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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
×
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Suggested Citation:"Chapter 2: Research Approach." National Academies of Sciences, Engineering, and Medicine. 2017. Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/24732.
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NCHRP 07‐19(02) Final Report 17 Chapter 2: Research Approach  This section describes the approach used for testing the nonmotorized counting devices and technologies investigated in Phase 2. Chapter 3 presents the results of this testing and merges the results with those obtained during Phase 1. Consistent with NCHRP practice, no product names or manufacturers are described here by name. Rather, when more than one product was tested representing a particular technology, the products are referred to as “Product A,” “Product B,” etc. Furthermore, the objective of testing different products was not to rate individual products, but rather to identify whether different implementations of a particular technology appear to have a bearing on the observed count error. TECHNOLOGY TESTING OBJECTIVES  The primary objective of testing the counters used in this research was to determine their accuracy under a variety of conditions. Good measurements of accuracy can be used to develop correction factors to account for regular under‐ or over‐counting by specific sensor technologies under specific conditions. One of the most common sources of error for devices that detect users from a distance is the tendency to undercount due to occlusion, or one traveler blocking another from the counting device’s field of detection. Devices that detect users through contact or close‐proximity movement (e.g., pneumatic tubes and loop detectors) may also have other sources of error, such as not detecting enough pressure, not detecting certain materials, or counting motor vehicles in addition to bicyclists. Other counting device characteristics were also evaluated, including:  Ease of installation,  Labor requirements,  Security,  Maintenance requirements,  Software requirements,  System power requirements,  Impact of weather conditions,  Cost (e.g., purchase, installation, and other costs related to obtaining and activating devices),  Coverage area (versatility), and  Flexibility to use data outputs for various applications, including matching the Traffic Monitoring Guide format (FHWA 2013).

NCHRP 07‐19(02) Final Report 18 SENSOR TECHNOLOGY SELECTION  Two of the devices included in Phase 2 entered the market for practical pedestrian and bicycle volume data collection after Phase 1 was underway and represented technologies that had not been tested in Phase 1. These devices were:  Thermal imaging camera. These devices combine the technologies of passive infrared detection and automated counting from imaging. The camera detects the infrared radiation (i.e., heat) given off by pedestrians and bicyclists, and the system counts the number of heat‐ emitting objects that pass through a defined detection zone within the camera’s field of view.  Radar. These devices operate by emitting electromagnetic pulses and deducing information about the surroundings based on the reflected pulses. The device that was tested is designed to be buried in the pavement. Both of these sensors required additional components to create a usable counting package. The thermal imaging camera, which was mounted on a street light mast arm, required an interface card installed in a nearby traffic signal controller cabinet to process and store the data, as well as data and power cabling. The radar unit, which was buried in a bicycle lane, required two additional communications devices. The first was a pole‐mounted repeater unit located nearby that received data transmitted by the buried sensor. The repeater retransmitted the data to a receiver module which processed the data and uploaded it to the vendor via a cellular modem. Both devices also required vendor‐supplied software for viewing and exporting the count data. The other three counting technologies, bicycle‐specific pneumatic tubes, piezoelectric strips, and passive infrared, had been tested in Phase 1, but using products from other vendors. The bicycle‐ specific pneumatic tubes tested in Phase 1 experienced problems with motor vehicles dislodging the tubes; as a result, few data were collected for this technology during Phase 1 relative to other technologies. Two piezoelectric products from different vendors had been planned to be tested in Phase 1, but one product experienced problems with vendor support and was therefore removed from the Phase 1 research program. The passive infrared counter that was tested in Phase 2 was part of a combination counter that included a piezoelectric sensor for counting bicyclists. Including devices from different vendors that share a common sensing technology allows the research to investigate whether issues with accuracy and precision appear to be inherent to the technology, or are a result of a particular vendor’s implementation of the technology. SITE SELECTION  Site Selection Process  Three jurisdictions were selected for testing the devices on the basis of (1) the researchers having existing staff contacts at the jurisdictions who could facilitate obtaining any required permits to install the devices, and (2) the locations being close to the vendors of the devices, allowing easier coordination for installation, calibration, and (if necessary) troubleshooting. These jurisdictions were:

