EXHIBIT 8
CRASH ANALYSIS – FINDINGS
Glendale Bicycle Plan Update
October 11, 2023
T
he below document outlines findings from the crash analysis portion of the Existing Conditions subtask of the Glendale Bicycle Plan Update. The crash analysis utilizes data on bicycle crashes from California’s Statewide Integrated Traffic Records System (SWITRS) and reflects requested changes to the Crash Analysis methodology.
Incorporating these changes, this analysis utilizes bicycle-involved crashes within the City of Glendale within a ten-year period between 2012 and 2021 and considers all bicycle crashes inclusive of property damage- only (PDO) crashes. Bicycle-involved crashes that took place on a state highway within Glendale have been excluded.
Summary Crash Statistics
The below section presents descriptive data derived from the last ten years of available data from bicycle crashes in the City of Glendale. The descriptive data also notes crashes included from the overall dataset that resulted in fatalities or severe injuries (killed or severely injured, or KSI). 2 General Crash Descriptions
Figure 1. Glendale Bicycle Crashes by Year (2012 – 2021)
0 10
20 30
40 50
60 70
80 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Other Crashes KSI Crashes
3 Figure 2. Bicycle Injury and Fatal Crashes Comparison by Year (2012 – 2021)
Table 1. Bicycle Crashes by Year1
(excluding PDO crashes)
Total
Bicycle
Crashes
%
Crashes
# of KSI
Crashes % of KSI Injury and Fatal Crashes /
100,000 residents
Glendale Pasadena LA County
2012 68 15% 2 10% 27.4 65.1 49.9
2013 61 14% 3 15% 29.8 68.5 46.5
2014 54 12% 4 20% 26.0 76.9 43.7
2015 53 12% 1 5% 21.7 51.1 41.2
2016 53 12% 3 15% 22.0 45.1 37.2
2017 48 11% 6 30% 22.3 45.8 35.6
2018 30 7% 1 5% 13.4 29.7 34.9
2019 32 7% 0 0% 15.6 43.3 33.1
1 The first column of each table lists total bicycle-involved crashes, including those resulting in fatalities or severe injuries (KSI). The KSI columns record the number of KSI crashes (20 total over ten years), and the percent of KSI crashes by year out of that separate total. 0 1,000
2,000
3,000
4,000
5,000
6,000
0 10
20 30
40 50
60 70
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
LA County Injury and Fatal Crashes
Glendale Injury and Fatal Crashes
Glendale LA County
4 2020 25 6% 0 0% 11.7 32.4 24.9
2021 21 5% 0 0% 10.4 39.8 18.4
Grand
Total 445 100% 20 100%
Bicycle crashes in Glendale have declined in the past ten years, from a peak in 2012 at the beginning of the observed period. The most number of severe injuries occurred in 2017. The decrease in overall bicycle-involved crashes in this period follows broader regional trends, as shown in Figure 2. KSI crashes in Glendale peaked in 2017, and none have been recorded in the last three years of the observed period.
The chart also shows rates of bicycle crashes resulting in injury or fatality per 100,000 residents, comparing to Pasadena and broader LA County. PDO crashes were excluded for comparison purposes. Pasadena, a peer city with similar land uses and approximately a third fewer people, also experienced a similar drop in crashes. While a multitude of factors likely influenced this trend, American Community Survey data does show bicycle commuting falling significantly in this period, suggesting fewer people were biking overall. When comparing by population, Glendale has fewer bicycle crashes per 100,000 people than LA County or Pasadena throughout this period.
It should be noted, however, that the data is not normalized by exposure and ridership, and data collected during 2020 and 2021 may be affected by changes in travel patterns brought upon by the COVID-19 pandemic.
Additional factors such as land use, availability of bicycle facilities, and demographic composition also likely influence exposure and ridership rates.
Table 2. Bicycle Crash Severity
Crash Severity # Crashes % Crashes
Property Damage Only 50 11%
Complaint of Pain 165 37%
Other Visible Injury 210 47%
Severe 18 4%
Fatal 2 0.4%
Grand Total 445 100%
Two fatal crashes and 18 crashes resulting in severe injuries took place in City of Glendale streets between 2012 and 2020. Only 11 percent of crashes in Glendale were property damage only, and nearly half resulted in a visible injury. By comparison, Pasadena had a similar distribution of severe and fatal crashes over this period, while LA County as a whole saw higher rates of severe and fatal crashes.
5 Table 3. COVID-19 and Crash Injury Comparison
Year KSI Visible
Injury
Complaint of
Pain PDO Total
Crashes
Pre-COVID-19 Total 1 30 27 4 62
2018 1 15 12 2 30
2019 0 15 15 2 32
COVID-19 Total 0 26 17 3 46
2020 0 13 10 2 25
2021 0 13 7 1 21
The incidence of bicycle-involved crashes within Glendale slowed during the COVID-19 pandemic. Compared to the two preceding years, the total number of crashes fell by approximately 25 percent. Crashes caus ing complaints of pain fell by nearly a third. While there was only one crash resulting in a severe injury in 2018, no crashes caused fatalities or severe injuries during the pandemic. Causes for the sharp reduction during the pandemic likely have multiple complex causes, possibly owing to a combination of changes in commuting behaviors and modes.
