This chapter presents the research approach used in this study and highlights the main findings.
The information for developing this report was gathered through review of published literature and telephone interviews with representatives of state Departments of Transportation (DOTs). This section summarizes the findings from the literature review and interviews.
Documents, conference proceedings and articles published in recent years dealing with HPMS, traffic data collection procedures and traffic monitoring equipment systems were reviewed. A complete listing of references is provided at the end of this document. The literature review focused on AADT monitoring on high-volume roads. Several states with significant mileage of roadways with high AADT volumes were identified. The review did not identify any state practices that are specific to high traffic-volume locations. State DOTs use a variety of programs directed at improving their traffic monitoring programs especially in urban locations, ranging from the use of Intelligent Transportation System (ITS) sensors to better training of agency personnel to collect data on urban/multi-lane facilities. State DOTs are also investigating new technology and equipment for use in urban areas. The most common equipment used by states are inductive loop and piezoelectric sensors for permanent counts and pneumatic tubes for short-term counts. Non-intrusive devices are not commonly used due to concerns with vehicle classification.
The Urban Transportation Monitor1 conducted a recent survey of traffic engineers in the U.S. and Canada to obtain information about traffic counting issues. The survey was sent out to 700 transportation professionals at public agencies via email. The following are some of the relevant findings based on responses received from 124 cities (i.e., 18 percent response rate):
The equipment mostly used for traffic data collection at permanent count stations is inductive loops while pneumatic road-tubes are mostly used for short term counts. Factors dictating the selection of permanent count locations include (high) traffic volumes and functional highway classification. Both permanent and short term count stations are used primarily for traffic volume data collection. Speed and classification data are secondary. The survey also revealed that consultants are extensively used in traffic data collection.
The respondents also listed some desirable improvements with counter equipment to include ability to import count data into software applications such as MS Excel, Access; increased durability, reliability, and accuracy.
The survey noted that data quality control (QC) was primarily done by the agency staff. Majority of the QC software used are provided by equipment manufacturers. Few agencies use in-house or third party software for quality control. About 36 percent respondents did not use any QC software. Several areas of improvements in the processing of traffic data were identified e.g.:
The survey results show that the present average error level reported by the respondents is closer to 5 percent. Most of the respondents (74 percent) indicated that their counts were accurate to about 95 percent (or 5 percent inaccuracies). In fact, 96 percent of the respondents indicated that the error in counts is less than 10 percent.
With regards to data sharing, the survey indicated that 79 percent of the responding agencies do not have any inter-local agreements that coordinate traffic collection activities. It was observed that the lack of coordination among agencies can lead to duplication of effort and an inability to share resources toward making traffic counting in a metropolitan area more efficient.
The main source of information for developing the best or common practices is interviews with traffic monitoring program managers and personnel from selected state DOTs. To determine the states to contact for information, those with the highest mileage of highways with high traffic-volumes were identified using HPMS 2001 data and National Highway Planning Network (NHPN) databases. Typically, high-volume routes have volumes in excess of 50,000 AADT. However, given that the definition of high traffic volume varies from agency to agency and from state to state, three threshold values were used 50,000, 75,000 and 100,000 AADT (Table 2.1). The top 13 states with high traffic volumes were selected: California, Texas, Florida, Georgia, Illinois, Massachusetts, Maryland, Michigan, Ohio, New York, New Jersey, Virginia, and Washington.
An interview guide was developed to facilitate the data collection process. Prior to the actual interviews, the guide was distributed to the state representatives. The interview guide was structured to capture information on various aspects relating to
|State Name||AADT >
|State Name||AADT >
|State Name||AADT >
|Florida||1122||New York||476||New York||286|
|New York||798||Florida||434||New Jersey||276|
|New Jersey||740||New Jersey||403||Illinois||244|
Telephone interviews were conducted with 12 state representatives. An on-site in person interview was conducted with Ohio DOT (ODOT) representatives. A summary of the interview responses was sent to the respondents to confirm the accuracy and completeness of the information provided during the interviews.
