Regional Bicycle and Pedestrian Count Summary Report

Transcription

1 2015 Regional Bicycle and Pedestrian Count Summary Report Prepared by PAG staff Published September 2016

2 Table of Contents Introduction and Overview... 1 This Report... 1 Process and Methodology... 2 Part 1: 2015 Counts Bicycle and Pedestrian Data Summary... 4 Bicycle Summary... 4 Pedestrian Summary Count Data by Intersections and Regional Locations... 7 Bicycle Data... 7 Pedestrian Data...11 Part 2: Comparisons with Previous Years and 2015 Bicyclist Attributes through 2015 Bicyclist Attributes through 2015 Pedestrian Counts...18 Unlawful Behaviors...21 Other Factors...23 Conclusion...23 Appendix A 2015 Data and Bicyclist Attributes: Top 10s...25 Female Ridership...25 Age Ranges...27 Safety Considerations...30 Helmet Use...30 Wrong-Way and Sidewalk Riding...33 Appendix B Data and Bicyclist Attributes: Rolling Average Trends...40 Appendix C Count Tally Sheet...44 Appendix D Count Reference Sheet...45

3 List of Figures Figure 1. Phases in the PAG Regional Bicycle and Pedestrian Count coordination process Figure bicycle and pedestrian count locations and sub-regions Figure bicycle count volumes by sub-region Figure 4. Percentage of 2015 pedestrians per count location and grouped by sub-region Figure pedestrian count volumes by count location Figure 6. Total bicycle counts at 39 locations from 2011 to Figure 7. Bicycle count percent change: 2015 compared to previous five-year average at 39 core locations Figure 8. Total bicycle counts at 39 locations from 2011 to Figure 9. Pedestrian rolling average Figure 10. Pedestrian count percent change: 2015 compared to previous five-year average at 39 core locations Figure 11. Unlawful riding behavior hot spots Figure A top 10 female ridership locations, by percentage Figure A top 10 female ridership locations, by count Figure A percent female riders by location Figure A top 10 locations with bicyclists under 18, by percentage Figure A top 10 locations with bicyclists under 18, by count Figure A top 10 locations with bicyclists over 65, by percentage Figure A top 10 locations with bicyclists over 65, by count Figure A bicycle count age range percentages by location Figure A top 10 locations for non-helmet use, by percentage Figure A top 10 locations for non-helmet use, by count Figure A non-helmet wearing bicyclist percentage ranges by location Figure A top 10 locations for helmet use, by percentage Figure A top 10 locations for helmet use, by count Figure A top 10 locations with wrong-way riding, by percentage Figure A top 10 locations with wrong-way riding, by count Figure A percentage of wrong-way riders per count site Figure A top 10 locations with sidewalk riders, by percentage Figure A top 10 locations with sidewalk riders, by count Figure A percentage of sidewalk riders by count site Figure B1. Bicyclist gender by 3-year rolling average Figure B2. Bicyclist age by 3-year rolling average Figure B3. Bicyclist helmet usage by 3-year rolling average Figure B4. Bicyclist unlawful riding behavior by 3-year rolling average List of Tables Table 1. Summary of 2015 bicycle count data Table 2. Top 10 bicyclist count locations, Table 3. Top 10 pedestrian count locations, Table bicycle count totals grouped by sub-region Table bicycle count attributes averaged by the number of count locations in each sub-region Table bicycle count attribute percentages summarized by sub-region Table bicycle count results ranked by attribute percentages per sub-region Table pedestrian summary information by sub-region Table 9. Comparison between 2014 and 2015 bicycle count data at 46 locations Table 10. Five-year averages and attribute percentages for 39 core locations Table 11. Five-year ( ) previous averages compared with 2015 data at 39 core locations Table 12. Bicycle count totals at 39 core locations, with 2015 totals compared with the previous five-year average ( ) Table 13. Pedestrian count totals at 39 core locations, with 2015 totals compared with the previous fiveyear average ( ) Table 14. Total bicyclists at core locations, by year, with data from possible influencing factors

4 Introduction and Overview With time and dedication of many volunteers and support of member jurisdictions, Pima Association of Governments (PAG) has coordinated the annual bicycle count since This effort helps regional planning efforts in several ways, including: Planning and evaluation: The count helps track numbers and trends of bicyclists and pedestrians over time, which helps in the assessment and evaluation of bicycle projects and programs. Prioritizing locations to improve: For example, high rates of wrong-way riding in a location can suggest a need for an engineering solution. Analyzing crash data: Combining police incident data with other site-specific information, such as volume of riders, helps us to better understand problems at crash locations. Raising awareness: The annual count helps to educate community members about bicycle and pedestrian characteristics and trends. Count Summary Report This count summary report looks at the data collected in 2015 in addition to previously collected data. These data are presented in a variety of ways in order to maximize their usefulness. Part 1 of this report looks at all the count locations from This section provides an overview of current bicycle and pedestrian use across the region from all 101 count locations included in 2015, but it is not meant for year-over-year comparisons. Part 2 is useful for year-over-year comparisons. This section starts with a summary of all 46 collection locations that were common to years 2014 and Part 2 continues with comparisons at core count locations, which are locations that have been consistently observed since 2008 for bicyclists and since 2010 for pedestrians. Appendix A includes charts highlighting the top 10 observed locations in 2015 for each of the attributes collected for bicyclists. These are accompanied with maps depicting the relative distribution of each attribute across the region. Appendix A also lists all 2015 weekday and weekend count locations, and lists the change from 2014 where appropriate. Appendix B summarizes bicyclist and pedestrian counts including the bicyclist attributes using rolling averages for comparison over time. Appendices C and D include materials that were used during the 2015 count for reference.

