Results from the 2009 City of Los Angeles Bicycle and Pedestrian Count

Results from the 2009 City of Los Angeles Bicycle and Pedestrian Count

Table of Contents Executive Summary 2 About the Los Angeles County Bicycle Coalition 3 2009 Bicycle and Pedestrian Count Objectives 3 Summary of Methodology 3 Meetings with City Staff 4 Number of Count Locations 4 Count Location Criteria 4 Table 1 5 Map 1 6 Count Dates and Times 7 Count Methodology/Materials 7 Summary of Count Data 7 Plans for Future Counts 14 Appendix: Count Data Tables, Maps and Forms 15 Tables 15 Maps 37 Forms 43 Acknowledgements LACBC would like to thank the staff and volunteers who made the Count and this report possible. This project could not have been done without the organizing vision of Yogi Hendlin, Alexis Lantz, Rye Baerg, Herbie Huff, Vicki Karlan, and Carol Feucht. We want to thank our staff, Dorothy Le and Juliet Marshall. Thanks go to Zach Elgart for working on the LA Count Blog. www.labikecount.wordpress.com Thanks to Robin Wisser who designed our logo and to Dawn Amadeo for proofing this report. Thanks to the LACBC Planning and Advocacy Committee for providing us with support and advice. Thanks to the National Bicycle and Pedestrian Documentation Project, Alta Planning and Design, and Ryan Snyder for providing us critical resources and advice to conduct a thorough and duplicable count. Thanks to Councilmember Bill Rosendahl and his staff for being supportive of the counts and attending our press conference. Thanks to the City of Los Angeles Department of Transportation bicycle and survey staff for providing us advice for the counts. We hope this data will empower the City to provide better infrastructure for cyclists and pedestrians. Also we want to acknowledge all the count volunteers and office interns who collected, processed and organized the data. Thanks to the press and others who spread the word about the project. For everyone who was involved, we really could not have done it without you! Visit www.labikecount.org and www.labikecount.wordpress.com for more information 1

Executive Summary The Los Angeles Bicycle and Pedestrian Count ( Count ) conducted by the Los Angeles County Bicycle Coalition (LACBC) in September 2009 demonstrates that bicyclists and pedestrians throughout the City of Los Angeles use our public streets and sidewalks for daily transportation, recreation and other purposes. The City of Los Angeles has not conducted pedestrian or bicycle counts in recent history. LACBC recognized a need to address the lack of data about pedestrian and cyclist public space usage and responded by organizing the first volunteer-directed Count. The Count was conducted in order to raise public awareness about the needs of this often overlooked population and to begin to enumerate the volume of cyclists and pedestrians at intersections across the City of Los Angeles on a typical day. The Los Angeles Bicycle and Pedestrian Count was organized by several graduate students from UCLA s Departments of Urban Planning and Political Science, with additional key support from LACBC staff and volunteers. Working together, LACBC convened over 100 volunteers who contributed over 1000 volunteer hours to conduct counts at 50 intersections over the course of two weekdays (morning and evening commute for each day) and one weekend day. The counts captured 14,222 cyclists and 62,275 pedestrians. Just like automobile users, cyclists and pedestrians use public streets to commute, to run errands, to visit friends, and to enjoy Los Angeles. The Count data creates an important baseline that can be used for evaluating education, engineering, encouragement and enforcement efforts. In addition it allows monitoring usage for comparison with future counts and for projecting future demands. The methodology used adopts the approach developed by the National Bicycle and Pedestrian Documentation Project (NBPD), which aims to establish consistent national bicycle and pedestrian count and survey methodologies and to generate a national database of bicycle and pedestrian count information. Variations were made to accommodate the City of Los Angeles needs. Moving forward, LACBC would like to conduct bicycle counts in partnership with the City of Los Angeles on an annual or biannual basis in order to capture the effects of changes in infrastructure, attitudes, the economy and other trends on patterns of public thoroughfare use among cyclists and pedestrians in the City of Los Angeles. 2

About the Los Angeles County Bicycle Coalition Founded in 1998, the Los Angeles County Bicycle Coalition (LACBC) is a nonprofit membership-supported working to create a more bicycle-friendly Los Angeles County. The mission of LACBC is to improve the bicycling environment and as a result has expanded to include issues relating to pedestrian-friendly streets, all modes of alternative transportation, and urban planning policy in and around Los Angeles County. Through advocacy, education and outreach, LACBC brings together the diverse bicycling community in a united mission to make the entire L.A. region a safe and enjoyable place to ride. LACBC works with government agencies and political offices to improve bicycle-related policies in LA County, conducts bicycling-specific education classes, and organizes bicycle activities. Bicycle and Pedestrian Count Objectives The primary objective of the 2009 Los Angeles Bicycle and Pedestrian Count was to establish baseline data. Known as an auto-centric city, the City of Los Angeles has not actively prioritized people powered transportation options. LACBC hopes the City of Los Angeles and its engaged citizens will be empowered by the count data to provide much needed and better engineering, education, encouragement and enforcement in areas where cycling and walking are occurring. Future counts will measure the impact of such interventions for bicycling and walking. Detailed information collected regarding bicycling behavior also provides LACBC with insights that will inform safety and encouragement programs. Finally, these counts contribute to the National Bicycle and Pedestrian Documentation Project (NBPD), an ongoing effort to record bicycling and walking activities throughout the country. Summary of Methodology The Los Angeles Count methodology was based on the NBPD methodology, which was informed by the Institute of Transportation Engineers, other transportation professionals, and best practices nationwide. The core of the NBPD methodology includes: Consistent count days and times Consistent count methods and materials Centralized data collection and analysis Open access to all research professionals and public agencies The NBPD methodology was further customized for relevance at the local level by the LACBC, as described in the following sections. 3

Meetings with City of LA Department of Transportation Staff & Bicycle Advisory Committee The Bicycle Count team presented the project summary, methodology and process to the City of Los Angeles Bicycle Advisory Committee, whose members represent bicycle issues on behalf of LA City Council Districts. The team also met with city of Los Angeles staff from the ways and Survey Department of LADOT. We were able to obtain important feedback on our locations, methodology, and process. Specifically, LADOT expressed that directionality of bicyclists and pedestrians would be useful for them, and we added that component to the bicycle count forms. Number of Count Locations The National Pedestrian and Bicycle Documentation Project recommends conducting counts at one intersection for every 15,000 residents. Applied to the City of Los Angeles, with a population of 3,694,820 people according to the 2000 Census, this recommendation would require 246 locations, which was not feasible given existing resources. LACBC conducted an online survey targeting the informed cycling public as well as field research to identify 56 intersections. Sufficient numbers of volunteers were recruited to collect data during the five count periods at 50 intersections. Count Location Criteria Selection of count locations followed the criteria developed by the NBPD data collection and analysis program. This criteria includes: Pedestrian and bicycle activity areas or corridors (employment centers, near schools, parks, etc) Locations near proposed major bicycle/pedestrian improvements, particularly locations identified by the Draft Bicycle Plan and the Sharrows Pilot Program. Representative locations in the urbanized area Key corridors that can be used to gauge the impacts of future improvements Locations where bicycle collision numbers are high Table 1 provides a list of the Los Angeles Count locations. Map 1 on the following page illustrates the geographical distribution of these count locations throughout the City. 4