Information from the literature review and interviews were analyzed to identify best or most common practices used by state DOTs as well as the equipment used. Each of these practices is described in detail, including use, technologies, and points of contact. Finally, based on the practices and a review of equipment, some basic guidelines were developed to aid state DOTs in improving their HPMS programs.
This section presents highlights of the current state of the practice with respect to traffic data monitoring. These findings are derived primarily from the interviews with state representatives.
Traffic data collection for HPMS reporting is managed primarily by the state DOTs and their district/zonal offices in all the interviewed states. Ohio, Florida, Michigan, Massachusetts, Washington, and California collect all the counts on the state highway system using state DOT staff through the district offices. Georgia, Maryland, New Jersey, New York, Virginia, Texas, and Illinois contract out their traffic data collection activities either fully or partially to private agencies. In all states, city, MPOs and local agencies are involved in data collection for minor roads to varying extents.
Continuous counts are used by state DOTs for HPMS reporting where possible. Automatic Traffic Recorders (ATRs) are used for continuous counts that are 24-hour counts for every day of the year. ATRs are permanently installed on or near the roadway. Continuous counts provide volume and classification data as well as data needed to calculate daily, monthly, and seasonal variations in traffic to develop adjustment factors to apply to short-term counts Continuous counts are carried out by State DOT personnel in all states except Virginia, where contractors are responsible for the equipment and data collection.
Short counts comprise the bulk of the data collection program for HPMS. Short-count durations range from 24 hours, 48 hours (recommended by the Traffic Monitoring Guide [TMG]) to a full week (California). HPMS counting cycles range, depending on functional class, from annually (e.g., Texas) to once every three years. Short-counts are often a mixture of volume only, and volume and classification counts. Each state has its own methods of calculating adjustment factors with the data from ATRs and classification stations based on TMG guidelines for converting short-term volumes into AADTs. California, Florida, and Washington have detailed documentation on the calculation of adjustment factors. Most of the states interviewed use contractors to some extent to collect short-count data.
Data collected from continuous and short-term counts are processed in central offices of most state DOTs, although in some states, the district offices also do some preliminary data quality checks. Typically, state DOTs download and review daily volume counts (ADTs) for accuracy, completeness and validity. Review of traffic counts is often automated using either in-house or off-the-shelf software packages applying various traffic editing rules and traffic checks.
The primary objective of this project is to identify the best or common practices used by state DOTs and other agencies for collecting, processing and reporting traffic data on routes carrying high volumes. The definition of high-volume traffic routes varies from agency to agency. In fact, there is little evidence in the literature to indicate that state DOTs identify the segments for special emphasis for AADT monitoring based only on traffic volumes. An arbitrary definition of 20,000 AADT was used by FHWA in the Highway Information Quarterly Newsletter (www.fhwa.dot.gov/ohim/hiqsep01.htm). Other definitions include those used by the New York State DOT (NYSDOT) Pavements Group (High-Volume > 80,000 AADT).
Interviews with state DOTs did not provide specific definitions for high-volume routes. Several factors influence state DOT concerns with traffic-volume monitoring in urban areas not only the volume of traffic on the roadway. A high-volume route is usually not defined solely in terms of traffic volume but rather in terms of the difficulty in installing data-collecting equipment.
In general, roadway geometry, safety of data collection personnel, congestion, and multilane facilities were identified as factors used in identifying locations where data collection, especially short-term counts, is a problem. These locations invariably carry high traffic volumes.
This section summarizes the major findings relating to the state-of-the-practice in traffic monitoring reported by state DOTs.
The use of non-intrusive equipment was primarily for volume data. These devices are not widely used for data collection due to lack of knowledge on the capabilities and limitations. High-cost was also identified as a deterrent. DOTs however recognize the advantages of these devices. Some states have either tested or use limited non-intrusive technology.