5 Process and Methodology The PAG Regional Bicycle and Pedestrian Count is scheduled annually for two weeks in October, when weather conditions are generally favorable for bicycle and pedestrian activity. Weekday counts occur during peak period hours on either a Tuesday, Wednesday or Thursday in the morning and late afternoon, from 7:00 to 9:00 a.m. and from 4:00 to 6:00 p.m. Weekend counts occur on either a Saturday or Sunday in the morning from 7:00 to 10:00 a.m. The count is principally a volunteer effort with PAG assisting as a technical resource and event coordinator. The count methodology, as described above, is consistent with general transportation engineering guidelines while tailored for bicyclists and pedestrians. In the weeks prior to the count, PAG recruits volunteers. This effort includes sharing instructions for using the PAG web map to sign up. First-time counters are required to attend a brief training conducted by PAG staff. An illustration of the count coordination process can be seen in Figure 1 on Page 3. Using a tally sheet (Appendix C), counters record the number of bicyclists and pedestrians that use an intersection at 15-minute increments during each two-hour count shift. For bicyclists, additional attributes are recorded, including whether a bicyclist is female, the estimated age range, and if the bicyclist is wearing a helmet, riding the wrong-way on the street, or riding on the sidewalk. These attributes help transportation planners and others to better understand bicyclist demographic and safety characteristics. For more on the details on the directions provided to volunteer counters see Appendix D.

6 Volunteer recruitment and training phase PAG distributes flier to recruit volunteers Volunteers sign up using web map Volunteers attend a brief training session Bicycle and pedestrian count phase Volunteers go to designated locations to count Count sheets are completed and then returned to PAG Data input and report creation phase Count sheet data are entered into databaseready tables Database is connected to ArcGIS and MS Excel for map, chart and table creation Regional Bicycle and Pedestrian Report is completed Figure 1. Phases in the PAG Regional Bicycle and Pedestrian Count coordination process.

7 Part 1: 2015 Counts 2015 Bicycle and Pedestrian Data Summary Bicycle Summary At 101 locations throughout the jurisdictions of eastern Pima County (Figure 2), 12,778 bicyclists were counted in As listed in Table 1, over 70 percent of the bicyclists were male, and over half of the bicyclists counted were wearing helmets. Table 1. Summary of 2015 bicycle count data. Attribute Total Percentage of Total Total Bicyclists 12, % Female Bicyclists 3,429 27% Male Bicyclists 9,349 73% Bicyclists under % Bicyclists between 18 & 65 10,919 85% Bicyclists over 65 1,115 9% Helmet Wearers 7,073 55% No Helmet 5,705 45% Wrong-way Bicyclists 424 3% Sidewalk Bicyclists 719 6% As shown in Table 2, five of the101 locations had over 500 bicyclists during the four hours of the count (two hours in the morning and two in the afternoon). This is down from 10 locations over 500 in 2014 but consistent with 2013 volumes. In general, the 2015 count volumes are lower than previous years. This may be a result of an unusual amount of precipitation during the collection window. See Table 14 on page 23 for more details. Of the 10 locations with the highest volumes, the top five were near the University of Arizona (UA). Table 2. Top 10 bicyclist count locations, Location 2015 Rank Total Bicyclists Park Ave / University Blvd 1 1,008 3rd St / Campbell Ave nd St / Highland Ave Helen St / Mountain Ave th St / Highland Ave Rillito Pathway / Swan Rd La Cañada Dr / Moore Rd Blacklidge Dr / Mountain Ave Dove Mountain Blvd / Moore Rd Stone Ave / University Blvd

8 Figure bicycle and pedestrian count locations and sub-regions.

9 Pedestrian Summary Pedestrians also are tallied at the same count locations as bicycles, although no additional attributes are collected. In 2015, 20,458 pedestrians were counted at 101 locations. Of the top 10 highest volume pedestrian locations listed in Table 3, eight are located near the University of Arizona, and two are in downtown Tucson locations in the Top 10 list. The highest volume locations require two people to count simultaneously and are usually conducted by experienced counters. In 2015, the Park Ave./University Blvd. location had the highest volume (see Table 3), with 3,229 pedestrians counted over four hours. This averages to over 800 pedestrians per hour, or approximately 200 per 15-minute count interval. Table 3. Top 10 pedestrian count locations, Location 2015 Rank Total Pedestrians Park Ave / University Blvd 1 3,229 2nd St / Highland Ave 2 2,774 6th St / Highland Ave 3 2,650 Council St / Stone Ave Helen St / Mountain Ave Congress St / Granada Ave th St / Cherry Ave Mabel St / Warren Ave rd St / Campbell Ave Cherry Ave / Speedway Blvd