Location Number Table 1 Los Angeles Bicycle & Pedestrian Count Locations Intersection Location Number Intersection 1 1st & Alameda 26 Laurel Canyon & Ventura 2 1st & Soto 27 Lincoln & Bluff Creek 3 4th & Wilton 28 Lincoln & Venice 4 7th & Figueroa 29 Long Beach & Los Flores 5 8th & La Brea 30 Los Feliz & Riverside 6 9th & Pacific 31 Manchester & Hoover 7 Adams & Normandie 32 National & Overland 8 Alvarado & 7th 33 PCH & Temescal Canyon 9 Ave 19 & N. Broadway 34 Reseda & Orange Line Station 10 Ballona Creek & Marvin Braude Path 35 Santa Monica & Highland 11 Broadway & Bridge 36 Santa Monica & Westwood 12 Cesar Chavez & Soto 37 Santa Monica & Wilshire 13 Cypress Ave & 28th & Pepper 38 Sepulveda & Ohio 14 Eagle Rock & Colorado 39 Sunset & Hyperion 15 Echo Park & Sunset 40 Topanga & Burbank 16 Figueroa & Pasadena 41 Venice & National 17 Florence & Graham 42 Verdugo & Eagle Rock 18 Fountain & Vermont 43 Washington & Admiralty 19 Glendale & Park 44 Washington & Compton 20 Hollywood & Highland 45 Westholme & Wilshire 21 Hoover & McClintock 46 Westwood & Le Conte 22 Idaho & Bundy 47 Wilshire & Western 23 Kittridge & De Soto 48 Woodman & Orange Line Station 24 LA River @ Baum Bridge 49 Workman & Ave 26 25 Lankershim & Vineland 50 York & Ave 50 5

Map 1 Los Angeles Bicycle and Pedestrian Count Locations 6

Count Dates and Times NBPD methodology suggests performing counts during three key peak-travel periods: weekday morning, weekday evening, and weekend mid-day. LACBC followed this approach by conducting counts during five time periods over the course of three days: on Tuesday, September 22 nd at both 7:00-9:30 AM and 4:00-6:30 PM, Wednesday, September 23 rd at both 7:00-9:30 AM and 4:00-6:30 PM, and Saturday, September 26 th from 10:00 AM-1:00 PM. Count Methodology/Materials Just over 100 volunteer counters helped staff count locations. They used standardized count forms (see Appendix, Figure 1). Counters recorded volumes of pedestrians and bicyclists, direction of travel, and gender of bicyclists. Counters also recorded observations regarding bicycling behavior, including wrong-way riding, helmet use, and riding on the sidewalk. Direction of travel was specifically added due to the City of Los Angeles stated need for directionality. Summary of Count Data Data were collected at 50 count locations. However, LACBC was only able to obtain one morning, one evening and one weekend count at 25 of the locations. For purposes of simplicity and data comparability with the NBPD methodology, LACBC averaged data collected for a given intersection on Tuesday and Wednesday mornings to create a single weekday morning count for that intersection. In some cases averaging was not necessary because the intersection was only counted on one morning, either Tuesday or Wednesday. Similarly, if necessary LACBC averaged data from Tuesday and Wednesday evenings to create a single weekday evening count figure for a given intersection. The following analysis of cyclist and pedestrian counts by time periods, intersection infrastructure, and rider gender and behavior draws only upon the data from those 25 locations where data are complete. The remaining 25 locations without complete data are included in the Summary tables at the end of this report. Also, much of our data analysis is bicycle-centric, as this count was primarily oriented towards bicycling. In addition, when choosing intersections, LACBC gave priority to intersections where we expected to observe many bicyclists, and as a result our choices do not line up perfectly with the areas of the city where many people may walk. 7

Tables 2-4: Pedestrian & Bicyclist Count Data show the data collected at the 25 locations where complete counts were conducted. Key findings: 1. The ratio of cyclists to pedestrians was similar across all three time periods. There were greater numbers of cyclists and pedestrians during the 4:00-6:30 PM count than during the 7:00-9:30 AM count. The number of cyclists, counted during the weekend midday period exceeded cyclists counted during the weekday periods. Part of the reason for this is that Saturday counts lasted for 3 hours while weekday counts were only 2,5 hours in duration. 2. To better compare time periods, we divide by the duration of the count to calculate per-hour volumes of pedestrians and bicyclists. Citywide total per-hour volumes were 4,981 peds per hour (Weekday AM), 5,706 peds per hour (Weekday PM), and 5,473 peds per hour (Weekend). For bicyclists, citywide total per-hour volumes were 813 cyclists per hour (Weekday AM), 1,121 cyclists per hour (Weekday PM), and 972 cyclists per hour (Weekend). 3. When compared across the three time periods, pedestrians and bicyclists combined were most numerous during the weekday evening count taken from 4:00 6:30 PM. Figure 1. Total of Counts at the 25 Complete Intersections by Time Period 4. Summing up the counts for all three time periods, the greatest number of cyclists (1,683) were counted at the intersection of Washington & Admiralty in Marina del Rey. 5. Summing up the counts for all three time periods, the greatest number of pedestrians (6,792) were counted at the intersection of Westwood and Le Conte. 6. Of the 25 intersections in the study with complete data, the top ten busiest intersections based on the total number of cyclists counted summed across all three time periods were as follows: 8

1. Washington & Admiralty (1,683) 6. LA River & Baum Bridge (368) 2. Santa Monica & Westwood (429) 7. Venice & National (367) 3. Sepulveda & Ohio (421) 8. Alvarado & 7 th (344) 4. Westwood & Le Conte (418) 9. Wilshire &Western (343) 5. Sunset & Hyperion (380) 10. Fountain & Vermont (283) 7. Of the 25 intersections in the study with complete data, the top ten busiest intersections based on the total number of pedestrians counted summed across all three time periods were as follows: 1. Westwood and Le Conte (6,792) 6. Sunset & Hyperion (1,979) 2. Wilshire and Western (6,138) 7. Fountain & Vermont (1,746) 3. Alvarado & 7 th (5,985) 8. Washington & Compton (1.489) 4. Hollywood & Highland (5,202) 9. Santa Monica & Westwood (1,132) 5. Echo Park & Sunset (4,533) 10. Venice & National (904) Tables 5-7: Gender Breakdown shows the data collected relating to the gender of bicyclists observed during the Count. Key findings include: 1. As Figure 2 illustrates, higher percentages of women rode on the weekends. Women constituted 18% of riders counted on the weekend, while during the weekday mornings 14% of riders were women and during the weekday evenings 12% of riders counted were women. Over the entire Count, 15% of bicycle riders were women. 2. When gender distribution was compared across all 25 intersections with complete data, female ridership ranged from 0% at the Washington & Compton intersection to 34% for weekend mid-day at Lincoln & Bluff Creek. Figure 2: Gender Distribution of Cyclists for the Three Time Periods (25 intersections) 9

Tables 8-10: Bicycling Behavior provides a breakdown of bicycling behavior including: helmet use, wrong-way riding, and sidewalk riding. Key findings include: 1. Helmet use was highest during the morning period when 49% of riders wore helmets. During the weekend count period 46% of riders wore helmets while 40% wore them during the evening count. 2. Wide variation of helmet use was observed across intersections. The highest percentage of cyclists wearing helmets was observed at Sepulveda and Ohio on the weekend, at 82%. The Westholme and Wilshire AM count came in as a close second at 80%. The lowest percentage of cyclists wearing helmets was observed at Alvarado and 7 th in the morning, at 6%. Glendale and Park on the weekend had the second lowest percentage of riders wearing helmets, at 12%. 3. Overall only 3-4% of bicyclists were observed riding on the wrong side of the street. For the AM count, there were four intersections where every single cyclist counted rode on the correct side of the street. For the PM count, there were four such intersections, and for the weekend count there were eight such intersections. Again, this only includes the 25 intersections for which we had complete data. The highest percentages of wrong way riding were observed at Fountain and Vermont in the evening, at 20%, and at Washington and Compton on the weekend, at 22%. 4. Overall, about 22-29% of riders were observed riding on sidewalks. Sidewalk riding was most commonly observed during the evening count, with an average of 29%. Eighty-one percent (81%) of riders at Wilshire and Western in the evening rode on the sidewalk. There is an anomaly in the data for Alvarado and 7 th, which shows no sidewalk riding during in the evening count. Considering that 71% of riders at this intersection in the morning were on the sidewalk, and on the weekend 29% were on the sidewalk, the counter probably neglected to record sidewalk-riding data. Similarly, data from Figueroa and Pasadena intersection counted 0% sidewalk riding, but this is probably also a data error. In the morning, Sunset and Hyperion had the lowest rate of sidewalk riding, at 6%. In the evening, Sunset and Hyperion and 4 th and Wilton both had very low rates, 13% and 17% respectively. On the weekend, Sunset and Hyperion again had the lowest rate of sidewalk riding at 6%. 10

