewalk width and separation: Sidewalk width (feet) and separation distance (feet) and direction are recorded. New Jersey Datasets include facility location and characteristics about the features collected: â¢ Route location and attribute information, including material, presence of buffer and facility width on paths, sidewalks and walkways on the left or right side of undivided and divided county routes â¢ Route location and attribute information, including shoulder width and whether a bikeway is present on shoulders to the left or right of undivided or divided county routes â¢ Point location and attribute information relating to pedestrian facilitiessuch as ramps, crosswalks, signal heads, pushbuttons and pedestrian- or bike- related signs on county routes. New York Two datasets are available â sidewalks and curb ramps: â¢ Sidewalks â Polyline data depicting the location of sidewalks on state-owned roads, as well as the DOT region responsible for each segment â¢ Curb ramps â Point data depicting the location of curb ramps on state-owned roads, as well as the DOT region responsible for each feature. North Carolina â¢ Bicycle facilities (linear): Includes existing and proposed facility type, existing and proposed signage and markings, surface condition, facility width, and presence of rumble strips, among other attributes. â¢ Bicycle facilities (point): Includes bike parking, maintenance stations and signals. Specific characteristics collected include existing and proposed facility type, existing and proposed signage (MUTCD code), and presence of hazardous grates. â¢ Pedestrian facilities (linear): Includes existing and proposed facility type, existing and proposed signage and markings, surface condition, facility width, buffer type and width, and slope, among otherattributes. â¢ Pedestrian facilities (point): Includes crosswalks, curb ramps, refuge islands, pedestrian signals, overpasses and underpasses. Specific characteristics include existing and proposed facility type, existing and proposed signage, presence of a hazard, and whether a facility is ADA-compliant. Table 2. Summary of pedestrian facility definition by select agencies.
Literature Review 13 â¢ Management â Management practices vary greatly from one location to the next. Some data- sets are updated annually, while others are updated as new information is received from local jurisdictions. Others appear to have no data management or update strategy. â¢ Sharing â Many datasets are publicly available for download in spatial formats from DOT, MPO or open data websites. â¢ Responsible parties â State DOTs or managing MPOs (such as the Delaware Valley Regional Planning Commission) often are the parties responsible for data management. Data Consistency Ensuring data consistency is an important part of creating a pedestrian infrastructure inven- tory, especially across a large region or state. This type of inventory typically requires multiple people working toward the same effort, and interpretation of instructions often varies by person. For example, when collecting sidewalk data, some people may simply record the sidewalk loca- tion, while others may collect additional information such as width, buffers and other physical characteristics. Table 4 summarizes reported practices to help ensure data consistency. While data collection and processing methodologies differ by location, almost all inventories studied included descriptive methods for data collection and processing. Some also referenced hiring and training staff specifically for this task. Notable examples, DVRPC and North Carolina have developed a comprehensive data model that is used for data submission. Data Maintenance and Update Strategy Proper planning for future recommendations requires accurate data about existing pedestrian infrastructure conditions. It is important to develop a strategy for data maintenance and updates to ensure that datasets accurately reflect infrastructure conditions. As shown in Table 5, some inventories reference data maintenance being conducted by staff from public entities, such as Location Features of data collected â¢ Shared-use path facilities (linear): Includes existing and proposed facility type, surface material and condition, facility width, buffer width, and slope, among other attributes. â¢ Shared-use-path facilities (point): Includes shared-use-path facilities, typically existing and proposed amenities (e.g., parking and restrooms), access points, crossings, and signage. Wa North Carolina (continued) shington (King County) Sidewalk data include the following information: â¢ Presence or absence of a sidewalk 0 = absence of a sidewalk 1 = presence of a sidewalk 2 = partial presence of a sidewalk on the segment (the sidewalk length is less than 90% of the streetlength) â¢ Location on the left or right side of each street segment â¢ Method (manual vs. automatic) used to code the data. DVRPC The following features and attributes are being collected for the inventory: â¢ Sidewalk â Location of sidewalk (some condition information included if available in existing dataset gathered from local jurisdiction) â¢ Curb ramps â Center and location (diagonal vs. nondiagonal) of curb ramp. Table 2. (Continued).