10 Totals per sub-region 2015 Count Data by Intersections and Regional Locations As in previous years, the count locations are grouped into six sub-regions for purposes of geographic comparison. These include the UA area, downtown, urban core, north and northwest, Green Valley/Sahuarita and eastside. Since the count requires the time of many volunteers, the locations where counts occur vary from year to year based upon where volunteers choose to conduct counts. However, efforts are made to recruit volunteers to count at the highest priority locations first. As volunteers sign up for these locations, additional locations are made available based upon volunteer demand. Priority count locations are determined by PAG staff with input from the PAG jurisdictions. Locations that have been counted every year are considered high priority because the data can provide insights into possible trends over time. Bicycle Data Within these sub-regions, more count locations have been established where population density is highest and, as a result, the number of count locations per sub-region is variable. Therefore, the tables below organize the data in different ways to show not only the total volumes and attribute values per sub-region, but also the number of count locations within the sub-region. For example, Table 4 shows the north and northwest sub-regions having significantly more cyclists than the east sub-region. For 2015, 2,108 cyclists were counted in the north and northwest and only 522 counted in the east sub-region. However, the north and northwest sub-region also had several more count locations than the east sub-region, which partially explains why more cyclists were counted in the north and northwest sub-regions. When the average number of cyclists is calculated per count location (as seen in Table 5), the north and northwest and the east sub-regions are very similar in number, 96 and 104 respectively. Table bicycle count totals grouped by sub-region. Attributes Downtown East Green Valley / Sahuarita North and NW UA Urban Core Total Bicyclists Count Locations Per Region Female Bicyclists Male Bicyclists Bicyclists under Age 18 to 65 Bicyclists Bicyclists over Helmet Wearers No Helmet Wrong-way Bicyclists Sidewalk Bicyclists

11 Percent Average per Location Considering the bicyclist attributes on a per location basis, Table 5 shows that the UA subregion had the most bicyclists per location and, as a result, also had the highest values in several of the attributes including females, males, helmet wearers and non-helmet wearers. Total Bicyclists Female Bicyclists Male Bicyclists Bicyclists under Age 18 to 65 Bicyclists Bicyclists over Helmet Wearers Non-Helmet Wearers Wrong-way Riders Sidewalk Riders Organizing the attribute data in each sub-region by percentages provides a different perspective. Table 6 shows the percentage of each sub-region s attributes based on the totals for that sub-region. This allows for rate comparisons which can then be paired with count volume for more insight. For example, Table 6 shows that the UA sub-region had the highest percentage of female riders as compared across sub-regions. In addition, nearly all bicyclists in the UA sub-region (97%) were between the ages of 18 to 65. Table bicycle count attribute percentages summarized by sub-region. Attributes Table bicycle count attributes averaged by the number of count locations in each sub-region. Green Attributes Downtown East Valley / Sahuarita North and NW UA Urban Core Downtown East Green Valley / Sahuarita North and NW UA Urban Core Total Bicyclists 10% 3% 1% 12% 24% 21% Female Bicyclists 26% 23% 17% 24% 32% 23% Male Bicyclists 74% 77% 83% 76% 68% 77% Bicyclists under 18 14% 3% 7% 6% 1% 8% Age 18 to 65 Bicyclists 73% 85% 34% 86% 97% 79% Bicyclists over 65 12% 11% 59% 9% 2% 13% Helmet Wearers 44% 84% 83% 92% 33% 62% Non-Helmet Wearers 56% 16% 17% 8% 67% 38% Wrong-way Riders 5% 3% 5% 2% 3% 3% Sidewalk Riders 8% 6% 5% 5% 4% 6%

12 Rank (by Percent) As a supplement to the percentages in Table 6, Table 7 lists the ranks of these percentages. For example, the north and northwest sub-regions ranked first in helmet usage and lowest in wrong-way riders. Table bicycle count results ranked by attribute percentages per sub-region. Attributes Downtown East Green Valley / Sahuarita North and NW Female Bicyclists Male Bicyclists Bicyclists under Age 18 to 65 Bicyclists Bicyclists over Helmet Wearers Non-Helmet Wearers Wrong-way Riders Sidewalk Riders UA Urban Core Figure 3, on page 10, shows the count volumes, by location and sub-region. For more details on regional comparisons of bicyclist attributes, Appendix A contains the top 10 locations, by volume and percentage.

13 Figure bicycle count volumes by sub-region.

14 Pedestrian Data In addition to counting bicyclists, volunteers also count pedestrians in 15-minute intervals at each of the count locations. As stated above, 20,458 pedestrians were counted in 2015 at 101 locations. Comparing the data across the six sub-regions (Table 8), the UA sub-region continues to have the highest number of total pedestrians and, by far, the highest number of pedestrians per count location. The high pedestrian volumes of the UA also are illustrated in Figure 4. It shows that 72 percent of the pedestrians were counted in this sub-region, with the remaining 38 percent counted in the other five sub-regions. Finally, Figure 5, on Page 12, shows the locations of the pedestrian counts, with symbols to indicate the relative volume at each. Table pedestrian summary information by sub-region. Attributes Downtown East Green Valley / Sahuarita North and NW UA Urban Core Grand Total Total Pedestrians 3, ,218 11,468 3,752 20,458 Number of Count Locations Pedestrians per Location , Figure 4. Percentage of 2015 pedestrians per count location and grouped by sub-region.