Table 11: Per-hour Volumes of Cyclists by Infrastructure Type explains some of the differences in bicyclist volumes at each location. The rightmost column indicates the type of infrastructure. 1 signifies that at least one of the directions features a Class I Path, which is an off-road facility. 2 signifies that at least one of the directions features a Class II Lane, and 3 signifies a Class III Route, which is a shared lane marked with signs. The table shows the correlation between the number of people bicycling and the type of bicycle infrastructure provided at the intersection. The top 7 intersections feature either Class I or Class II bikeways. Note that ridership at intersections with no bicycle infrastructure in many cases exceeds ridership at intersections with Class III Routes. In fact, LACBC observed per-hour volumes below the Count-wide average of 48 bicyclists per hour at all of the intersections with Class III Routes. The figure below color-codes Table 11 to illustrate the correlation between the number of bicyclists passing through the intersection and the type of infrastructure provided. Average numbers of cyclists passing per hour were greater than or equal to 48 at all of the intersections featuring bike lanes. Only two intersections with no infrastructure had per-hour volumes above the Count-wide average of 48, and these were Wilshire and Western and 7 th and Alvarado, which are both next to major transit stations and in densely populated areas. 11

Intersection Table 11 Avg. Cyclists / Hour Infrastructure Type Washington & Admiralty 259 1,2 Santa Monica & Westwood 66 2 Sepulveda & Ohio 65 1,3 Westwood & Le Conte 64 2 Sunset & Hyperion 58 2 LA River @ Baum Bridge 57 1 Venice & National 53 2 Alvarado & 7th 53 none Wilshire & Western 53 none Echo Park & Sunset 48 2 Fountain & Vermont 44 none Idaho & Bundy 37 none Hollywood & Highland 36 none Figueroa & Pasadena 35 none Los Feliz & Riverside 35 3 Washington & Compton 35 none Woodman & Orange Line Station 32 1,3 1st & Alameda 27 none Glendale & Park 25 3 8th & La Brea 23 none Lincoln & Bluff Creek 19 1 4th & Wilton 19 3 Westholme & Wilshire 18 3 York & Ave 50 17 none National & Overland 16 none Total 48 n/a Legend: 1- Paths, 2- Lanes, 3- Routes, and none Table 12: Percentage of Women Riders by Infrastructure Type ranks the intersections according to the percentage of women riders that were observed. Percentage of women riders appeared to relate to infrastructure type. The six intersections with the lowest percentages of women riders had no bikeway infrastructure. Tables 13-15, 16-18, 19-21 Pedestrian & Bicyclist Count Data for all Locations provides all of the data collected during the AM, PM and Weekend counts. In the morning, 7 th and Figueroa had the highest number of pedestrians with 2,761, followed by Wilshire and Western with 1,950. Washington and Admiralty had the highest number of cyclists in the morning, with 237, followed by 7 th and Figueroa with 160. In the evening, Westwood and Le Conte had the highest number of pedestrians with 3,806, followed by Wilshire and Western with 2,303. For cyclists in the evening, the highest numbers were observed at Hoover and McClintock with 977, followed by Washington 12

and Admiralty with 391. For the weekend count, the highest numbers of pedestrians were observed at Alvarado and 7 th with 3,670, followed by Echo Park and Sunset with 2,355. The highest number of cyclists observed on the weekend was at Ballona Creek with 1,251, followed by Washington and Admiralty with 1,056. Note that all of the superlative intersections listed above have some special feature or another. Wilshire and Western, 7 th and Figueroa, and 7 th and Alvarado are all immediately adjacent to major transit stations. Westwood and Le Conte are on the border of the UCLA campus, while Hoover and McClintock is near USC. Washington and Admiralty and Ballona Creek are off-road bike paths. Table 22 Infrastructure Type ranks the intersections by the number of cyclists who were counted and also displays the infrastructure type. Again, as would be expected we observed that ridership is generally higher on bike paths and bike lanes. Ridership on bike routes was lower than the Count-wide average. We also noted high counts near Metro stations and universities, and in high-density central city areas. Table 23 Intersections and Female Cyclists ranks the intersections by the percentage of female cyclists. We observed a relationship between female ridership and the presence of bike infrastructure: bike paths, in particular, drew the highest percentage of female cyclists. Relatively high percentages of female cyclists were also observed at York and Avenue 50, and National and Overland, but due to the low absolute count at these intersections the percentages should be interpreted with caution. Another note of caution: some of these intersections have only partial data. Since fewer women were observed riding during the evening counts, intersections that were not counted during the morning or the weekend may appear to have lower ridership, which may be an artifact of incomplete data. Maps 2-4: Bicycle Count Data with 2000 US Census Journey to Work by Bicycle Data the maps visualize the data with where existing bicycle infrastructure are and by placing the Count data over the US Census Journey to Work by Bicycle data we are able to see the areas where people self reported cycling as their primary mode of transportation to work. The maps suggest that LACBC s method of choosing intersections successfully identified city roadways commonly used by bicyclists. Future counts should pay more attention to the portions of the San Fernando Valley where US Census data show that many people bicycle to work. Maps 5-7: Pedestrian Count Data with 2000 US Census Journey to Work by Walking Data the maps visualize the data and by placing the Count data over the US Census Journey to Work by Walking data we are able to see the areas where people self reported walking as their primary form of transit to work. The Count intersections do not correspond as well with the places where many people walk to work. This is one of the difficulties of conducting bicycle and pedestrian counts simultaneously. LACBC s survey soliciting intersections for the count primarily targeted bicyclists. When choosing intersections, LACBC gave priority to intersections where we expected to observe many 13

bicyclists, and as a result our choices do not line up perfectly with the areas of the city where many people walk. Plans for Future Counts We will work to influence the City of Los Angeles to either conduct their own counts or be more actively supportive of counts on a regular basis. We will work to organize the 2 nd City of Los Angeles Count for the fall of 2011. We hope to improve upon our process and build upon this baseline. These counts and future counts will be invaluable to decision-making about where to make engineering, education, enforcement, and encouragement improvements with regards to bicycling and walking in the City of Los Angeles. Lessons Learned: Confirm more of our locations prior to the day of the first count to ensure we know exact street conditions (e.g., avoid intersections with a convergence of six streets and choose streets where bicycle networks from a neighboring city end at the border of Los Angeles) Conduct two hour time slot counts for both weekday and weekend peak time periods, and count on only one weekday and one weekend. Rank intersections (on volunteer spreadsheet) to make sure volunteers are assigned to the most critical intersections first. Increase number of count locations, especially in the Valley and South LA. Get the City more involved. Better document our process to track total time devoted to the counts and procedures followed as well as through photography and other media. Delineate between children on bicycles and children walking on count forms. Work with pedestrian group, AARP and other citizen-based non-bike orgs. Conduct a greater number of volunteer training sessions (e.g., offer in various locations across the city, various hours to better accommodate volunteers). Conduct train-the-trainer sessions to broaden the reach with hope of attracting a greater number of volunteers and volunteers who live in various areas of the city. 14

