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

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

2 Table of Contents Executive Summary 2 About the Los Angeles County Bicycle Coalition 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. 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 and for more information 1

3 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

4 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

5 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

6 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 Baum Bridge 49 Workman & Ave Lankershim & Vineland 50 York & Ave 50 5

7 Map 1 Los Angeles Bicycle and Pedestrian Count Locations 6

8 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

9 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

10 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

11 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

12 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

13 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 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 th & La Brea 23 none Lincoln & Bluff Creek th & Wilton 19 3 Westholme & Wilshire 18 3 York & Ave 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, 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

14 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

15 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 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

16 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 th & Wilton th & La Brea Alvarado & 7th 1, Echo Park & Sunset Figueroa & Pasadena Fountain & Vermont Glendale & Park Hollywood & Highland 1, Idaho & Bundy LA Baum Bridge Lincoln & Bluff Creek Los Feliz & Riverside National & Overland Santa Monica & Westwood Sepulveda & Ohio Sunset & Hyperion Venice & National Washington & Admiralty Washington & Compton Westholme & Wilshire Westwood & Le Conte 1, Wilshire & Western 1, Woodman & Orange Line Station York & Ave Totals 12,452 2,032 15

17 Table 3: Weekday PM Count Locations Pedestrian & Bicyclist Data Intersections with all data PM Ped PM 1st & Alameda th & Wilton th & La Brea Alvarado & 7th Echo Park & Sunset 1, Figueroa & Pasadena Fountain & Vermont Glendale & Park Hollywood & Highland 1, Idaho & Bundy LA Baum Bridge Lincoln & Bluff Creek Los Feliz & Riverside National & Overland Santa Monica & Westwood Sepulveda & Ohio Sunset & Hyperion Venice & National Washington & Admiralty Washington & Compton Westholme & Wilshire Westwood & Le Conte 3, Wilshire & Western 2, Woodman & Orange Line Station York & Ave Totals 14,264 2,802 16

18 Table 4: Weekend Mid-day Count Locations Pedestrian & Bicyclist Data Intersections with all data WKND Ped WKND 1st & Alameda th & Wilton th & La Brea Alvarado & 7th 3, Echo Park & Sunset 2, Figueroa & Pasadena Fountain & Vermont Glendale & Park Hollywood & Highland 2, Idaho & Bundy LA Baum Bridge Lincoln & Bluff Creek Los Feliz & Riverside National & Overland Santa Monica & Westwood Sepulveda & Ohio Sunset & Hyperion 1, Venice & National Washington & Admiralty 219 1,056 Washington & Compton Westholme & Wilshire Westwood & Le Conte 1, Wilshire & Western 1, Woodman & Orange Line Station York & Ave Totals 16,418 2,915 17

19 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 % 43 4th & Wilton % 32 8th & La Brea % 45 Alvarado & 7th % 95 Echo Park & Sunset % 66 Figueroa & Pasadena % 55 Fountain & Vermont % 70 Glendale & Park % 38 Hollywood & Highland % 70 Idaho & Bundy % 58 LA Baum Bridge % 98 Lincoln & Bluff Creek % 32 Los Feliz & Riverside % 55 National & Overland % 19 Santa Monica & Westwood % 114 Sepulveda & Ohio % 119 Sunset & Hyperion % 75 Venice & National % 96 Washington & Admiralty % 186 Washington & Compton % 90 Westholme & Wilshire % 26 Westwood & Le Conte % 94 Wilshire & Western % 83 Woodman & Orange Line Station % 72 York & Ave % 21 Totals 2, % 1,746 18

20 Table 6: PM Count Locations Gender Data Intersections with all data PM Total PM Female % Female PM Male 1st & Alameda % 53 4th & Wilton % 44 8th & La Brea % 69 Alvarado & 7th % 150 Echo Park & Sunset % 111 Figueroa & Pasadena % 90 Fountain & Vermont % 102 Glendale & Park % 55 Hollywood & Highland % 82 Idaho & Bundy % 85 LA Baum Bridge % 147 Lincoln & Bluff Creek % 32 Los Feliz & Riverside % 86 National & Overland % 34 Santa Monica & Westwood % 136 Sepulveda & Ohio % 116 Sunset & Hyperion % 125 Venice & National % 102 Washington & Admiralty % 310 Washington & Compton % 90 Westholme & Wilshire % 43 Westwood & Le Conte % 172 Wilshire & Western % 145 Woodman & Orange Line Station % 44 York & Ave % 35 Totals 2, % 2,453 19