15 Figure pedestrian count volumes by count location.

16 Part 2: Comparisons with Previous Years 2014 and 2015 Bicyclist Attributes Forty-six locations were counted both in 2014 and The attribute data for these locations are summarized in Table 9. At these locations, the count showed an overall 16 percent decrease in the volume of bicyclists. Again, one possible reason for this decrease was the high amount of precipitation during the observation window. See Table 14 for more details on other factors that can influence this data collection effort. The ratio that each attribute contributes to the total volume remains relatively unchanged with no helmet riding showing the largest change from 53 percent in 2014 to 48 percent in Table 9. Comparison between 2014 and 2015 bicycle count data at 46 locations. Attribute Percent 2015 Percent Difference Percent Change Total Bicyclists 8,876 7, % Female Bicyclists 2,436 2,023 27% 27% % Male Bicyclists 6,440 5,434 73% 73% % Bicyclists under % 5% % Age 18 to 65 Bicyclists 8,227 6,611 93% 89% % Bicyclists over % 6% 57 14% Helmet Wearers 4,190 3,898 47% 52% % No Helmet 4,686 3,559 53% 48% % Wrong-way Riding Bicyclists % 3% % Sidewalk Riding Bicyclists % 5% 36 11% 2011 through 2015 Bicyclist Attributes Since 2008, volunteers have counted at the same 39 locations in the region. As Figure 6 on Page 14 shows, the average number of total bicyclists counted over the five years from 2011 to 2015 was 6,791 for these 39 locations, averaging slightly over 174 bicyclists per location. With 6,274 bicyclists counted in 2015, the total number was the slightly lower than average from the past five years.

17 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1, ,022 6,737 6,860 7,064 6, Figure 6. Total bicycle counts at 39 locations from 2011 to Table 10 serves as a reliability test of current year counts and also includes regional averages from the past six years. The data only consist of the 39 core locations. To check the reliability, the average and percent of the previous five years of data are included in the first two data columns. The next two columns, 2015 Count Totals and Percent of 2015 Count, are then compared to the values of the previous five years. This comparison illustrates that the 2015 count was neither anomalous in its total count nor for any of the attributes collected. The largest deviation from the previous five-year average is 4 percent, which occurred in the ratio of bicyclists between the ages of 18 and 65. This table also illustrates regional patterns in bicycle usage and behavior. The last two columns show the current five-year averages and percentages. In this time span, nearly three times as many male bicyclists were counted than female bicyclists (73% compared to 27%). Also, less than half the bicyclists were seen using helmets. Table 10. Five-year averages and attribute percentages for 39 core locations. Attributes Previous 5- year average ( ) Percentage of each attribute from the previous 5- year average 2015 Count Totals Percent of 2015 Count Current 5-year average ( ) Percentage of each attribute from the current 5- year average Total Bicyclists 6, % % 6, % Female Bicyclists 1,882 28% % 1,866 27% Male Bicyclists 4,957 72% % 4,925 73% Bicyclists under % 293 5% 191 3% Age 18 to 65 Bicyclists 6,484 95% % 6,398 94% Bicyclists over % 254 4% 202 3% Helmet Wearers 3,063 45% % 3,103 46% No Helmet 3,776 55% % 3,688 54% Wrong-way Bicyclists 188 3% 189 3% 184 3% Sidewalk Riding Bicyclists 367 5% 358 6% 357 5%

18 Table 11 and Figure 7 on Page 16 compare 2015 data at the core locations with the previous five-year averages ( ). The 2015 count saw a decline in the total number of cyclists at the 39 core locations. Therefore, the count shows a corresponding decrease in many of the attribute numbers. Three notable exceptions that had increases were bicyclists under the age of 18, over the age of 65 and wrong-way riding. Table 11. Five-year ( ) previous averages compared with 2015 data at 39 core locations. Attribute Previous 5-year average ( ) 2015 Percent Change from previous 5- year average Total Bicyclists 6,512 7,022 6,737 6,860 7,064 6,274 6,839-8% Female Bicyclists 1,809 1,937 1,734 2,047 1,884 1,730 1,882-8% Male Bicyclists 4,703 5,085 5,003 4,813 5,180 4,544 4,957-8% Bicyclists under % Age 18 to 65 Bicyclists 6,158 6,721 6,471 6,451 6,619 5,727 6,484-12% Bicyclists over % Helmet Wearers 2,720 3,171 3,097 3,059 3,268 2,922 3,063-5% No Helmet 3,792 3,851 3,640 3,801 3,796 3,352 3,776-11% Wrong-way Bicyclists % Sidewalk Bicyclists %