14 Availability and Use of Pedestrian Infrastructure Data to Support Active Transportation Planning Location Data collection, management, sharing and responsible parties Colorado Collection: Existing intersection data, video logs, aerial imagery and other Information. Management: None identified. Sharing: Database is publicly available as a spatial dataset on CDOTâs website. Responsible parties: CDOT. Florida Collection: Appropriate data collection methods vary for each feature. Management: Data are managed by FDOT staff in the Transportation Data and Analytics (TDA) Office and staff in specified feature management offices. Sharing: Datasets are available for download from the FDOT website. Responsible Parties: Various offices are responsible for collection and management of inventory features. New Jersey Collection: GPS-equipped vehicle with four mounted digital cameras collected nearly 8 million images along 13,200 miles of county roadways. Management: None identified. Sharing: The inventory is available as county-level maps and spatial datasets for download from the NJDOT website. Responsible parties: NJDOT. New York Collection: Assessment of NYSDOTâs VISIDATA digital photo log files and other resources. Management: NYSDOT is responsible for data management. The original inventory was completed in 2008 and updated annually until 2013. Sharing: The data are available for download in multiple spatial formats from the data.ny.gov site. Responsible parties: NYSDOT regional offices. North Carolina Collection: The PBIN database was created by combining existing pedestrian and bicycle infrastructure datasets gathered from, or submitted by, North Carolina jurisdictions. Management: NCDOT manages the data but relies on new submissions for data updates from local jurisdictions. Sharing: The PBIN database is available for download from the NCDOT website. Responsible parties: NCDOT. Washington (King County) Collection: The dataset was compiled by combining sidewalk datasets from local jurisdictions in King County, in addition to computer-based data collection methods using Google Maps and similar online resources. Management: None identified. Sharing: None identified. Responsible parties: University of Washington Urban Form Lab (UFL) and WSDOT. DVRPC Collection: The data are being compiled by DVRPC and a private consultant using existing datasets and aerial imagery. Management: DVRPC is working with consultants to develop appropriate management methodologies. Sharing: DVRPC is sharing the inventory in stages via its online GIS data portal and an online mapping platform. Responsible parties: DVRPC is the primary party responsible for maintaining the inventory. Table 3. Data collection and management responsibilities by select agencies.
Literature Review 15 MPOs or state DOTs, with input from local authorities. North Carolina makes the update pro- cess seamless as long as data are provided to the state in a consistent format. Others do not indi- cate a specific strategy for data maintenance and future updates to infrastructure inventories. Program Funding Available funding and resources dictate the amount of data that can be collected. Put simply, the more funding available for data collection and processing, the more features and characteris- tics can be included in an inventory. Knowing how states and regions fund pedestrian infrastruc- ture inventory development can help inform how future inventories are funded. The answers are summarized in Table 6. There was limited information available on funding sources for these inventories. Some locations did not identify funding sources, while others referenced funding from FHWA, as well as state resources. Location Ensuring data consistency Colorado CDOT hired and trained temporary GIS field technicians to collect data. Florida The guidance and standards provided in the handbook were created to ensure data consistency. New Jersey Staff were educated and trained on data processing strategies to ensure consistency of data processing and management, and standard naming conventions were identified to define certain attributes. North Carolina To be considered for incorporation, data must use a standardized geodatabase template created by NCDOT and follow standardized terminology related to facility types. Washington (King County) The report identifies a clear method for coding sidewalk data in the region to ensure data consistency. DVRPC DVRPC is working with a consultant to develop a data model and method for data collection that will be available to users via the online mapping platform. Table 4. Data quality and consistency strategies by select agencies. Location Data maintenance and update strategy Colorado No specific maintenance and update strategy is identified. Florida An RCI coordinator works with managing offices in charge of the collection and maintenance of features, and appropriate staff submit correction forms to indicate needed inventory modifications. New Jersey No specific maintenance and update strategy is identified. New York Each regional office is responsible for maintenance and updates to sidewalk and curb ramp data within its jurisdiction. North Carolina NCDOT depends on local government submittals to keep the geodatabase current, and information received from local partners is added to the geodatabase and available for download on at least an annual basis. DVRPC DVRPC is developing an online mapping platform that will allow users to add new features to or update attributes of the pedestrian inventory using updated aerial and street-level imagery on an ongoing basis. Table 5. Data maintenance and update strategies by select agencies.
16 Availability and Use of Pedestrian Infrastructure Data to Support Active Transportation Planning Table 6. Program funding by select agencies. Location Program funding Colorado The previous 2013 ADA Transition Plan identified a need to inventory CDOT curb ramps and schedule upgrades to the infrastructure. The CDOT Transportation Commission approved $85 million to bring curb ramps up to ADA and PROWAG standards within 5 years, which included development of this inventory. New Jersey Initial data collection and processing were conducted using funding obtained from FHWA in 2006. Washington (King County) Grant funding was provided by WSDOT. DVRPC DVRPC received funding to build the sidewalk inventory using New Jersey and Pennsylvania TIP dollars, while the online mapping application was developed using Pennsylvania State Planning and Research Program funds.