21 Table 7: Weekend Midday Count Locations Gender Data Intersections with all data WKND Total WKND Female % Female WKND Male 1st & Alameda % 51 4th & Wilton % 29 8th & La Brea % 24 Alvarado & 7th % 93 Echo Park & Sunset % 95 Figueroa & Pasadena % 72 Fountain & Vermont % 86 Glendale & Park % 51 Hollywood & Highland % 52 Idaho & Bundy % 61 LA Baum Bridge % 80 Lincoln & Bluff Creek % 33 Los Feliz & Riverside % 58 National & Overland % 28 Santa Monica & Westwood % 124 Sepulveda & Ohio % 111 Sunset & Hyperion % 125 Venice & National % 109 Washington & Admiralty 1, % 780 Washington & Compton % 44 Westholme & Wilshire % 25 Westwood & Le Conte % 65 Wilshire & Western % 96 Woodman & Orange Line Station % 66 York & Ave % 33 Totals 2, % 2,391 20

22 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 % 26 49% 3 5% 4th & Wilton % 11 28% 0 0% 8th & La Brea % 26 53% 3 5% Alvarado & 7th % 70 71% 1 1% Echo Park & Sunset % 10 14% 5 7% Figueroa & Pasadena % 14 24% 0 0% % Wrong Way Fountain & Vermont % 26 34% 9 11% Glendale & Park % 9 21% 5 11% Hollywood & Highland % 41 51% 1 1% Idaho & Bundy % 8 11% 3 4% LA Baum Bridge % 12 11% 0 0% Lincoln & Bluff Creek % 12 30% 3 6% Los Feliz & Riverside % 24 38% 1 2% National & Overland % 11 41% 2 8% Santa Monica & Westwood % 32 23% 2 1% Sepulveda & Ohio % 33 23% 1 1% Sunset & Hyperion % 6 6% 1 1% Venice & National % 27 24% 1 0% Washington & Admiralty % 26 11% 8 3% Washington & Compton % 40 44% 11 12% Westholme & Wilshire % 5 16% 0 0% Westwood & Le Conte % 29 23% 1 0% Wilshire & Western % 70 76% 4 4% Woodman & Orange Line Station % 15 18% 3 3% York & Ave % 7 26% 3 9% Totals 2, % % 64 3% 21

23 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 % 33 53% 3 4% 4th & Wilton % 8 17% 2 4% 8th & La Brea % 36 50% 2 3% Alvarado & 7th % 0 0% 1 1% Echo Park & Sunset % 23 19% 6 5% Figueroa & Pasadena % 28 30% 2 2% % Wrong Way Fountain & Vermont % 56 51% 22 20% Glendale & Park % 14 22% 5 7% Hollywood & Highland % 48 52% 1 1% Idaho & Bundy % 36 34% 19 18% LA Baum Bridge % 31 19% 1 1% Lincoln & Bluff Creek % 17 49% 0 0% Los Feliz & Riverside % 24 24% 4 4% National & Overland % 14 34% 1 1% Santa Monica & Westwood % 29 19% 0 0% Sepulveda & Ohio % 42 31% 13 9% Sunset & Hyperion % 20 13% 6 4% Venice & National % 33 28% 5 4% Washington & Admiralty % 61 15% 17 4% Washington & Compton % 47 52% 14 15% Westholme & Wilshire % 13 25% 0 0% Westwood & Le Conte % 49 22% 0 0% Wilshire & Western % % 2 1% Woodman & Orange Line Station % 16 33% 1 2% York & Ave % 24 60% 4 10% Totals 2,802 1,128 40% % 126 4% 22