19 Figure 7. Bicycle count percent change: 2015 compared to previous five-year average at 39 core locations.

20 Table 12. Bicycle count totals at 39 core locations, with 2015 totals compared with the previous five-year average ( ). Location 2010 Total 2011 Total 2012 Total 2013 Total 2014 Total 2015 Total Previous 5-year average ( ) 2015 Percent Change (from previous 5- year average) 10th Ave / 43rd St % 18th St / 6th Ave % 1st Ave / Tangerine Rd % 22nd St / Kolb Rd % 3rd St / Campbell Ave % 3rd St / Swan Rd % 4th Ave / Lester St % 6th St / 9th Ave % 6th St / Highland Ave % 7th Ave / 7th St % Ajo Way / Mission Rd % Alvernon Way / Broadway Blvd % Alvernon Way / Ft Lowell Rd % Anklam Rd / St Mary's Rd % Arroyo Chico / Tucson Blvd % Aviation Hwy / Broadway Blvd - Snake Bridge % Blacklidge Dr / Mountain Ave % Broadway Blvd / Wilmot Rd % Camino del Sol / Continental Rd % Campbell Ave / Grant Rd % Campbell Ave / River Rd % Columbus Blvd / Pima St % Congress St / Granada Ave % Cortaro Rd / Silverbell Rd % Craycroft Rd / Golf Links Rd % Elm St / Tucson Blvd % Fairview Ave / Prince Rd % Glenn St / Treat Ave % Helen St / Mountain Ave % Ina Rd / Oracle Rd % Ironwood Hill Dr / Silverbell Rd % Kolb Rd / Tanque Verde Rd % La Cholla Blvd / River Rd % Park Ave / University Blvd % Rillito Pathway / Oracle Rd % River Rd / Sabino Canyon Rd % Santa Cruz Pathway / St Mary's Rd % Stone Ave / University Blvd % Sunrise Dr / Swan Rd %

21 2011 through 2015 Pedestrian Counts 2015 marks the sixth year of pedestrian data collection. The growth of this dataset now allows for comparison to previous years. Figure 8 presents the total pedestrian counts for the past five years at core locations. 12,000 10,000 8,000 6,000 4,000 2,000 0 Five-year Pedestrian Count Totals for 39 'Core' Locations (Average = 9,778) 8,748 9,367 9,481 Figure 8. Total bicycle counts at 39 locations from 2011 to ,415 10, Figure 9 presents one means of assessing trends across years with data that can be highly variable. A moving average takes a set number of years, in this case three, and averages the values for that time span which results in one data point. The process is repeated, advancing the beginning and end year for the average by one year until all years are included. This results in single year data being included in multiple averages, thereby reducing the variability for trend analysis (This same process is used in Appendix B with the bicycle attribute data). Following this method, the trend of pedestrian counts is positive. 12,000 Pedestrian 3-year Rolling Average: at 39 core locations 10,000 8,000 6,000 4,000 2, Figure 9. Pedestrian rolling average. Figure 10, on Page 19, displays the change in pedestrian volumes between the average and the 2015 counts. Table 13, on Page 20, displays this same pedestrian data in a table format. This table mimics Table 12, on Page 17.

22 Figure 10. Pedestrian count percent change: 2015 compared to previous five-year average at 39 core locations.

23 Table 13. Pedestrian count totals at 39 core locations, with 2015 totals compared with the previous fiveyear average ( ). Location Previous 5-year average ( ) 2015 Percent Change (from previous 5-year average) 10th Ave / 43rd St % 18th St / 6th Ave % 1st Ave / Tangerine Rd % 22nd St / Kolb Rd % 3rd St / Campbell Ave % 3rd St / Swan Rd % 4th Ave / Lester St % 6th St / 9th Ave % 6th St / Highland Ave % 7th Ave / 7th St % Ajo Way / Mission Rd % Alvernon Way / Broadway Blvd % Alvernon Way / Ft Lowell Rd % Anklam Rd / St Mary's Rd % Arroyo Chico / Tucson Blvd % Aviation Hwy / Broadway Blvd - Snake Bridge % Blacklidge Dr / Mountain Ave % Broadway Blvd / Wilmot Rd % Camino del Sol / Continental Rd % Campbell Ave / Grant Rd % Campbell Ave / River Rd % Columbus Blvd / Pima St % Congress St / Granada Ave % Cortaro Rd / Silverbell Rd % Craycroft Rd / Golf Links Rd % Elm St / Tucson Blvd % Fairview Ave / Prince Rd % Glenn St / Treat Ave % Helen St / Mountain Ave % Ina Rd / Oracle Rd % Ironwood Hill Dr / Silverbell Rd % Kolb Rd / Tanque Verde Rd % La Cholla Blvd / River Rd % Park Ave / University Blvd % Rillito Pathway / Oracle Rd % River Rd / Sabino Canyon Rd % Santa Cruz Pathway / St Mary's Rd % Stone Ave / University Blvd % Sunrise Dr / Swan Rd %

24 Unlawful Behaviors In addition to being unlawful, certain bicycling actions or behaviors are safer than others. Crash history shows that riding on the wrong side of the street (opposing the flow of traffic) and riding on the sidewalk are two of the more inadvisable bicycling behaviors. This is the result of sidewalk and wrong-way bicyclists occupying space where drivers are not expecting to find them, resulting in less visibility for drivers and consequently shorter reaction times. Such behaviors also increase conflicts with pedestrians when riding on the sidewalk in addition to other fixed hazards. It is likely not the intent of a bicyclist to increase his or her danger by riding in these manners; it is more likely that other circumstances exist that are promoting these behaviors. These other circumstances could include a lack of bicycle facilities, a false perception of increased safety from high vehicle speeds, a high concentration of heavy/commercial vehicles or a popular destination with insufficient bicycle connectivity, among others. Figure 11 on Page 22 lists 30 observed locations with high incidence of sidewalk and wrong-way riding.