Data Tables Intersections with Data from All Time Periods Pedestrian & Bicyclist Data Table 2: Weekday AM Count Locations Pedestrian & Bicyclist Data Intersections with all data AM Ped AM 1st & Alameda 168 54 4th & Wilton 158 39 8th & La Brea 125 49 Alvarado & 7th 1,690 98 Echo Park & Sunset 810 74 Figueroa & Pasadena 227 59 Fountain & Vermont 507 77 Glendale & Park 217 42 Hollywood & Highland 1,730 80 Idaho & Bundy 134 66 LA River @ Baum Bridge 48 110 Lincoln & Bluff Creek 43 40 Los Feliz & Riverside 132 64 National & Overland 93 26 Santa Monica & Westwood 375 136 Sepulveda & Ohio 191 142 Sunset & Hyperion 341 86 Venice & National 384 111 Washington & Admiralty 144 237 Washington & Compton 595 90 Westholme & Wilshire 180 32 Westwood & Le Conte 1,823 124 Wilshire & Western 1,950 91 Woodman & Orange Line Station 195 83 York & Ave 50 196 27 Totals 12,452 2,032 15

Table 3: Weekday PM Count Locations Pedestrian & Bicyclist Data Intersections with all data PM Ped PM 1st & Alameda 241 62 4th & Wilton 87 48 8th & La Brea 272 72 Alvarado & 7th 625 150 Echo Park & Sunset 1,369 121 Figueroa & Pasadena 253 93 Fountain & Vermont 518 110 Glendale & Park 189 65 Hollywood & Highland 1,377 93 Idaho & Bundy 263 105 LA River @ Baum Bridge 46 164 Lincoln & Bluff Creek 32 35 Los Feliz & Riverside 124 97 National & Overland 147 42 Santa Monica & Westwood 370 153 Sepulveda & Ohio 167 138 Sunset & Hyperion 542 145 Venice & National 287 118 Washington & Admiralty 154 391 Washington & Compton 621 90 Westholme & Wilshire 162 52 Westwood & Le Conte 3,806 220 Wilshire & Western 2,303 155 Woodman & Orange Line Station 133 49 York & Ave 50 180 40 Totals 14,264 2,802 16

Table 4: Weekend Mid-day Count Locations Pedestrian & Bicyclist Data Intersections with all data WKND Ped WKND 1st & Alameda 238 58 4th & Wilton 118 35 8th & La Brea 246 30 Alvarado & 7th 3,670 96 Echo Park & Sunset 2,355 115 Figueroa & Pasadena 168 75 Fountain & Vermont 722 97 Glendale & Park 266 57 Hollywood & Highland 2,095 61 Idaho & Bundy 277 71 LA River @ Baum Bridge 11 95 Lincoln & Bluff Creek 79 50 Los Feliz & Riverside 88 65 National & Overland 66 34 Santa Monica & Westwood 387 140 Sepulveda & Ohio 163 141 Sunset & Hyperion 1,096 149 Venice & National 233 118 Washington & Admiralty 219 1,056 Washington & Compton 273 46 Westholme & Wilshire 167 32 Westwood & Le Conte 1,163 74 Wilshire & Western 1,885 97 Woodman & Orange Line Station 68 77 York & Ave 50 365 46 Totals 16,418 2,915 17

Intersections with Data from All Time Periods Gender Data Table 5: AM Count Locations Gender Data Intersections with all data AM Total AM Female % Female AM Male 1st & Alameda 54 11 20% 43 4th & Wilton 39 8 19% 32 8th & La Brea 49 4 8% 45 Alvarado & 7th 98 3 3% 95 Echo Park & Sunset 74 8 10% 66 Figueroa & Pasadena 59 4 7% 55 Fountain & Vermont 77 7 8% 70 Glendale & Park 42 4 10% 38 Hollywood & Highland 80 11 13% 70 Idaho & Bundy 66 8 12% 58 LA River @ Baum Bridge 110 12 11% 98 Lincoln & Bluff Creek 40 8 20% 32 Los Feliz & Riverside 64 9 14% 55 National & Overland 26 7 27% 19 Santa Monica & Westwood 136 23 17% 114 Sepulveda & Ohio 142 24 17% 119 Sunset & Hyperion 86 12 13% 75 Venice & National 111 15 13% 96 Washington & Admiralty 237 51 21% 186 Washington & Compton 90 0 0% 90 Westholme & Wilshire 32 7 20% 26 Westwood & Le Conte 124 30 24% 94 Wilshire & Western 91 9 9% 83 Woodman & Orange Line Station 83 11 13% 72 York & Ave 50 27 7 24% 21 Totals 2,032 286 14% 1,746 18

Table 6: PM Count Locations Gender Data Intersections with all data PM Total PM Female % Female PM Male 1st & Alameda 62 9 14% 53 4th & Wilton 48 4 8% 44 8th & La Brea 72 3 4% 69 Alvarado & 7th 150 1 0% 150 Echo Park & Sunset 121 10 8% 111 Figueroa & Pasadena 93 4 4% 90 Fountain & Vermont 110 8 7% 102 Glendale & Park 65 10 15% 55 Hollywood & Highland 93 12 12% 82 Idaho & Bundy 105 21 20% 85 LA River @ Baum Bridge 164 17 10% 147 Lincoln & Bluff Creek 35 3 9% 32 Los Feliz & Riverside 97 11 11% 86 National & Overland 42 8 19% 34 Santa Monica & Westwood 153 18 11% 136 Sepulveda & Ohio 138 22 16% 116 Sunset & Hyperion 145 20 14% 125 Venice & National 118 16 14% 102 Washington & Admiralty 391 81 21% 310 Washington & Compton 90 0 0% 90 Westholme & Wilshire 52 9 17% 43 Westwood & Le Conte 220 48 22% 172 Wilshire & Western 155 10 6% 145 Woodman & Orange Line Station 49 5 10% 44 York & Ave 50 40 5 13% 35 Totals 2,802 349 12% 2,453 19

Table 7: Weekend Midday Count Locations Gender Data Intersections with all data WKND Total WKND Female % Female WKND Male 1st & Alameda 58 7 12% 51 4th & Wilton 35 6 17% 29 8th & La Brea 30 6 20% 24 Alvarado & 7th 96 3 3% 93 Echo Park & Sunset 115 20 17% 95 Figueroa & Pasadena 75 3 4% 72 Fountain & Vermont 97 11 11% 86 Glendale & Park 57 6 11% 51 Hollywood & Highland 61 9 15% 52 Idaho & Bundy 71 10 14% 61 LA River @ Baum Bridge 95 15 16% 80 Lincoln & Bluff Creek 50 17 34% 33 Los Feliz & Riverside 65 7 11% 58 National & Overland 34 6 18% 28 Santa Monica & Westwood 140 16 11% 124 Sepulveda & Ohio 141 30 21% 111 Sunset & Hyperion 149 24 16% 125 Venice & National 118 9 8% 109 Washington & Admiralty 1,056 276 26% 780 Washington & Compton 46 2 4% 44 Westholme & Wilshire 32 7 22% 25 Westwood & Le Conte 74 9 12% 65 Wilshire & Western 97 1 1% 96 Woodman & Orange Line Station 77 11 14% 66 York & Ave 50 46 13 28% 33 Totals 2,915 524 18% 2,391 20