NCHRP 07‐19(02) Final Report 19  Arlington County, Virginia;  Washington, D.C.; and  Oakland, California. The site used in Arlington was the same test site on the Four Mile Run multiuse trail used in Phase 1. The site was selected as both piezoelectric counters being tested were already located there, one having been installed by Arlington County in April 2010 prior to Phase 1 and the other having been installed during Phase 1. The test sites in the other two cities were selected in consultation with local agency staff and the vendor on the basis of:  From the researchers’ point of view, locations with relatively high bicycle volumes, to allow the devices’ accuracy and precision to be tested under a range of volume conditions;  From the jurisdictions’ point of view, locations that would provide useful data for them in the future, as they would take over ownership of the counter following the tests; and  From the vendors’ point of view, locations that complied with the vendors’ guidance for suitable installation locations for the sensors and their supporting technology (e.g., detection area dimensions, access to power, radio communication ranges). The bicycle‐specific pneumatic tubes, being portable, were tested during a one‐week period at each test site. Individual Site Descriptions  This section describes the sites used for the follow‐up testing. Descriptions of the sites used in Phase 1 are provided in NCHRP Web‐Only Document 205 (Ryus et al. 2014b). Arlington, Virginia The Arlington site was located on Four Mile Run Trail east of I‐395 (Figures 2‐1 and 2‐2). Two piezoelectric counters were already located there. One had been installed by Arlington County in April 2010, prior to Phase 1 (not visible in Figure 2‐2), while the other was installed during Phase 1 (marked “A” in Figure 2‐2). The latter device experienced communication problems which the device’s original vendor was unable to solve; therefore, the device could not be tested during the original research. However, at the start of Phase 2, Arlington County staff worked with the device’s new vendor to install new hardware to connect to the existing piezoelectric sensors and to obtain updated software; these actions solved the communications problem and allowed the device to be tested. In addition, the new vendor installed a passive infrared sensor (marked “B” in Figure 2‐2) that allowed pedestrians to be detected in addition to bicyclists. (The piezoelectric sensor detects bicycles only, the passive infrared sensor detects both pedestrians and bicycles, and the difference in the two counts is the pedestrian count.) Bicycle‐specific pneumatic tubes were also temporarily installed at this site for one week (marked “D” in Figure 2‐2); the tubes were dislodged toward the end of the week and were not reinstalled. Other equipment at the site includes a passive infrared counter installed by Arlington County (marked “C” in Figure 2‐2) that was tested in Phase 1.

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NCHRP 07‐19(02) Final Report 24 SUMMARY OF TEST SITES AND TECHNOLOGIES  Table 2‐1 summarizes the counting technologies and products tested at each site. Table 2‐1.  Counting Technologies and Products Tested in Phase 2  Technology Category  Product  Site  Arlington  Washington, D.C.  Oakland  Piezoelectric strips  A  Existing B  Existing Passive infrared  C  New Pneumatic tubes: bike‐specific  C  New  New  New  Pneumatic tubes: standard  C New  Thermal camera  A New Radar  A New  Notes:  Existing = existing installation, New = new device installation during Phase 2.  Product letter designations are continued from Phase 1 testing (e.g., passive infrared products A and B  were tested during Phase 1 but are not shown in this table).  EVALUATION METHOD  Evaluation Criteria  Pedestrian and bicycle counting technologies were evaluated according to several performance measures. The primary evaluation criterion was accuracy. However, ease of installation, labor requirements, security, maintenance requirements, software requirements, cost, flexibility of data, and other characteristics were also assessed. Accuracy  Accuracy was determined by comparing data generated by the automated counting devices with ground truth pedestrian or bicycle volumes generated from manual counts taken from video recordings. This method of generating ground truth counts was selected primarily because it is believed to be the most accurate, as the data reducers can play back the time‐synchronized videotape at a suitable speed for making sure all pedestrians or bicyclists are recorded and classified to the appropriate time period. Data reducers can also rewind the tape if necessary to check that no pedestrian or bicyclist was missed. This method also had the benefit of allowing a relatively large amount of video to be collected, from which the researchers could select only the time periods with environmental conditions (e.g., rain, darkness) or nonmotorized volumes of interest to be counted. Finally, the method allowed data to be collected at a different time from when it was reduced, which helped spread out the use of research team labor. The process used to generate the ground truth counts is described in a subsequent section.