25 Figure 11. Unlawful riding behavior hot spots.

26 Other Factors As in previous reports, we continue to gather data from several other sources that may provide insights into bicycle volumes from year to year. Table 13 lists October average low and high temperatures, average retail gas prices and unemployment rates. It also lists population estimates both for Pima County and the UA student body. Table 14. Total bicyclists at core locations, by year, with data from possible influencing factors. Tucson Average October Low Temp. 1 Tucson Average October High Temp. 1 Tucson Total Precipitation for October 1 Average U.S. Retail Gas Price October 2 Tucson MSA Unemploy -ment Rate in October 3 Population Estimates for Pima County 4 University of Arizona Student Population 5 Total* Year Biyclists , Trace $ ,032 37, , $ ,274 38, , $ ,168 39, , $ ,081 39, , Trace $ ,380 40, , $ ,046 40, , $ ,007,162 42, , $ ,009,371 43,088 *Total bicyclists from 39 core locations collected every year 1 National Weather Service Forecast Office, Tucson, AZ. Monthly climate reports and F-6 data for Tucson AZ. Accessed at: 2 U.S. Energy Information Administration. U.S. Regular Conventional Retail Gasoline Prices. Accessed at: 3 Arizona Dept. of Administration, Office of Employment and Population Statistics. Local Area Unemployment Statistics. Accessed at: 4 Arizona Dept. of Administration, Office of Employment and Population Statistics. Census Data and Population Estimates. Accessed at: 5 University of Arizona Analytics and Institutional Research, student data. Accessed at: Demographics

27 Conclusion Each year, the PAG Regional Bicycle and Pedestrian Count contributes to the expanding dataset of biking and walking behaviors in the region. Preserving the accuracy of datasets is an ongoing challenge met with real-time and resource constraints. Trained volunteers enable an extensive count each year. Data collection protocols, including mandatory trainings, help ensure data quality. In order to further ensure its accuracy, the data should be paired with other data to achieve the maximum benefit and use from any dataset. Other sources that can complement this data include the National Household Travel Survey and the American Community Survey. The PAG Regional Bicycle and Pedestrian Count continues to be an important resource to planners and stakeholders by providing key data on bicycle and pedestrian activity within eastern Pima County. PAG staff members thank the community, jurisdiction volunteers and partners for making this effort possible. PAG staff will continue to work with jurisdictional representatives and stakeholders to conduct counts in high priority areas that will benefit the region.

28 Appendix A 2015 Data and Bicyclist Attributes: Top 10s Female Ridership Top 10 locations with highest percentage of female bicyclists 60% 50% 40% 50% 43% 43% 41% 39% 38% 37% 36% 36% 35% 30% 20% 10% 0% Lee St / Sahuara Ave Coachline Blvd / Twin Peaks Rd Pantano Pathway / Speedway Blvd 4th Ave / Speedway Blvd Mabel St / Warren Ave Cortaro Rd / Silverbell Rd Santa Cruz Pathway / St Mary's Rd 3rd St / Campbell Ave Ina Rd / Thornydale Rd Tangarine Rd / Thornydale Rd Figure A top 10 female ridership locations, by percentage. Top 10 locations with the highest number of female bicyclists Park Ave / University Blvd 3rd St / Campbell Ave 2nd St / 6th St / Highland Ave Highland Ave Helen St / Mountain Ave Rillito Pathway / Swan Rd Stone Ave / University Blvd Dove Mountain Blvd / Moore Rd La CañadaDr / Moore Rd La Cañada Dr / Naranja Dr Figure A top 10 female ridership locations, by count.

29 Figure A percent female riders by location.

30 Age Ranges Top 10 locations with highest percentage of bicyclists under 18 years of age 120% 100% 80% 96% 78% 60% 40% 20% 52% 52% 50% 48% 48% 41% 40% 37% 0% Congress St / Toole Ave Cortaro Rd / Silverbell Rd Elm St / Treat Ave Santa Cruz Pathway / St Mary's Rd Pima Mine Rd / Rancho Sahuarita Blvd 4th Ave / Speedway Blvd Lee St / Sahuara Ave 22nd St / Park Ave Alameda St / Church Ave Palo Verde Blvd / Seneca St Figure A top 10 locations with bicyclists under 18, by percentage Cortaro Rd / Silverbell Rd Top 10 locations with the highest number of bicyclists under 18 years of age 78 4th Ave / Speedway Blvd 56 Santa Cruz Pathway / St Mary's Rd 45 Elm St / Treat Ave Lee St / Congress St / Sahuara Ave Toole Ave Stone Ave / University Blvd Anklam Rd / Aviation Hwy Alameda St / St Mary's Rd / Broadway Church Ave Blvd - Snake Bridge Figure A top 10 locations with bicyclists under 18, by count.