24 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 % 28 48% 6 10% 4th & Wilton % 7 20% 2 6% 8th & La Brea % 20 67% 0 0% Alvarado & 7th % 28 29% 1 1% Echo Park & Sunset % 40 35% 10 9% Figueroa & Pasadena % 0 0% 0 0% Fountain & Vermont % 34 35% 1 1% Glendale & Park % 16 28% 1 2% Hollywood & Highland % 24 39% 1 2% Idaho & Bundy % 13 18% 1 1% LA Baum Bridge % 7 7% 4 4% Lincoln & Bluff Creek % 27 54% 0 0% Los Feliz & Riverside % 21 32% 10 15% National & Overland % 15 44% 1 3% Santa Monica & Westwood % 29 21% 2 1% Sepulveda & Ohio % 25 18% 0 0% Sunset & Hyperion % 9 6% 4 3% Venice & National % 37 31% 1 1% Washington & Admiralty 1, % 96 9% 39 4% Washington & Compton % 22 48% 10 22% Westholme & Wilshire % 11 34% 0 0% Westwood & Le Conte % 30 41% 0 0% Wilshire & Western % 63 65% 0 0% Woodman & Orange Line Station % 18 23% 0 0% York & Ave % 17 37% 2 4% Totals 2,915 1,352 46% % 96 3% 23

25 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 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 th & La Brea 23 none Lincoln & Bluff Creek th & Wilton 19 3 Westholme & Wilshire 18 3 York & Ave none National & Overland 16 none Totals 48 24

26 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 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

27 All Intersections Pedestrian & Bicyclist Data Table 13: AM Count Locations Pedestrian & Bicycle Data AM Count Intersections AM Ped AM 1st & Alameda th & Wilton th & Figueroa 2, th & La Brea Alvarado & 7th 1, Broadway Bridge Echo Park & Sunset Figueroa & Pasadena Fountain & Vermont Glendale & Park Hollywood & Highland 1, Idaho & Bundy LA Baum Bridge Lankershim & Vineland Lincoln & Bluff Creek Lincoln & Venice Long Beach & Los Flores Los Feliz & Riverside National & Overland PCH & Temescal Canyon Reseda & Orange Line Station 1, Santa Monica & Westwood Santa Monica & Wilshire Sepulveda & Ohio Sunset & Hyperion Venice & National Verdugo & Eagle Rock Washington & Admiralty Washington & Compton Westholme & Wilshire Westwood & Le Conte 1, Wilshire & Western 1, Woodman & Orange Line Station Workman & Ave York & Ave Totals 17,826 2,788 26

28 Table 14: PM Count Locations Pedestrian & Bicycle Data PM Count Intersections PM Ped PM 1st & Alameda th & Wilton th & Figueroa 1, th & La Brea th & Pacific Alvarado & 7th Ballona Creek Broadway Bridge Eagle Rock & Colorado Echo Park & Sunset 1, Figueroa & Pasadena Florence & Graham 1, Fountain & Vermont Glendale & Park Hollywood & Highland 1, Hoover & McClintock Idaho & Bundy Kittridge & De Soto LA Baum Bridge Lankershim & Vineland Lincoln & Bluff Creek Long Beach & Los Flores Los Feliz & Riverside Manchester & Hoover National & Overland Santa Monica & Highland Santa Monica & Westwood Sepulveda & Ohio Sunset & Hyperion Topanga & Burbank Venice & National Washington & Admiralty Washington & Compton Westholme & Wilshire Westwood & Le Conte 3, Wilshire & Western 2, Woodman & Orange Line Station York & Ave Totals 20,635 5,043 27