Intersections with Data from All Time Periods Behavioral Data Table 8: AM Count Locations Behavioral Data Intersections with all data AM Total AM Helmet Use % Helmet Use AM Sidewalk % On Sidewalk AM Wrong Way 1st & Alameda 54 13 23% 26 49% 3 5% 4th & Wilton 39 16 41% 11 28% 0 0% 8th & La Brea 49 24 49% 26 53% 3 5% Alvarado & 7th 98 6 6% 70 71% 1 1% Echo Park & Sunset 74 34 46% 10 14% 5 7% Figueroa & Pasadena 59 25 42% 14 24% 0 0% % Wrong Way Fountain & Vermont 77 24 31% 26 34% 9 11% Glendale & Park 42 20 48% 9 21% 5 11% Hollywood & Highland 80 40 50% 41 51% 1 1% Idaho & Bundy 66 34 51% 8 11% 3 4% LA River @ Baum Bridge 110 87 79% 12 11% 0 0% Lincoln & Bluff Creek 40 25 63% 12 30% 3 6% Los Feliz & Riverside 64 48 75% 24 38% 1 2% National & Overland 26 12 47% 11 41% 2 8% Santa Monica & Westwood 136 91 67% 32 23% 2 1% Sepulveda & Ohio 142 95 67% 33 23% 1 1% Sunset & Hyperion 86 40 46% 6 6% 1 1% Venice & National 111 46 42% 27 24% 1 0% Washington & Admiralty 237 136 58% 26 11% 8 3% Washington & Compton 90 27 30% 40 44% 11 12% Westholme & Wilshire 32 26 80% 5 16% 0 0% Westwood & Le Conte 124 65 52% 29 23% 1 0% Wilshire & Western 91 23 25% 70 76% 4 4% Woodman & Orange Line Station 83 35 42% 15 18% 3 3% York & Ave 50 27 10 35% 7 26% 3 9% Totals 2,032 997 49% 585 29% 64 3% 21

Table 9: PM Count Locations Behavioral Data Intersections with all data PM Total PM Helmet Use % Helmet Use PM Sidewalk % On Sidewalk PM Wrong Way 1st & Alameda 62 11 17% 33 53% 3 4% 4th & Wilton 48 15 31% 8 17% 2 4% 8th & La Brea 72 32 44% 36 50% 2 3% Alvarado & 7th 150 92 61% 0 0% 1 1% Echo Park & Sunset 121 40 33% 23 19% 6 5% Figueroa & Pasadena 93 40 43% 28 30% 2 2% % Wrong Way Fountain & Vermont 110 24 22% 56 51% 22 20% Glendale & Park 65 21 32% 14 22% 5 7% Hollywood & Highland 93 35 37% 48 52% 1 1% Idaho & Bundy 105 34 32% 36 34% 19 18% LA River @ Baum Bridge 164 106 65% 31 19% 1 1% Lincoln & Bluff Creek 35 12 34% 17 49% 0 0% Los Feliz & Riverside 97 59 61% 24 24% 4 4% National & Overland 42 15 35% 14 34% 1 1% Santa Monica & Westwood 153 105 68% 29 19% 0 0% Sepulveda & Ohio 138 75 54% 42 31% 13 9% Sunset & Hyperion 145 37 25% 20 13% 6 4% Venice & National 118 38 32% 33 28% 5 4% Washington & Admiralty 391 107 27% 61 15% 17 4% Washington & Compton 90 39 43% 47 52% 14 15% Westholme & Wilshire 52 37 71% 13 25% 0 0% Westwood & Le Conte 220 105 48% 49 22% 0 0% Wilshire & Western 155 32 20% 125 81% 2 1% Woodman & Orange Line Station 49 16 33% 16 33% 1 2% York & Ave 50 40 7 18% 24 60% 4 10% Totals 2,802 1,128 40% 822 29% 126 4% 22

Table 10: Weekend Midday Count Locations Behavioral Data Intersections with all data WKND Total WKND Helmet Use % Helmet Use WKND Side walk % On Side walk WKND Wrong Way % Wrong Way 1st & Alameda 58 19 33% 28 48% 6 10% 4th & Wilton 35 16 46% 7 20% 2 6% 8th & La Brea 30 7 23% 20 67% 0 0% Alvarado & 7th 96 56 58% 28 29% 1 1% Echo Park & Sunset 115 25 22% 40 35% 10 9% Figueroa & Pasadena 75 34 45% 0 0% 0 0% Fountain & Vermont 97 42 43% 34 35% 1 1% Glendale & Park 57 7 12% 16 28% 1 2% Hollywood & Highland 61 35 57% 24 39% 1 2% Idaho & Bundy 71 33 46% 13 18% 1 1% LA River @ Baum Bridge 95 61 64% 7 7% 4 4% Lincoln & Bluff Creek 50 24 48% 27 54% 0 0% Los Feliz & Riverside 65 52 80% 21 32% 10 15% National & Overland 34 15 44% 15 44% 1 3% Santa Monica & Westwood 140 79 56% 29 21% 2 1% Sepulveda & Ohio 141 115 82% 25 18% 0 0% Sunset & Hyperion 149 65 44% 9 6% 4 3% Venice & National 118 54 46% 37 31% 1 1% Washington & Admiralty 1,056 472 45% 96 9% 39 4% Washington & Compton 46 24 52% 22 48% 10 22% Westholme & Wilshire 32 15 47% 11 34% 0 0% Westwood & Le Conte 74 32 43% 30 41% 0 0% Wilshire & Western 97 27 28% 63 65% 0 0% Woodman & Orange Line Station 77 28 36% 18 23% 0 0% York & Ave 50 46 15 33% 17 37% 2 4% Totals 2,915 1,352 46% 637 22% 96 3% 23

Table 11: Relationship between Cyclist Counts and Infrastructure Type Avg. Intersection Cyclists / Hour Infrastructure Type Washington & Admiralty 259 1,2 Santa Monica & Westwood 66 2 Sepulveda & Ohio 65 1,3 Westwood & Le Conte 64 2 Sunset & Hyperion 58 2 LA River @ Baum Bridge 57 1 Venice & National 53 2 Alvarado & 7th 53 none Wilshire & Western 53 none Echo Park & Sunset 48 2 Fountain & Vermont 44 none Idaho & Bundy 37 none Hollywood & Highland 36 none Figueroa & Pasadena 35 none Los Feliz & Riverside 35 3 Washington & Compton 35 none Woodman & Orange Line Station 32 1,3 1st & Alameda 27 none Glendale & Park 25 3 8th & La Brea 23 none Lincoln & Bluff Creek 19 1 4th & Wilton 19 3 Westholme & Wilshire 18 3 York & Ave 50 17 none National & Overland 16 none Totals 48 24

Table 12: Relationship between Percentages of Women Riders and Infrastructure Type Infrastructure Intersection Female % Type Washington & Admiralty 24% 1,2 Lincoln & Bluff Creek 22% 1 York & Ave 50 22% none National & Overland 21% none Westwood & Le Conte 21% 2 Westholme & Wilshire 19% 3 Sepulveda & Ohio 18% 1,3 Idaho & Bundy 16% none 1st & Alameda 15% none Sunset & Hyperion 15% 2 4th & Wilton 14% 3 Hollywood & Highland 13% none Santa Monica & Westwood 13% 2 Woodman & Orange Line Station 13% 1,3 Echo Park & Sunset 12% 2 Glendale & Park 12% 3 Los Feliz & Riverside 12% 3 LA River @ Baum Bridge 12% 1 Venice & National 11% 2 Fountain & Vermont 9% none 8th & La Brea 9% none Wilshire & Western 6% none Figueroa & Pasadena 5% none Alvarado & 7th 2% none Washington & Compton 1% none Totals 15% 25