31 Top 10 locations with highest percentage of bicyclists over 65 years of age 120% 100% 80% 95% 83% 75% 60% 40% 50% 49% 43% 35% 33% 31% 31% 20% 0% Camino del Sol / Continental Rd Drachman St / Stone Ave Broadway Blvd / Wilmot Rd 4th Ave / Speedway Blvd Duval Mine Rd / La Cañada Dr Santa Cruz Pathway / St Mary's Rd CDO Linear Park / La Cañada Dr Pima Mine Rd / Rancho Sahuarita Blvd 18th St / Plumer Ave Dodge Blvd / Pima St Figure A top 10 locations with bicyclists over 65, by percentage. Top 10 locations with the highest number of bicyclists over 65 years of age Rillito Pathway / Swan Rd Drachman St / Stone Ave 4th Ave / Speedway Blvd Santa Cruz Pathway / El Camino del Cerro Santa Cruz Pathway / St Mary's Rd Freeman Rd / Old Spanish Trail Blacklidge Dr / Mountain Ave Broadway Blvd / Wilmot Rd La Cañada Dr / Moore Rd Duval Mine Rd / La Cañada Dr Figure A top 10 locations with bicyclists over 65, by count.

32 Figure A bicycle count age range percentages by location.

33 Safety Considerations Helmet Use 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Top 10 locations with highest percentages of bicyclists not wearing helmets 100% 15th Ave / Kelso St 85% 84% 83% 81% 81% 79% 78% 78% 78% 1st St / Euclid Ave 6th St / Cherry Ave 4th Ave / Speedway Blvd Kolb Rd / Tanque Verde Rd Santa Cruz Pathway / Irvington Rd 6th St / Highland Ave Fairview Ave / Prince Rd 2nd St / Santa Cruz Highland Ave Pathway / St Mary's Rd Figure A top 10 locations for non-helmet use, by percentage. Top 10 locations with the highest number of bicyclists not wearing helmets Park Ave / University Blvd 546 2nd St / Highland Ave 516 3rd St / Campbell Ave 423 6th St / Highland Ave 341 Helen St / Mountain Ave Kolb Rd / Tanque Verde Rd Rillito Pathway / Oracle Rd 4th Ave / Speedway Blvd Stone Ave / University Blvd 1st St / Euclid Ave Figure A top 10 locations for non-helmet use, by count.

34 Figure A non-helmet wearing bicyclist percentage ranges by location.

35 100% 99% 98% 97% 96% 95% 94% 93% 92% Top 10 locations with highest percentage of bicyclists wearing helmets 100% 100% Cortaro Rd / Silverbell Rd Tangerine Rd / Twin Peaks Rd / Dove Mtn Blvd 98% La Cañada Dr / Moore Rd 97% 97% Freeman Rd Nogales Hwy / Old Spanish / Old Nogales Trail Hwy 96% 96% Dove Mountain Blvd / Moore Rd Freeman Rd / Old Spanish Trail 95% 95% 95% Santa Cruz Pathway / El Camino del Cerro River Rd / Sabino Canyon Rd Dove Mountain Blvd / Moore Rd Figure A top 10 locations for helmet use, by percentage. Top 10 locations with the highest number of bicyclists wearing helmets rd St / Campbell Ave Rillito Pathway / Swan Rd Park Ave / University Blvd 327 La Cañada Dr / Moore Rd Dove Mountain Blvd / Moore Rd Santa Cruz Pathway / El Camino del Cerro La Cañada Dr / Naranja Dr Freeman Rd / Old Spanish Trail Helen St / Mountain Ave 204 Tangerine Rd / Twin Peaks Rd / Dove Mtn Blvd Figure A top 10 locations for helmet use, by count.

36 Wrong-Way and Sidewalk Riding 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 42% Pima Mine Rd / Rancho Sahuarita Blvd Top 10 locations with highest percentage of bicyclists riding the wrong way 31% 18th St / Plumer Ave 24% 10th Ave / 43rd St 22% 20% 20% 19% 19% 22nd St / Park Ave 22nd St / Kolb Rd 9th St / Euclid Ave Santa Cruz Pathway / Irvington Rd Alameda St / Church Ave 16% 14% Broadway Blvd / Wilmot Rd 6th St / Cherry Ave Figure A top 10 locations with wrong-way riding, by percentage Top 10 locations with the highest number of bicyclist riding the wrong way nd St / 6th St / Highland Ave Highland Ave 28 9th St / Euclid Ave 16 4th Ave / Speedway Blvd Park Ave / University Blvd 6th St / Cherry Ave Cherry Ave / Speedway Blvd 22nd St / Kolb Rd Kolb Rd / Tanque Verde Rd Columbus Blvd / Pima St Figure A top 10 locations with wrong-way riding, by count.

37 Figure A percentage of wrong-way riders per count site.

38 Top 10 locations with highest percentage of bicyclists riding on the sidewalk 60% 50% 52% 46% 40% 30% 42% 41% 39% 37% 37% 37% 33% 29% 20% 10% 0% Santa Cruz Pathway / Irvington Rd 6th St / Cherry Ave Pima Mine Rd / Rancho Sahuarita Blvd 22nd St / Park Ave CDO Linear Park / La Cañada Dr 9th St / Euclid Ave 22nd St / Kolb Rd River Rd / Sabino Canyon Rd Alvernon Way / Ft Lowell Rd Council St / Stone Ave Figure A top 10 locations with sidewalk riders, by percentage. Top 10 locations with the highest number of bicyclists riding on the sidewalk th St / Euclid Ave 6th St / Highland Ave 6th St / Cherry Ave Cortaro Rd / Silverbell Rd 3rd St / Campbell Ave Cherry Ave / Speedway Blvd 22nd St / Kolb Rd Council St / Stone Ave CDO Linear Park / La Cañada Dr Campbell Ave / Grant Rd Figure A top 10 locations with sidewalk riders, by count.