NCHRP 07‐19(02) Final Report 25 All of the counters tested, except for pneumatic tubes, were permanent installations. The tube counter was moved from site to site and only installed during a period when a camera was present collecting video for the ground truth counts. Ground truth video for the permanent installations was recorded during two one‐week time periods. The first occurred after the devices had been calibrated and all parts of the system (e.g., communications) were working. The second occurred later, when warm weather was forecast, to capture higher volumes of bicyclists and pedestrians. The pneumatic tubes were in place during the first ground truth data collection period for each site. As described in detail in Chapter 3, correction factors were developed by comparing the ground truth counts to the counts produced by each device that was tested. The researchers selected specific hours from each week of video to develop ground truth counts, corresponding to hours when specific conditions of interest occurred (e.g., high bicycle volumes, rain). Other Characteristics Evaluated  In addition to accuracy, the following factors were evaluated:  Ease of installation. Potential installation difficulties include the need for specialized equipment (e.g., saw cutters, junction boxes), the need for specialized knowledge, difficult‐ to‐reach mounting points (e.g., points high above the ground), difficulties with calibration, and length of time required to complete the installation under normal conditions. The level of technical assistance required from vendors to install and calibrate the technologies was noted (i.e., how easy was the technology to install “out of the box”?).  Labor requirements. Labor requirements include the time and effort needed for installation, ongoing maintenance, data cleaning, and data analysis.  Durability and security from theft and tampering. Durability and security were evaluated based on both inspection of the hardware to assess the relative durability and resistance to tampering or theft, as well as recording any damage sustained while a device was in place. Some possible problems that were anticipated included theft, obstruction of optical devices (lenses) with foreign objects (e.g., chewing gum, paint), disconnection of parts or wiring (e.g., pneumatic tubes removed from logger), and opened device cases.  Maintenance requirements. Maintenance requirements included regular site visits for visual inspection, data downloads, re‐calibration of the device to maintain accuracy, optical lens cleaning, or removal of obstructions. Anything requiring a site visit after installation to continue accurate data collection was documented as a potential maintenance requirement. Costs associated with ongoing maintenance were considered.  Flexibility of data produced. The data formats exported by the counter were evaluated for ease of export and transfer, as well as compatibility with the FHWA’s Traffic Monitoring Guide format (FHWA 2013).  Cost. Cost refers to the monetary cost of purchasing and installing the device, including any additional accessories or software necessary for count data collection and analysis, as well

NCHRP 07‐19(02) Final Report 26 as costs associated with ongoing use, such as replacing batteries and charges associated with telemetry.  Weather tolerance. To the extent scheduled data collection times and budget permitted, technologies were evaluated based on their ability to operate and maintain accuracy under a range of climates and weather conditions (e.g., heat, cold, rain, fog). These factors were evaluated largely from a qualitative standpoint, except for in cases where a quantitative approach was feasible (e.g., times and costs). VIDEO DATA REDUCTION PROCESS TO GENERATE GROUND TRUTH COUNTS  All of the manual counts were conducted using video footage collected at the test sites. Videos were typically recorded for two seven‐day periods at each of the sites in the study, aiming to test the technologies under a diverse set of environmental and traffic conditions. The video cameras and counting devices were time‐synchronized with each other to ensure accurate assessment of events captured by specific time periods. Videos were shipped from the test sites on DVDs. The video collection dates for the follow‐up research are listed in Table 2‐2. The first week of data collection occurred soon after device calibration had been completed. The second week of data collection occurred during a week when good weather was forecast, in an effort to maximize the number of bicyclists observed. An additional day of testing was added in Oakland to coincide with Bike to Work Day, when high bicycle volumes were expected. Table 2‐2.  Dates of Video Collection for All Sites Used in Phase 2  Site  Video Data Collection Dates  Arlington  June 19–26, 2015  October 19–28, 2015  Washington, DC  February 22–29, 2016 April 18–23, 2016  Oakland  November 10‐15, 2015 April 18–24, 2016  May 12, 2016  INTERRATER RELIABILITY  Similar to the process used in Phase 1, interrater reliability was evaluated by having data collectors conduct counts on a set of 30 one‐minute video clips. These counts were then evaluated against one another using the Concordance Correlation Coefficient, a measure of agreement commonly used for interrater reliability evaluation. All data collectors largely agreed with one another, producing very high rates of interrater reliability, as shown in Table 2‐3. Note that in Phase 1, an error was made in the interrater reliability data entered for one of the data collectors and subsequently reported in the final report; the results in this report have been corrected. Table 2‐3 includes all of the data collectors who participated in either Phase 1 or Phase 2.