All Intersections Pedestrian & Bicyclist Data Table 13: AM Count Locations Pedestrian & Bicycle Data AM Count Intersections AM Ped AM 1st & Alameda 168 54 4th & Wilton 158 39 7th & Figueroa 2,761 160 8th & La Brea 125 49 Alvarado & 7th 1,690 98 Broadway Bridge 42 54 Echo Park & Sunset 810 74 Figueroa & Pasadena 227 59 Fountain & Vermont 507 77 Glendale & Park 217 42 Hollywood & Highland 1,730 80 Idaho & Bundy 134 66 LA River @ Baum Bridge 48 110 Lankershim & Vineland 118 80 Lincoln & Bluff Creek 43 40 Lincoln & Venice 148 122 Long Beach & Los Flores 112 22 Los Feliz & Riverside 132 64 National & Overland 93 26 PCH & Temescal Canyon 104 92 Reseda & Orange Line Station 1,244 104 Santa Monica & Westwood 375 136 Santa Monica & Wilshire 466 75 Sepulveda & Ohio 191 142 Sunset & Hyperion 341 86 Venice & National 384 111 Verdugo & Eagle Rock 133 33 Washington & Admiralty 144 237 Washington & Compton 595 90 Westholme & Wilshire 180 32 Westwood & Le Conte 1,823 124 Wilshire & Western 1,950 91 Woodman & Orange Line Station 195 83 Workman & Ave 26 247 15 York & Ave 50 196 27 Totals 17,826 2,788 26

Table 14: PM Count Locations Pedestrian & Bicycle Data PM Count Intersections PM Ped PM 1st & Alameda 241 62 4th & Wilton 87 48 7th & Figueroa 1,979 216 8th & La Brea 272 72 9th & Pacific 160 58 Alvarado & 7th 625 150 Ballona Creek 181 353 Broadway Bridge 26 63 Eagle Rock & Colorado 246 53 Echo Park & Sunset 1,369 121 Figueroa & Pasadena 253 93 Florence & Graham 1,526 119 Fountain & Vermont 518 110 Glendale & Park 189 65 Hollywood & Highland 1,377 93 Hoover & McClintock 711 977 Idaho & Bundy 263 105 Kittridge & De Soto 191 56 LA River @ Baum Bridge 46 164 Lankershim & Vineland 213 97 Lincoln & Bluff Creek 32 35 Long Beach & Los Flores 224 39 Los Feliz & Riverside 124 97 Manchester & Hoover 407 73 National & Overland 147 42 Santa Monica & Highland 411 103 Santa Monica & Westwood 370 153 Sepulveda & Ohio 167 138 Sunset & Hyperion 542 145 Topanga & Burbank 98 35 Venice & National 287 118 Washington & Admiralty 154 391 Washington & Compton 621 90 Westholme & Wilshire 162 52 Westwood & Le Conte 3,806 220 Wilshire & Western 2,303 155 Woodman & Orange Line Station 133 49 York & Ave 50 180 40 Totals 20,635 5,043 27

Table 15: Weekend Midday Count Locations Pedestrian & Bicycle Data Weekend Intersections WKND Ped WKND 1st & Alameda 238 58 1st & Soto 478 49 4th & Wilton 118 35 8th & La Brea 246 30 Adams & Normandie 338 93 Alvarado & 7th 3,670 96 Ave 19 & N. Broadway 224 23 Ballona Creek 421 1,251 Cesar Chavez & Soto 712 76 Cypress Ave & 28th & Pepper 193 43 Echo Park & Sunset 2,355 115 Figueroa & Pasadena 168 75 Florence & Graham 1,425 312 Fountain & Vermont 722 97 Glendale & Park 266 57 Hollywood & Highland 2,095 61 Hoover & McClintock 663 500 Idaho & Bundy 277 71 LA River @ Baum Bridge 11 95 Laurel Canyon & Ventura 761 43 Lincoln & Bluff Creek 79 50 Lincoln & Venice 295 283 Los Feliz & Riverside 88 65 National & Overland 66 34 PCH & Temescal Canyon 359 326 Santa Monica & Highland 288 89 Santa Monica & Westwood 387 140 Santa Monica & Wilshire 396 62 Sepulveda & Ohio 163 141 Sunset & Hyperion 1,096 149 Topanga & Burbank 101 32 Venice & National 233 118 Verdugo & Eagle Rock 164 65 Washington & Admiralty 219 1,056 Washington & Compton 273 46 Westholme & Wilshire 167 32 Westwood & Le Conte 1163 74 Wilshire & Western 1885 97 Woodman & Orange Line Station 68 77 Workman & Ave 26 365 24 York & Ave 50 365 46 Totals 23,601 6,186 28

All Intersections Gender Data Table 16: AM Count Locations Gender Data AM Count Intersections AM Total AM Female % Female AM Male 1st & Alameda 54 11 20% 43 4th & Wilton 39 8 19% 32 7th & Figueroa 160 5 3% 156 8th & La Brea 49 4 8% 45 Alvarado & 7th 98 3 3% 95 Broadway Bridge 54 4 7% 50 Echo Park & Sunset 74 8 10% 66 Figueroa & Pasadena 59 4 7% 55 Fountain & Vermont 77 7 8% 70 Glendale & Park 42 4 10% 38 Hollywood & Highland 80 11 13% 70 Idaho & Bundy 66 8 12% 58 LA River @ Baum Bridge 110 12 11% 98 Lankershim & Vineland 80 5 6% 75 Lincoln & Bluff Creek 40 8 20% 32 Lincoln & Venice 122 31 25% 91 Long Beach & Los Flores 22 1 5% 21 Los Feliz & Riverside 64 9 14% 55 National & Overland 26 7 27% 19 PCH & Temescal Canyon 92 16 17% 76 Reseda & Orange Line Station 104 17 16% 88 Santa Monica & Westwood 136 23 17% 114 Santa Monica & Wilshire 75 0 0% 75 Sepulveda & Ohio 142 24 17% 119 Sunset & Hyperion 86 12 13% 75 Venice & National 111 15 13% 96 Verdugo & Eagle Rock 33 5 15% 28 Washington & Admiralty 237 51 21% 186 Washington & Compton 90 0 0% 90 Westholme & Wilshire 32 7 20% 26 Westwood & Le Conte 124 30 24% 94 Wilshire & Western 91 9 9% 83 Woodman & Orange Line Station 83 11 13% 72 Workman & Ave 26 15 1 7% 14 York & Ave 50 27 7 24% 21 Totals 2,788 370 13% 2,418 29

PM Count Intersections Table 17: PM Count Locations Gender Data PM Total PM Female % Female PM Male 1st & Alameda 62 9 14% 53 4th & Wilton 48 4 8% 44 7th & Figueroa 216 22 10% 194 8th & La Brea 72 3 4% 69 9th & Pacific 58 1 2% 57 Alvarado & 7th 150 1 0% 149 Ballona Creek 353 77 22% 276 Broadway Bridge 63 7 11% 56 Eagle Rock & Colorado 53 2 3% 52 Echo Park & Sunset 121 10 8% 111 Figueroa & Pasadena 93 4 4% 90 Florence & Graham 119 0 0% 119 Fountain & Vermont 110 8 7% 102 Glendale & Park 65 10 15% 55 Hollywood & Highland 93 12 12% 82 Hoover & McClintock 977 0 0% 977 Idaho & Bundy 105 21 20% 85 Kittridge & De Soto 56 2 4% 54 LA River @ Baum Bridge 164 17 10% 147 Lankershim & Vineland 97 7 7% 90 Lincoln & Bluff Creek 35 3 9% 32 Long Beach & Los Flores 39 1 3% 38 Los Feliz & Riverside 97 11 11% 86 Manchester & Hoover 73 2 3% 71 National & Overland 42 8 19% 34 Santa Monica & Highland 103 10 9% 94 Santa Monica & Westwood 153 18 11% 136 Sepulveda & Ohio 138 22 16% 116 Sunset & Hyperion 145 20 14% 125 Topanga & Burbank 35 3 7% 33 Venice & National 118 16 14% 102 Washington & Admiralty 391 81 21% 310 Washington & Compton 90 0 0% 90 Westholme & Wilshire 52 9 17% 43 Westwood & Le Conte 220 48 22% 172 Wilshire & Western 155 10 6% 145 Woodman & Orange Line Station 49 5 10% 44 York & Ave 50 40 5 13% 35 Totals 5,043 481 10% 4,562 30