39 Figure A percentage of sidewalk riders by count site.

40 Table A top 50 weekday bicycle count locations by total compared with 2014 totals Total 2014 Total 2015 Rank Change ( ) Percent Change [( )/2014] Location Park Ave / University Blvd % 3rd St / Campbell Ave % 2nd St / Highland Ave % Helen St / Mountain Ave % 6th St / Highland Ave % Blacklidge Dr / Mountain Ave % Stone Ave / University Blvd % Rillito Pathway / Oracle Rd % Kolb Rd / Tanque Verde Rd % Santa Cruz Pathway / St Mary's Rd % Speedway Blvd / Treat Ave N/A N/A Campbell Ave / Grant Rd % Cherry Ave / Speedway Blvd % Mabel St / Warren Ave % Drachman St / Park Ave % 9th St / Euclid Ave % Aviation Hwy / Broadway Blvd - Snake Bridge % 1st St / Euclid Ave % Glenn St / Treat Ave % Alvernon Way / Dodge Blvd % Drachman St / Stone Ave % Freeman Rd / Old Spanish Trail N/A N/A Columbus Blvd / Pima St % La Cañada Dr / Moore Rd % Cortaro Rd / Silverbell Rd % 7th Ave / 7th St % 4th Ave / Speedway Blvd % Elm St / Tucson Blvd % 6th St / Cherry Ave % Congress St / Granada Ave % Santa Cruz Pathway / Commerce Dr % 1st Ave / Tangerine Rd % Fontana Ave / Glenn St % Anklam Rd / St Mary's Rd % 6th St / 9th Ave %

41 Table A top 50 weekday bicycle count locations by total compared with 2014 totals (continued) Total 2014 Total 2015 Rank Change ( ) Percent Change [( )/2014] Location La Cholla Blvd / River Rd % Council St / Stone Ave % Alvernon Way / Broadway Blvd % Speedway Blvd / Whole Foods crosswalk % 4th Ave / Lester St % Ina Rd / Oracle Rd % Lee St / Sahuara Ave N/A N/A Dove Mountain Blvd / Moore Rd N/A N/A 22nd St / Kolb Rd % 18th St / 6th Ave % Pantano Pathway / Speedway Blvd N/A N/A Roger Rd / Stone Ave N/A N/A Campbell Ave / River Rd % CDO Linear Park / La Cañada Dr % Craycroft Rd / Golf Links Rd %

42 Table A weekend bicycle count locations ranked by total and compared with 2014 totals Total 2014 Total 2015 Rank Change ( ) Percent Change (( )/2014) Location Rillito Pathway / Swan Rd % La Cañada Dr / Moore Rd % Dove Mountain Blvd / Moore Rd N/A N/A La Cañada Dr / Naranja Dr N/A N/A Santa Cruz Pathway / El Camino del Cerro % Freeman Rd / Old Spanish Trail % Tangerine Rd / Twin Peaks Rd / Dove Mtn Blvd % 1st Ave / Tangerine Rd % 4th Ave / Speedway Blvd % Rillito Pathway / Oracle Rd % 4th Ave / 9th St N/A N/A Santa Cruz Pathway / St Mary's Rd % Elm St / Treat Ave N/A N/A Blacklidge Dr / Mountain Ave % 3rd St / Country Club Rd % Camino de Oeste / Gates Pass Rd N/A N/A Ina Rd / Thornydale Rd % Tangarine Rd / Thornydale Rd % Camino Campestre / Randolph Way (Reid Park SUP) % Coachline Blvd / Twin Peaks Rd % Congress St / Scott Ave % Nogales Hwy / Old Nogales Hwy N/A N/A Congress St / Toole Ave % Campbell Ave / Grant Rd N/A N/A 16th St / 3rd Ave % 15th Ave / Kelso St N/A N/A Cortaro Rd / Silverbell Rd N/A N/A

43 Appendix B Data and Bicyclist Attributes: Rolling Average Trends Many efforts are made to reduce year-to-year fluctuation in this counting effort. These include counting during the same time period, scheduling around regionally significant events, counting during seasonally typical weather conditions, to name a few. Nevertheless, data that is collected on a once per annum basis can be subject to variability. A technique that further reduces that fluctuation and facilitates understanding of trends is the rolling average. In essence, this approach takes a series of years, in this case three, and averages them together to arrive at one value, then shifts that series one year later and takes the average again. The following charts show the rolling average which includes average of the following series: , , , , and This approach was applied to the 39 core locations that have been included in the count since Figure B1. Bicyclist gender by 3-year rolling average.

44 Figure B2. Bicyclist age by 3-year rolling average.

45 Figure B3. Bicyclist helmet usage by 3-year rolling average.

46 Figure B4. Bicyclist unlawful riding behavior by 3-year rolling average.

47 Appendix C Count Tally Sheet

48 Appendix D Count Reference Sheet