NCHRP 07‐19(02) Final Report 27 Table 2‐3.   Results of Interrater Reliability Evaluation (Concordance Correlation  Coefficients): Phases 1 and 2 Combined      Data Collector      1  2  3  4  5  6  7  8  9  Da ta  Co lle ct or   1  1.000  0.989  0.986  0.989  0.989  0.989  0.989  0.986  0.992  2  ‐‐‐  1.000  0.997  0.989  0.995  0.995  0.995  0.997  0.992  3  ‐‐‐  ‐‐‐  1.000  0.987  0.992  0.992  0.992  0.995  0.989  4  ‐‐‐  ‐‐‐  ‐‐‐  1.000  0.995  0.995  0.995  0.992  0.997  5  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  1.000  0.995  1.000  0.997  0.997  6  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  1.000  0.995  0.997  0.997  7  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  1.000  0.997  0.997    8  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  1.000  0.995    9  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  ‐‐‐  1.000  DATA STORAGE  For Phase 2, a Google Form was used by data collectors to input their manual count data. Automated counts and weather data files were all stored in CSV files, which were merged using the Python programming language. Code is available upon request from SafeTREC for any research team that would like to duplicate the methodology. WEATHER DATA SOURCES  To test the effects of weather on accuracy, weather data were obtained from the National Climatic Data Center’s Quality Controlled Local Climatological Database, except for weather data for Montreal, which was acquired through the Government of Canada’s Historical Climate Database. Data was obtained for the nearest monitoring station for each city, as detailed in Table 2‐4. This table includes all of the weather stations used for Phases 1 and 2. Table 2‐4.  Weather Stations Used as Sources of Weather Data for Equipment Testing  City  Weather Station  Weather Station ID  Washington, DC and Arlington, VA  Ronald Reagan International Airport  13743/DCA  San Francisco, CA  San Francisco International Airport  23234/SFO  Berkeley and Oakland, CA  Oakland International Airport  23230/OAK  Davis, CA  Nut Tree Airport (Vacaville, CA)  93241/VCB  Portland, OR  Portland International Airport  24229/PDX  Minneapolis, MN  Minneapolis‐St. Paul International  Airport  14922/MSP  Montreal, QC, Canada  Montreal International Airport  not applicable 

NCHRP 07‐19(02) Final Report 28 DATA CLEANING  The automated counters did not export data in a consistent format. Some devices exported counts in 15‐minute bins, some exported counts in 1‐hour bins, and some timestamped each individual count. The timestamp‐stored values were converted to 15‐minute bins to allow for consistent analysis. All data were then converted to 1‐hour time periods for consistency of analysis. For the devices that output data in 15‐minute intervals, this meant summing the automated and manual count values across the four component intervals of the hour. For the devices that output data in 1‐ hour format, the manual count values were summed across the four component intervals to yield an hourly total. Some devices being tested performed in ways inconsistent with other devices of the same type installed at different sites. While every effort was made not to omit any data points without a solid rationale to justify their exclusion, the sites summarized in Table 2‐5 were excluded for the reasons shown. The research team felt that these periods of data collection were not representative of typical operating conditions of the technologies being tested (given their inconsistency with other devices of the same type). In some cases, the source of the problem could not be diagnosed, but possible explanations include a problem inherent to the device, installation error, calibration error, or poor placement of the ground truth video camera.

NCHRP 07‐19(02) Final Report 29 Table 2‐5.  Summary of Data Removed from Analysis in Phases 1 and 2  Research Phase  Site and Device  Reason  Phase 2  Oakland radar  A single outlier observation was removed due to strong effect on  results. Results in Chapter 3 are presented both with and  without this observation.  Phase 1  L Street inductive loops Very high undiagnosed overcounts, inconsistent with  performance at all other sites.  L Street passive  infrared  High overcounts during one month of testing were removed.  These were attributed to the installation of the counter, which  was oriented toward a plate glass window with foliage in the  foreground. During the summer, when temperatures were high,  the foliage was suspected to heat up and trigger false positives.  Rue Maisonneuve  inductive loops  Only 4 hours of observations were taken, 2 of which were false  0s, leading to limited reliability of results.  University Ave.  inductive loop facility  counts  Data at this location were collected before the need to collect  counts for the full facility was identified. The results for the  “detection zone” are reported on.  Eastbank Esplanade  radio beam  Automated counts were faulty, with extended periods of 0  counts followed by periods averaging 1000s of people per hour.  Berkeley radio beam Automated counts appeared to be faulty, with extended periods  of 0 counts during the middle of the day.  Midtown Greenway  inductive loops  (sensor counts only)  Poor ground truth camera placement that prevented  researchers from defining whether bicyclists were in or out of  the loop’s detection zone, which did not cover the entire width  of the facility.  Midtown Greenway  pneumatic tubes  These pneumatic tubes showed substantial undercounting when  initially installed. A representative from the vendor adjusted the  sensitivity setting remotely, after which the counter  demonstrated a consistent pattern of overcounting. The  consistent pattern of overcounting suggests that the tube could  be adjusted again to achieve a more accurate count, but  because the research team did not recognize that this was  needed until after video had been collected, this counter was  removed from the analysis to avoid an unfair representation of  the device that would be avoided in practice by more careful  calibration of the device.  15th Avenue  (Minneapolis)  pneumatic tubes  These tubes substantially overcounted bicyclists, inconsistent  with pneumatic tubes at other sites. Part of this could be  attributable to poor validation video footage, as trucks and  buses frequently obscured the detection zone from the camera. 