29 Table 15: Weekend Midday Count Locations Pedestrian & Bicycle Data Weekend Intersections WKND Ped WKND 1st & Alameda st & Soto th & Wilton th & La Brea Adams & Normandie Alvarado & 7th 3, Ave 19 & N. Broadway Ballona Creek 421 1,251 Cesar Chavez & Soto Cypress Ave & 28th & Pepper Echo Park & Sunset 2, Figueroa & Pasadena Florence & Graham 1, Fountain & Vermont Glendale & Park Hollywood & Highland 2, Hoover & McClintock Idaho & Bundy LA Baum Bridge Laurel Canyon & Ventura Lincoln & Bluff Creek Lincoln & Venice Los Feliz & Riverside National & Overland PCH & Temescal Canyon Santa Monica & Highland Santa Monica & Westwood Santa Monica & Wilshire Sepulveda & Ohio Sunset & Hyperion 1, Topanga & Burbank Venice & National Verdugo & Eagle Rock Washington & Admiralty 219 1,056 Washington & Compton Westholme & Wilshire Westwood & Le Conte Wilshire & Western Woodman & Orange Line Station Workman & Ave York & Ave Totals 23,601 6,186 28

30 All Intersections Gender Data Table 16: AM Count Locations Gender Data AM Count Intersections AM Total AM Female % Female AM Male 1st & Alameda % 43 4th & Wilton % 32 7th & Figueroa % 156 8th & La Brea % 45 Alvarado & 7th % 95 Broadway Bridge % 50 Echo Park & Sunset % 66 Figueroa & Pasadena % 55 Fountain & Vermont % 70 Glendale & Park % 38 Hollywood & Highland % 70 Idaho & Bundy % 58 LA Baum Bridge % 98 Lankershim & Vineland % 75 Lincoln & Bluff Creek % 32 Lincoln & Venice % 91 Long Beach & Los Flores % 21 Los Feliz & Riverside % 55 National & Overland % 19 PCH & Temescal Canyon % 76 Reseda & Orange Line Station % 88 Santa Monica & Westwood % 114 Santa Monica & Wilshire % 75 Sepulveda & Ohio % 119 Sunset & Hyperion % 75 Venice & National % 96 Verdugo & Eagle Rock % 28 Washington & Admiralty % 186 Washington & Compton % 90 Westholme & Wilshire % 26 Westwood & Le Conte % 94 Wilshire & Western % 83 Woodman & Orange Line Station % 72 Workman & Ave % 14 York & Ave % 21 Totals 2, % 2,418 29

31 PM Count Intersections Table 17: PM Count Locations Gender Data PM Total PM Female % Female PM Male 1st & Alameda % 53 4th & Wilton % 44 7th & Figueroa % 194 8th & La Brea % 69 9th & Pacific % 57 Alvarado & 7th % 149 Ballona Creek % 276 Broadway Bridge % 56 Eagle Rock & Colorado % 52 Echo Park & Sunset % 111 Figueroa & Pasadena % 90 Florence & Graham % 119 Fountain & Vermont % 102 Glendale & Park % 55 Hollywood & Highland % 82 Hoover & McClintock % 977 Idaho & Bundy % 85 Kittridge & De Soto % 54 LA Baum Bridge % 147 Lankershim & Vineland % 90 Lincoln & Bluff Creek % 32 Long Beach & Los Flores % 38 Los Feliz & Riverside % 86 Manchester & Hoover % 71 National & Overland % 34 Santa Monica & Highland % 94 Santa Monica & Westwood % 136 Sepulveda & Ohio % 116 Sunset & Hyperion % 125 Topanga & Burbank % 33 Venice & National % 102 Washington & Admiralty % 310 Washington & Compton % 90 Westholme & Wilshire % 43 Westwood & Le Conte % 172 Wilshire & Western % 145 Woodman & Orange Line Station % 44 York & Ave % 35 Totals 5, % 4,562 30