Table 18: Weekend Midday Count Locations Gender Data Weekend Intersections PM Total PM Female % Female PM Male 1st & Alameda 58 7 12% 51 1st & Soto 49 0 0% 49 4th & Wilton 35 6 17% 29 8th & La Brea 30 6 20% 24 Adams & Normandie 93 8 9% 85 Alvarado & 7th 96 3 3% 93 Ave 19 & N. Broadway 23 3 13% 20 Ballona Creek 1,251 337 27% 914 Cesar Chavez & Soto 76 3 4% 73 Cypress Ave & 28th & Pepper 43 2 5% 41 Echo Park & Sunset 115 20 17% 95 Figueroa & Pasadena 75 3 4% 72 Florence & Graham 312 5 2% 307 Fountain & Vermont 97 11 11% 86 Glendale & Park 57 6 11% 51 Hollywood & Highland 61 9 15% 52 Hoover & McClintock 500 146 29% 354 Idaho & Bundy 71 10 14% 61 LA River @ Baum Bridge 95 15 16% 80 Laurel Canyon & Ventura 43 2 5% 41 Lincoln & Bluff Creek 50 17 34% 33 Lincoln & Venice 283 64 23% 219 Los Feliz & Riverside 65 7 11% 58 National & Overland 34 6 18% 28 PCH & Temescal Canyon 326 39 12% 287 Santa Monica & Highland 89 15 17% 74 Santa Monica & Westwood 140 16 11% 124 Santa Monica & Wilshire 62 6 10% 56 Sepulveda & Ohio 141 30 21% 111 Sunset & Hyperion 149 24 16% 125 Topanga & Burbank 32 5 16% 27 Venice & National 118 9 8% 109 Verdugo & Eagle Rock 65 5 8% 60 Washington & Admiralty 1,056 276 26% 780 Washington & Compton 46 2 4% 44 Westholme & Wilshire 32 7 22% 25 Westwood & Le Conte 74 9 12% 65 Wilshire & Western 97 1 1% 96 Woodman & Orange Line Station 77 11 14% 66 Workman & Ave 26 24 5 21% 19 York & Ave 50 46 13 28% 33 Totals 6,186 1,169 19% 5,017 31

All Intersections Bicyclists Behavioral Data Table 19: AM Count Locations Behavioral Data AM Count Intersections AM Total AM Helmet Use % Helmet Use AM Sidewalk % On Sidewalk AM Wrong Way % Wrong Way 1st & Alameda 54 13 23% 26 49% 3 5% 4th & Wilton 39 16 41% 11 28% 0 0% 7th & Figueroa 160 85 53% 42 26% 0 0% 8th & La Brea 49 24 49% 26 53% 3 5% Alvarado & 7th 98 6 6% 70 71% 1 1% Broadway Bridge 54 26 48% 10 19% 0 0% Echo Park & Sunset 74 34 46% 10 14% 5 7% Figueroa & Pasadena 59 25 42% 14 24% 0 0% Fountain & Vermont 77 24 31% 26 34% 9 11% Glendale & Park 42 20 48% 9 21% 5 11% Hollywood & Highland 80 40 50% 41 51% 1 1% Idaho & Bundy 66 34 51% 8 11% 3 4% LA River @ Baum Bridge 110 87 79% 12 11% 0 0% Lankershim & Vineland 80 35 44% 27 34% 0 0% Lincoln & Bluff Creek 40 25 63% 12 30% 3 6% Lincoln & Venice 122 63 52% 31 25% 1 1% Long Beach & Los Flores 22 2 7% 11 49% 4 19% Los Feliz & Riverside 64 48 75% 24 38% 1 2% National & Overland 26 12 47% 11 41% 2 8% PCH & Temescal Canyon 92 76 83% 8 9% 6 7% Reseda & Orange Line Station 104 42 40% 0 0% 0 0% Santa Monica & Westwood 136 91 67% 32 23% 2 1% Santa Monica & Wilshire 75 53 71% 24 32% 3 4% Sepulveda & Ohio 142 95 67% 33 23% 1 1% Sunset & Hyperion 86 40 46% 6 6% 1 1% Venice & National 111 46 42% 27 24% 1 0% Verdugo & Eagle Rock 33 21 64% 6 18% 0 0% Washington & Admiralty 237 136 58% 26 11% 8 3% Washington & Compton 90 27 30% 40 44% 11 12% Westholme & Wilshire 32 26 80% 5 16% 0 0% Westwood & Le Conte 124 65 52% 29 23% 1 0% Wilshire & Western 91 23 25% 70 76% 4 4% Woodman & Orange Line Station 83 35 42% 15 18% 3 3% Workman & Ave 26 15 5 31% 5 34% 1 7% York & Ave 50 27 10 35% 7 26% 3 9% Totals 2,788 1,404 50% 748 27% 79 3% 32

Table 20: PM Count Locations Behavioral Data PM Count Intersections PM Total PM Helmet Use % Helmet Use PM Sidewalk % On Sidewalk PM Wrong Way % Wrong Way 1st & Alameda 62 11 17% 33 53% 3 4% 4th & Wilton 48 15 31% 8 17% 2 4% 7th & Figueroa 216 75 35% 103 48% 3 1% 8th & La Brea 72 32 44% 36 50% 2 3% 9th & Pacific 58 0 0% 26 45% 19 33% Alvarado & 7th 150 92 61% 0 0% 1 1% Ballona Creek 353 150 43% 0 0% 1 0% Broadway Bridge 63 26 41% 23 37% 19 30% Eagle Rock & Colorado 53 24 45% 20 37% 0 0% Echo Park & Sunset 121 40 33% 23 19% 6 5% Figueroa & Pasadena 93 40 43% 28 30% 2 2% Florence & Graham 119 4 3% 98 82% 0 0% Fountain & Vermont 110 24 22% 56 51% 22 20% Glendale & Park 65 21 32% 14 22% 5 7% Hollywood & Highland 93 35 37% 48 52% 1 1% Hoover & McClintock 977 432 44% 375 38% 50 5% Idaho & Bundy 105 34 32% 36 34% 19 18% Kittridge & De Soto 56 10 18% 42 75% 1 2% LA River @ Baum Bridge 164 106 65% 31 19% 1 1% Lankershim & Vineland 97 17 18% 52 53% 1 1% Lincoln & Bluff Creek 35 12 34% 17 49% 0 0% Long Beach & Los Flores 39 3 8% 22 56% 8 21% Los Feliz & Riverside 97 59 61% 24 24% 4 4% Manchester & Hoover 73 10 14% 59 81% 3 3% National & Overland 42 15 35% 14 34% 1 1% Santa Monica & Highland 103 25 24% 77 75% 2 2% Santa Monica & Westwood 153 105 68% 29 19% 0 0% Sepulveda & Ohio 138 75 54% 42 31% 13 9% Sunset & Hyperion 145 37 25% 20 13% 6 4% Topanga & Burbank 35 7 19% 30 84% 0 0% Venice & National 118 38 32% 33 28% 5 4% Washington & Admiralty 391 107 27% 61 15% 17 4% Washington & Compton 90 39 43% 47 52% 14 15% Westholme & Wilshire 52 37 71% 13 25% 0 0% Westwood & Le Conte 220 105 48% 49 22% 0 0% Wilshire & Western 155 32 20% 125 81% 2 1% Woodman & Orange Line Station 49 16 33% 16 33% 1 2% York & Ave 50 40 7 18% 24 60% 4 10% Totals 5,043 1,910 38% 1,747 35% 232 5% 33