NCHRP 07‐19(02) Final Report 30 SUMMARY OF DATA COLLECTED AND EVALUATED  Video data were collected twice for most of the sites in the study. Data collection periods were typically between 2 and 5 days long (Phase 1) or 7 days long (Phase 2), and took place between March and November 2013 for Phase 1 and between June 2015 and May 2016 for Phase 2, as described earlier in this chapter in Table 2‐2. Specific hourly intervals were selected for reduction from these large batches of video. Videos were selected heuristically, with a focus on maximizing the amount of data under extreme conditions (e.g., high volumes, hot or cold temperatures, thunderstorms) and maximizing the amount of data for the technologies that were underrepresented in the study (active infrared, piezoelectric strips, and radio beam). Table 2‐6 summarizes the characteristics of the collected data. All of the variables denoted “hours” show the number of hours of automated counts with corresponding ground truth counts under each of those conditions. The variables marked with (mean/SD) show the mean value and standard deviation of the variable in question across all hours of video used for analysis for a given technology. Table 2‐6.  Summary of All Data Evaluated in Phases 1 and 2   Notes:  SD = standard deviation.  “Facility” considers the ground truth count to be all bicyclists on the facility (i.e., street or path) to account for bypass errors.  Condition  Active  Infrared  Thermal  Camera  Passive Infrared  Radar  Radio  Beam  Induction  Loops  Induction  Loops  (facility)  Piezo‐ electric  Strips  Pneu‐ matic  Tubes  Total hours of data  34  28  398  32  56  165  202  120  279  Temperature (°F)  (mean/SD)  64 / 25  54 / 12  72 / 11  60 / 5  78 / 6  70 / 13  69 / 15  73 / 11  69 / 10  Temperature range   (°F)  12–86  40–83  13–93  48–72  66–90  17–93  12–93  48–93  40–91  Hourly user volume  (mean/SD)  327 / 209  100 / 97  258 / 190 69 / 50  271 / 186 152 / 104 184 / 163  104 / 53  160 / 171 Hourly volume range  28–769  8–340  1–846  1–205  18–769  7–500  1–731  21–283  7–963  Nighttime hours  4  5  35  2  0  23  28  4  22  Rain hours  0  10  31  3  0  5  3  3  33  Cold hours (<30 °F)  6  0  7  0  0  3  9  0  0  Hot hours (>90 °F)  0  0  15  0  0  4  4  10  3  Thunder hours  0  1  8  0  0  1  1  3  4 

Next: Chapter 3: Combined Findings from Phases 1 and 2 »
Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2 Get This Book
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TRB's National Cooperative Highway Research Program (NCHRP) Web-Only Document 229: Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2 explores automated count technologies that capture pedestrian and bicycle volume data. The publication focuses on technologies that came onto the market too late to be included in previous Phase 1 research. Findings from Phase 1 are documented in NCHRP Report 797: Guidebook on Pedestrian and Bicycle Volume Data Collection and NCHRP Web-Only Document 205: Methods and Technologies for Pedestrian and Bicycle Volume Data Collection.

The report presents combined results for a range of technologies tested by both the Phase 1 research and the continuation research (Phase 2). The research evaluated automated nonmotorized count technologies in different settings, including ranges of temperature, varying weather conditions, mixed traffic conditions, mixed travel directions, and facility types (e.g., roadways, multiuse paths), to determine their accuracy and reliability in different contexts. This report documents the research findings on the accuracy and consistency found for the different automated count technologies. It provides an account of the process used to select technologies for testing, identifies test sites, and evaluates the effectiveness of the technologies.

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