32 Table 18: Weekend Midday Count Locations Gender Data Weekend Intersections PM Total PM Female % Female PM Male 1st & Alameda % 51 1st & Soto % 49 4th & Wilton % 29 8th & La Brea % 24 Adams & Normandie % 85 Alvarado & 7th % 93 Ave 19 & N. Broadway % 20 Ballona Creek 1, % 914 Cesar Chavez & Soto % 73 Cypress Ave & 28th & Pepper % 41 Echo Park & Sunset % 95 Figueroa & Pasadena % 72 Florence & Graham % 307 Fountain & Vermont % 86 Glendale & Park % 51 Hollywood & Highland % 52 Hoover & McClintock % 354 Idaho & Bundy % 61 LA Baum Bridge % 80 Laurel Canyon & Ventura % 41 Lincoln & Bluff Creek % 33 Lincoln & Venice % 219 Los Feliz & Riverside % 58 National & Overland % 28 PCH & Temescal Canyon % 287 Santa Monica & Highland % 74 Santa Monica & Westwood % 124 Santa Monica & Wilshire % 56 Sepulveda & Ohio % 111 Sunset & Hyperion % 125 Topanga & Burbank % 27 Venice & National % 109 Verdugo & Eagle Rock % 60 Washington & Admiralty 1, % 780 Washington & Compton % 44 Westholme & Wilshire % 25 Westwood & Le Conte % 65 Wilshire & Western % 96 Woodman & Orange Line Station % 66 Workman & Ave % 19 York & Ave % 33 Totals 6,186 1,169 19% 5,017 31

33 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 % 26 49% 3 5% 4th & Wilton % 11 28% 0 0% 7th & Figueroa % 42 26% 0 0% 8th & La Brea % 26 53% 3 5% Alvarado & 7th % 70 71% 1 1% Broadway Bridge % 10 19% 0 0% Echo Park & Sunset % 10 14% 5 7% Figueroa & Pasadena % 14 24% 0 0% Fountain & Vermont % 26 34% 9 11% Glendale & Park % 9 21% 5 11% Hollywood & Highland % 41 51% 1 1% Idaho & Bundy % 8 11% 3 4% LA Baum Bridge % 12 11% 0 0% Lankershim & Vineland % 27 34% 0 0% Lincoln & Bluff Creek % 12 30% 3 6% Lincoln & Venice % 31 25% 1 1% Long Beach & Los Flores % 11 49% 4 19% Los Feliz & Riverside % 24 38% 1 2% National & Overland % 11 41% 2 8% PCH & Temescal Canyon % 8 9% 6 7% Reseda & Orange Line Station % 0 0% 0 0% Santa Monica & Westwood % 32 23% 2 1% Santa Monica & Wilshire % 24 32% 3 4% Sepulveda & Ohio % 33 23% 1 1% Sunset & Hyperion % 6 6% 1 1% Venice & National % 27 24% 1 0% Verdugo & Eagle Rock % 6 18% 0 0% Washington & Admiralty % 26 11% 8 3% Washington & Compton % 40 44% 11 12% Westholme & Wilshire % 5 16% 0 0% Westwood & Le Conte % 29 23% 1 0% Wilshire & Western % 70 76% 4 4% Woodman & Orange Line Station % 15 18% 3 3% Workman & Ave % 5 34% 1 7% York & Ave % 7 26% 3 9% Totals 2,788 1,404 50% % 79 3% 32

34 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 % 33 53% 3 4% 4th & Wilton % 8 17% 2 4% 7th & Figueroa % % 3 1% 8th & La Brea % 36 50% 2 3% 9th & Pacific % 26 45% 19 33% Alvarado & 7th % 0 0% 1 1% Ballona Creek % 0 0% 1 0% Broadway Bridge % 23 37% 19 30% Eagle Rock & Colorado % 20 37% 0 0% Echo Park & Sunset % 23 19% 6 5% Figueroa & Pasadena % 28 30% 2 2% Florence & Graham % 98 82% 0 0% Fountain & Vermont % 56 51% 22 20% Glendale & Park % 14 22% 5 7% Hollywood & Highland % 48 52% 1 1% Hoover & McClintock % % 50 5% Idaho & Bundy % 36 34% 19 18% Kittridge & De Soto % 42 75% 1 2% LA Baum Bridge % 31 19% 1 1% Lankershim & Vineland % 52 53% 1 1% Lincoln & Bluff Creek % 17 49% 0 0% Long Beach & Los Flores % 22 56% 8 21% Los Feliz & Riverside % 24 24% 4 4% Manchester & Hoover % 59 81% 3 3% National & Overland % 14 34% 1 1% Santa Monica & Highland % 77 75% 2 2% Santa Monica & Westwood % 29 19% 0 0% Sepulveda & Ohio % 42 31% 13 9% Sunset & Hyperion % 20 13% 6 4% Topanga & Burbank % 30 84% 0 0% Venice & National % 33 28% 5 4% Washington & Admiralty % 61 15% 17 4% Washington & Compton % 47 52% 14 15% Westholme & Wilshire % 13 25% 0 0% Westwood & Le Conte % 49 22% 0 0% Wilshire & Western % % 2 1% Woodman & Orange Line Station % 16 33% 1 2% York & Ave % 24 60% 4 10% Totals 5,043 1,910 38% 1,747 35% 232 5% 33