Table 21: Weekend Midday Count Locations Behavioral Data Weekend Intersections PM Total PM Helmet Use % Helmet Use PM Sidewalk % On Sidewalk PM Wrong Way % Wrong Way 1st & Alameda 58 19 33% 28 48% 6 10% 1st & Soto 49 21 43% 25 51% 10 20% 4th & Wilton 35 16 46% 7 20% 2 6% 8th & La Brea 30 7 23% 20 67% 0 0% Adams & Normandie 93 4 4% 75 81% 1 1% Alvarado & 7th 96 56 58% 28 29% 1 1% Ave 19 & N. Broadway 23 4 17% 15 65% 2 9% Ballona Creek 1,251 744 59% 0 0% 0 0% Cesar Chavez & Soto 76 19 25% 51 67% 21 28% Cypress Ave & 28th & Pepper 43 10 23% 17 40% 4 9% Echo Park & Sunset 115 25 22% 40 35% 10 9% Figueroa & Pasadena 75 34 45% 0 0% 0 0% Florence & Graham 312 104 33% 52 17% 25 8% Fountain & Vermont 97 42 43% 34 35% 1 1% Glendale & Park 57 7 12% 16 28% 1 2% Hollywood & Highland 61 35 57% 24 39% 1 2% Idaho & Bundy 71 33 46% 13 18% 1 1% LA River @ Baum Bridge 95 61 64% 7 7% 4 4% Laurel Canyon & Ventura 43 21 49% 14 33% 0 0% Lincoln & Bluff Creek 50 24 48% 27 54% 0 0% Lincoln & Venice 283 108 38% 90 32% 3 1% Los Feliz & Riverside 65 52 80% 21 32% 10 15% National & Overland 34 15 44% 15 44% 1 3% PCH & Temescal Canyon 326 277 85% 7 2% 4 1% Santa Monica & Highland 89 29 33% 73 82% 0 0% Santa Monica & Westwood 140 79 56% 29 21% 2 1% Santa Monica & Wilshire 62 50 81% 16 26% 0 0% Sepulveda & Ohio 141 115 82% 25 18% 0 0% Sunset & Hyperion 149 65 44% 9 6% 4 3% Topanga & Burbank 32 18 56% 13 41% 0 0% Venice & National 118 54 46% 37 31% 1 1% Verdugo & Eagle Rock 65 29 45% 17 26% 0 0% Washington & Admiralty 1,056 472 45% 96 9% 39 4% Washington & Compton 46 24 52% 22 48% 10 22% Westholme & Wilshire 32 15 47% 11 34% 0 0% Westwood & Le Conte 74 32 43% 30 41% 0 0% Wilshire & Western 97 27 28% 63 65% 0 0% Woodman & Orange Line Station 77 28 36% 18 23% 0 0% Workman & Ave 26 24 5 21% 9 38% 0 0% York & Ave 50 46 15 33% 17 37% 2 4% Totals 6,186 2,788 45% 1,634 26% 372 6% 34

Table 22: 50 Intersections Ranked by Cyclists per Hour with Infrastructure Type Intersection Avg. Cyclists / Hour Infrastructure Type Intersection Avg. Cyclists / Hour Infrastructure Type 1 Ballona Creek 356 1 26 Los Feliz & Riverside 35 3 2 Washington & Admiralty 259 1,2 27 Washington & Compton 35 none Woodman & Orange Line 3 Hoover & McClintock 227 2 28 Station 32 1,3 4 Florence & Graham 96 none 29 Santa Monica & Wilshire 30 none 5 PCH & Temescal Canyon 93 2,3 30 Cesar Chavez & Soto 30 none 6 Lincoln & Venice 90 2 31 Broadway & Bridge 29 none 7 7th & Figueroa 75 none 32 9th & Pacific 29 none 8 Santa Monica & Westwood 66 2 33 Kittridge & De Soto 28 3 9 Sepulveda & Ohio 65 1,3 34 1st & Alameda 27 none 10 Westwood & Le Conte 64 2 35 Eagle Rock & Colorado 27 3 11 Sunset & Hyperion 58 2 36 Glendale & Park 25 3 12 LA River @ Baum Bridge 57 1 37 8th & La Brea 23 none 13 Venice & National 53 2 38 Verdugo & Eagle Rock 22 2 14 Alvarado & 7th 53 none 39 1st & Soto 20 none 15 Wilshire & Western 53 none 40 Lincoln & Bluff Creek 19 1 Reseda & Orange Line 16 Station 52 1,2 41 4th & Wilton 19 3 17 Echo Park & Sunset 48 2 42 Westholme & Wilshire 18 3 18 Lankershim & Vineland 44 none 43 York & Ave 50 17 none Cypress Ave & 28th & 19 Fountain & Vermont 44 none 44 Pepper 17 3 20 Santa Monica & Highland 43 none 45 Laurel Canyon & Ventura 17 none 21 Adams & Normandie 37 none 46 National & Overland 16 none 22 Idaho & Bundy 37 none 47 Long Beach & Los Flores 15 none 23 Manchester & Hoover 37 3 48 Topanga & Burbank 15 none 24 Hollywood & Highland 36 none 49 Ave 19 & N. Broadway 9 3 25 Figueroa & Pasadena 35 none 50 Workman & Ave 26 9 none 50 Intersection Average 43 Legend: Paths, Lanes, Routes, and none 35

Table 23: 50 Intersections Ranked by Percentage of Women Riders with Infrastructure Type Intersection % Female Infrastructure Type Intersection % Female Infrastructure Type 1 Ballona Creek 26% 1 26 Venice & National 11% 2 2 Washington & Admiralty 24% 1,2 27 Topanga & Burbank 11% none 3 Lincoln & Venice 23% 2 28 Verdugo & Eagle Rock 10% 2 4 Lincoln & Bluff Creek 22% 1 29 Hoover & McClintock 10% 2 5 York & Ave 50 22% none 30 Broadway & Bridge 9% none 6 National & Overland 21% none 31 Fountain & Vermont 9% none 7 Westwood & Le Conte 21% 2 32 8th & La Brea 9% none 8 Westholme & Wilshire 19% 3 33 Adams & Normandie 9% none 9 Sepulveda & Ohio 18% 1,3 34 Lankershim & Vineland 7% none 10 Idaho & Bundy 16% none 35 Wilshire & Western 6% none 11 Reseda & Orange Line Station 16% 1,2 36 7th & Figueroa 5% none 12 Workman & Ave 26 16% none 37 Cypress Ave & 28th & Pepper 5% 3 13 1st & Alameda 15% none 38 Laurel Canyon & Ventura 5% none 14 Sunset & Hyperion 15% 2 39 Figueroa & Pasadena 5% none 15 4th & Wilton 14% 3 40 Santa Monica & Wilshire 4% none 16 Hollywood & Highland 13% none 41 Cesar Chavez & Soto 4% none 17 PCH & Temescal Canyon 13% 2,3 42 Kittridge & De Soto 4% 3 18 Santa Monica & Westwood 13% 2 43 Long Beach & Los Flores 3% none 19 Ave19 & N.Broadway 13% 3 44 Eagle Rock & Colorado 3% 3 Woodman & Orange Line 20 Station 13% 1,3 45 Manchester & Hoover 3% 3 21 Santa Monica & Highland 13% none 46 Alvarado & 7th 2% none 22 Echo Park & Sunset 12% 2 47 9th & Pacific 2% none 23 Glendale & Park 12% 3 48 Florence & Graham 1% none 24 Los Feliz & Riverside 12% 3 49 Washington & Compton 1% none 25 LA River @ Baum Bridge 12% 1 50 1st & Soto 0% none 50 Intersection Average 14% Legend: Paths, Lanes, Routes, and none 36

Count Maps Map 2: AM Count Data with 2000 US Census Journey to Work by Bicycle Data 37

Map 3: PM Count Data with 2000 US Census Journey to Work by Bicycle Data 38

Map 4: Weekend Count Data with 2000 US Census Journey to Work by Bicycle Data 39

Map 5: AM Pedestrian Count Data with 2000 US Census Journey to Work by Walking Data 40