Figure 3. Bicycle Crashes by Time of Day
More than half of all crashes, including KSI crashes, occurred during the daytime, between 8:00 am and 4:00 pm.
Notably, nearly a third of crashes occurred in the early evening hours, between 4:00 pm and 8:00 pm, when conditions are darker or becoming darker. KSI crashes followed these trends, with 90 percent taking place during the day or early evening.
0 20
40 60
80 100
120
140
12 - 4 AM 4 - 8 AM 8 AM - 12 PM 12 PM - 4 PM 4 PM - 8 PM 8 PM - 12 AM Total Crashes KSI Crashes
6 Crash Behaviors
Table 4. Most Common Vehicle Code Violation Categories
Violation Category # Crashes % Crashes # of
KSI % of KSI
Wrong Side of Road 98 22% 2 10%
Automobile Right of Way 88 20% 3 15%
Improper Turning 75 17% 2 10%
Other Hazardous Violation 47 11% 2 10%
Traffic Signals and Signs 38 9% 4 20%
Unsafe Speed 31 7% 3 15%
Table 4 shows the six most common vehicle code violation categories cited in the crash data. As this is a selection of most common factors, the table does not total to 445 crashes. These violations include “Wrong Side of the Road,” “Automobile Right of Way,” and “Improper Turning.” The first refers to a vehicle operating on the wrong side of the street or bicyclists not riding as far right as practicable as required by law, while the second includes violations where road users fail to yield properly, such as failing to yield to others when making turns or entering the roadway. “Improper Turning” refers to unsafe turning practices by road users.
Notably, while “Traffic Signals and Signs” and “Unsafe Speed” are cited for only 9 and 7 percent of all crashes respectively, they comprise 20 and 15 percent of KSI crashes. “Unsafe Speed” includes instances where a person was driving or riding at a speed considered “unreasonable,” which includes exceeding the speed limit, while “Traffic Signals and Signs” includes violations such as failing to come to a complete stop at stop signs and red lights. Responding officers to these crashes under these common violation categories found both drivers and bicyclists commonly at fault.
Table 5. Crashes by Collision Type
Collision Type # Crashes % Crashes # of KSI % of KSI
Head-On 15 3% 1 5%
Sideswipe 77 17% 0 0%
Rear End 37 8% 4 20%
Broadside 244 55% 8 40%
Hit Object 4 1% 0 0%
Overturned 3 1% 0 0%
Vehicle/Pedestrian 16 4% 1 5%
Other/Not Recorded 49 11% 6 30%
7 Grand Total 445 100% 20 100%
Table 5 details the distribution of crashes by their collision type, or how the collision physically occurred. Many collisions in this period were broadsides, in which a bicyclist and motorist collided at a right angle. This also contributed to a plurality of KSI crashes, suggesting that conditions relating to broadside crashes may include those that frequently yield more severe crash outcomes, such as higher speeds.
Table 6. Alcohol Involved Crashes
Alcohol
Involved? # Crashes % Crashes # of KSI % of KSI
Yes 26 6% 4 20%
No 419 94% 16 80%
445 100% 20 100%
Table 6 depicts the influence of alcohol in bicycle-involved crashes. Six percent of all crashes involved alcohol, but 20 percent of all KSI crashes involved at least one party being under the influence of alcohol.
Environmental Factors
Table 7. Collision by Lighting Condition
Lighting Condition # Crashes % Crashes # of KSI % of KSI Daylight 348 78% 15 75%
Dusk - Dawn 12 3% 0 0%
Dark - Street Lights 78 18% 4 20%
Dark - No Street Lights 3 1% 1 5%
Not Stated 4 1% 0 0%
Grand Total 445 100% 20 100%
As most crashes took place during the day, daylight lighting is the most common condition. However, almost a fifth of crashes took place during the dark under streetlights. This pattern is shared by KSI crashes as well.
8 Table 8. Collisions by Location in Street
Crash Location # Crashes % Crashes # of KSI % of KSI
At street segment 127 29% 6 30%
At intersection 318 71% 14 70%
Grand Total 445 100% 20 100%
More than a third of bicycle collisions took place at intersections, which, when combined with the above rates of right-of-way and turning vehicle violations, may support a high need for intersection safety improvements.
Bicycle Crash Party Descriptions
Table 9. Bicyclists by Race
Bicyclist Race Count
Not stated 253
White 94
Hispanic 72
Asian 11
Black 9
Other 6
Total 445
Note: Table 9 documents the race of bicyclist parties involved in crashes, as is presented in the SWITRS crash data. For more than half of people involved in a crash, no race was provided.