35 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 % 28 48% 6 10% 1st & Soto % 25 51% 10 20% 4th & Wilton % 7 20% 2 6% 8th & La Brea % 20 67% 0 0% Adams & Normandie % 75 81% 1 1% Alvarado & 7th % 28 29% 1 1% Ave 19 & N. Broadway % 15 65% 2 9% Ballona Creek 1, % 0 0% 0 0% Cesar Chavez & Soto % 51 67% 21 28% Cypress Ave & 28th & Pepper % 17 40% 4 9% Echo Park & Sunset % 40 35% 10 9% Figueroa & Pasadena % 0 0% 0 0% Florence & Graham % 52 17% 25 8% Fountain & Vermont % 34 35% 1 1% Glendale & Park % 16 28% 1 2% Hollywood & Highland % 24 39% 1 2% Idaho & Bundy % 13 18% 1 1% LA Baum Bridge % 7 7% 4 4% Laurel Canyon & Ventura % 14 33% 0 0% Lincoln & Bluff Creek % 27 54% 0 0% Lincoln & Venice % 90 32% 3 1% Los Feliz & Riverside % 21 32% 10 15% National & Overland % 15 44% 1 3% PCH & Temescal Canyon % 7 2% 4 1% Santa Monica & Highland % 73 82% 0 0% Santa Monica & Westwood % 29 21% 2 1% Santa Monica & Wilshire % 16 26% 0 0% Sepulveda & Ohio % 25 18% 0 0% Sunset & Hyperion % 9 6% 4 3% Topanga & Burbank % 13 41% 0 0% Venice & National % 37 31% 1 1% Verdugo & Eagle Rock % 17 26% 0 0% Washington & Admiralty 1, % 96 9% 39 4% Washington & Compton % 22 48% 10 22% Westholme & Wilshire % 11 34% 0 0% Westwood & Le Conte % 30 41% 0 0% Wilshire & Western % 63 65% 0 0% Woodman & Orange Line Station % 18 23% 0 0% Workman & Ave % 9 38% 0 0% York & Ave % 17 37% 2 4% Totals 6,186 2,788 45% 1,634 26% 372 6% 34

36 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 Los Feliz & Riverside Washington & Admiralty 259 1,2 27 Washington & Compton 35 none Woodman & Orange Line 3 Hoover & McClintock 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 Broadway & Bridge 29 none 7 7th & Figueroa 75 none 32 9th & Pacific 29 none 8 Santa Monica & Westwood Kittridge & De Soto Sepulveda & Ohio 65 1,3 34 1st & Alameda 27 none 10 Westwood & Le Conte Eagle Rock & Colorado Sunset & Hyperion Glendale & Park LA Baum Bridge th & La Brea 23 none 13 Venice & National Verdugo & Eagle Rock 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 Echo Park & Sunset Westholme & Wilshire Lankershim & Vineland 44 none 43 York & Ave none Cypress Ave & 28th & 19 Fountain & Vermont 44 none 44 Pepper 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 Topanga & Burbank 15 none 24 Hollywood & Highland 36 none 49 Ave 19 & N. Broadway Figueroa & Pasadena 35 none 50 Workman & Ave 26 9 none 50 Intersection Average 43 Legend: Paths, Lanes, Routes, and none 35

37 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% th & 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% st & 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% th & 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 Baum Bridge 12% st & Soto 0% none 50 Intersection Average 14% Legend: Paths, Lanes, Routes, and none 36

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

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

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

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

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