The states interviewed employ the following approaches for data quality control and assurance:
The findings were analyzed to identify major issues facing state DOTs and other agencies in collecting data on high-volume routes. The major issues and challenges are listed below and discussed in detail in the following sections:
Safety of the traffic data collection crew was identified as the primary concern in installing equipment on high-volume routes. This applies to all types of data collection equipment.
Collecting traffic data in stop-and-go traffic conditions was identified as a major challenge. This includes technological limitations of sensors under those traffic conditions.
Traffic congestion precludes reliable classification counts.
Equipment failures (e.g., sensor), communication problems, and inability to secure road tubes throughout the duration of the counts was also identified as an issue associated with collecting traffic data on high-volume routes.
Construction affects traffic counts.
Incidents also impact traffic data collection activities.
Institutional issues, including funding constraints and lack of interagency cooperation, were noted to impact traffic data collection activities.
Data processing and quality control and assurance are challenges especially for high traffic-volume routes.
This section discusses the issues and challenges associated with data collection on high-volume routes in detail. In order to improve the quality of data for high-volume routes, these issues need to be addressed.
Safety of the traffic data collection crew was indicated by all the states interviewed as the primary concern in conducting short-term counts. Ohio, Massachusetts, Washington, Texas, Illinois, and New Jersey mentioned safety as the primary concern in collecting data on high-volume routes. Massachusetts indicated that the major distinction between regular routes and high-volume routes relates to the safety procedures that need to be employed to protect staff and the traveling public.
Traffic data collection in stop-and-go traffic conditions was identified as a major challenge. Stop-and-go traffic often results in volume and classification errors due to equipment limitations. Detectors that work on vehicle presence detection fail under these situations, resulting in erroneous data.
Similar to stop-and-go traffic, heavy congestion or high-volume traffic precludes reliable classification. For example, in congested traffic, the class tables provided by the vendors frequently fail to determine whether four counted axles represent two cars or one truck. It is also difficult and unsafe to install and remove data collection equipment under such traffic conditions.
Equipment failures (e.g., sensors), communication problems, and inability to secure road-tubes properly throughout the duration of counts are factors that affect the quality of data collected on high-volume routes. Some equipment failures are caused by external factors such as vandalism, utility operations, pavement repair and maintenance, pavement surface striping, and pavement deterioration.
Construction was identified as an impediment in data collection, but most states interviewed consider anticipated construction activities when planning their counting programs. However, the effect of construction on alternative routes is a concern, as it can result in abnormal data during a particular year on a given route. For example, construction on a major highway might result in increased traffic on nearby or alternate county and local roads. Unless clearly specified, the final user of the data has no way of knowing the underlying reasons for abnormality in the data.
Incidents are often more troublesome from a traffic data collection standpoint for the obvious reason that they are unforeseen. An incident on a section with ATRs can result in significant data losses.
Data quality and assurance were identified as important issues. The ability to process and assess the quality of data from different data collection equipment efficiently was noted as a challenge especially for high-volume routes. While states do not have a separate process for high-volume routes, they expect their processes to be robust enough to verify the validity of data for such traffic conditions.
The institutional issues were based on information from the literature review. The Volpe National Transportation Systems Center (VNTSC) conducted a survey of traffic monitoring in urban areas for FHWA (Volpe, 1997). The study noted that funding and staffing cutbacks have hurt data collection efforts in the recent past, and continue to pose a threat in the future. It also concluded that successful coordinated data collection programs were based on a spirit of cooperation and professionalism among all involved parties within a region. While current programs generally provide the data that is needed, data quality and accessibility are major concerns.
The best or common practices were identified to address these issues and challenges based on the findings, issues, and challenges described above. The next chapter presents detailed descriptions of the practices with examples
2The Urban Transportation Monitor. Vol. 18, No. 7, April 16, 2004.
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