Additional work may be done to separate racial makeup of crash victims from other parties involved; however, the large number of missing entries may not yield data that is easily comparable to other trends or conditions.
Table 10. Bicyclist Victims by Age
Ages Number of
Victims Percent of Victims Number of
KSI Victims
Percent of
KSI Victims
7-14 35 8% 1 5%
9 15-19 61 14% 0 0%
20-24 46 10% 0 0%
25-29 56 13% 4 20%
30-34 51 11% 1 5%
35-39 26 6% 1 5%
40-44 29 7% 2 10%
45-49 28 6% 3 15%
50-54 31 7% 3 15%
55-59 32 7% 3 15%
60-64 14 3% 0 0%
65-69 13 3% 0 0%
70 and Above 12 3% 1 5%
Unknown 11 2% 1 5%
Total 445 100% 20 100%
Figure 4. Bicycle Crash Victims by Age Range2
2 For summary purposes, age ranges are not presented in equal intervals. 0 20
40 60
80 100
120
140
160
180
7-19 20-34 35-49 50-64 65 and above
Number of Victims Number of KSI Victims
10 More than 50 percent of crash victims were 34 or younger, and more than a third were between the ages of 20 and 34.
Table 11. Collision Victims by Gender
Gender Total Crashes Percent of Total
Crashes KSI Crashes Percent of KSI
Crashes
Female 55 12% 3 15%
Male 385 87% 17 85%
Unknown 5 1% 0 0%
Grand Total 445 100% 20 100%
11 Bicycle Crash Density
The below map shown in Figure 5 demonstrates the density of bicycle-involved crashes within the City of Glendale. As with the above summary statistics, this analysis uses 2012-2021 crash data from the Statewide Integrated Traffic Record System.
Methodology
Based on these trends, several Safety Corridors have been identified. The analysis uses the Sliding Windows methodology to understand crashes throughout the street network, identifying segments with the highest crash density, weighted by crash severity. The analysis is done by determining the number and severity of crashes in a half-mile “window” on a roadway and shifting that window along the roadway 1/10 mile at a time. Crashes are weighted by severity, and individual street segments receive a score. Following input from the Project Development Team, crashes resulting in only property damage were included in the analysis. To preserve the balance in segment scoring by severity, weights were adjusted to five points for KSI crashes, two points for all other injuries, and one point for PDO crashes.
The below findings present the results of the Sliding Windows analysis of historical crash data with functional classifications, with some cleaning conducted to remove segments double-counted at intersection crashes. The list comprises the highest-scoring segments, as well as several additional streets that included consistent clusters of crashes. The Sliding Windows results may be further modified based on additional considerations, such as ground truthing lane width, intersection conditions on high-scoring segments, and stakeholder input.
Initial Findings
The below Safety Corridors are largely major arterials that connect major destinations, neighborhoods, and commercial areas in downtown and central Glendale. Several arterials, such as Glenoaks Blvd and Brand Blvd, are key connections to Burbank and Los Angeles, respectively. Several corridors that cross SR -134 north-south appear in the list: these are often where access across the highway is restricted to major streets. No streets in northern Glendale appeared in the list, as fewer crashes occurred there.
The inclusion of additional years of bicycle crash data, as well as PDO crashes, within the analysis, surfaced several additional low and medium crash density segments, several of which are along residential streets. These include Columbus Ave and Riverdale Dr in southwestern Glendale, as well as E Chevy Chase Dr and E Glenoaks Blvd as they pass beneath the 2 Freeway in eastern Glendale.
Highest-scoring streets generally include wide thoroughfares with four-to-six lanes and no bicycling infrastructure.
Some, such as Pacific Ave and Broadway, include sharrow markings on the outer lanes to signify bicycling routes.
Glenoaks Blvd, which is six lanes wide with a planted median, does include a striped, Class II bike lane adjacent to parking lanes. Central Ave features Class II bike lanes as well, though these end to the north of the highest scoring segment (Broadway to Chevy Chase Dr).
Table 12. Draft Safety Corridors
CORRIDOR FROM TO
GLENOAKS BLVD Allen Ave Brand Blvd
S BRAND BLVD Los Feliz Rd Glenoaks Blvd
COLORADO ST Pacific Ave Brand Blvd
12 BROADWAY San Fernando Rd Chevy Chase Dr
S GLENDALE AVE San Fernando Rd Chestnut St
N GLENDALE AVE/
VERDUGO RD
Broadway Mountain St
PACIFIC AVE Broadway Glenwood Rd
SAN FERNANDO RD Central Ave SR-134
S CENTRAL AVE Broadway Chevy Chase Dr
CHEVY CHASE DR Windsor Rd Broadway
13 Figure 5. Revised Bicycle Crash Density and Bicycle Crashes (2012 – 2021)