Local_Road_Safety_Plan.pdf

City of Calabasas

Local Roadway Safety Plan (LRSP)

MAY 2022

Prepared for:

City of Calabasas

Department of Public Works

100 Civic Center Way

Calabasas, CA 91302

Prepared By:

2141 W. Orangewood Avenue, Suite A

Orange, CA 92868

T: 714.573.0317 | F: 714.573.9584 www.koacorp.com

JC13044

CITY OF CALABASAS | LRSP PAGE 1

TABLE OF CONTENTS

1.0 EXECUTIVE SUMMARY 5

2.0 INTRODUCTION 7

2.1 Five E’s of Transportation Safety

2.2 Purpose of the LRSP

2.3 City of Calabasas

2.4 LRSP Overview

2.4.1 Data Collection 9

2.4.2 Safety Data Analysis 9

2.4.3 Identify Safety Measures 9

2.4.4 Develop Safety Projects And Cost Estimates 9

3.0 METHODOLOGY 10

3.1 Crash Data Source

3.1.1 SWITRS 10

3.1.2 TIMS 10

3.2 Identifying Locations for Engineering Countermeasures

3.2.1 Ranking Function 11

3.2.2 Average Crash Frequency 11

3.2.3 Crash Rate 11

3.2.4 EPDO Scores 11

3.3 Stakeholder Outreach

3.4 Proposing Engineering Countermeasures

4.0 SYSTEMIC SAFETY ANALYSIS – CRASH TREND AND PATTERNS 13

4.1 Total Crashes and KSI Crashes

4.2 Crashes by Facility Type

4.3 Calabasas vs. Los Angeles County

4.4 Calabasas vs. Cities of Similar Sizes

5.0 TRANSPORTATION SAFETY EMPHASIS AREAS 28

5.1 Automobile Right-of-Way, Head-on, and Sideswipe Crashes

5.2 Pedestrians And Bicyclists

5.3 Signalized Intersections

5.4 Speeding and Broadside Crashes

5.5 Young Drivers

6.0 ENGINEERING COUNTERMEASURES 32

6.1 Systemic Safety Countermeasures

6.2 Identify Project Locations

6.2.1 Identified Roadway Segment 35

6.2.2 Identified Intersections 40

6.3 Roadway Segment Recommendations

6.3.1 Calabasas Road between Mureau Road and Parkway Calabasas 42

6.3.2 Las Virgenes Road between Agoura Road and Mureau Road 43

6.3.3 Las Virgenes Road between Lost Hills Road and City Boundary 44

6.3.4 Calabasas Road between Park Granada and City Boundary 45

6.3.5 Agoura Road between Lost Hills Road and Las Virgenes Road 46

6.4 Intersection Recommendations

6.4.1 Calabasas Road and Parkway Calabasas 47

6.4.2 Las Virgenes Road and Agoura Road 50

6.4.3 Mulholland Highway and Old Topanga Canyon Road 52

6.4.4 Las Virgenes Road and Mureau Road 53

6.4.5 Parkway Calabasas and Park Granada 55

6.4.6 Lost Hills Road and Calabasas Hills Road 57

6.4.7 Las Virgenes Road and Lost Hills Road 59

6.4.8 Lost Hills Road and Agoura Road 61

6.4.9 Calabasas Road and Park Granada 63

6.4.10 Mulholland Highway and Paul Revere Drive 65

6.4.11 Parkway Calabasas and Camino Portal 67

7.0 NON-ENGINEERING SAFETY MEASURES 69

7.1 Funding Sources

7.2 Young Drivers

7.2.1 Education 71

7.2.2 Enforcement 72

7.2.3 Funding Sources 72

7.3 Rear-ends and Speeding

7.3.1 Education 73

7.3.2 Encouragement/Emerging Technology 73

7.3.3 Enforcement 73

7.3.4 Funding Sources 73

7.4 Improper Turning/Hit-Object/Sideswipe

7.4.1 Encouragement/Emerging Technology 74

7.4.2 Enforcement 74

7.4.3 Funding Source 74

8.0 SAFETY PROJECTS 76

8.1 Project Scopes and Benefit Calculations

8.2 Cost Estimate

8.3 Benefit/Cost Ratio

8.4 Project Prioritization

8.5 Funding Sources

LIST OF FIGURES

Figure 2.1 Calabasas Citywide Crash Severity Map (2015-2020)

Figure 4.1 Crash Severity

Figure 4.2 Total Crashes by Year

Figure 4.3 Crashes by Type, Total Crashes vs. KSI Crashes

Figure 4.4 Crashes by Primary Crash Factor (PCF), Total Crashes vs. KSI Crashes

Figure 4.5 Primary Crash Factor vs. Top 4 Crash Types

Figure 4.6 At-Fault Parties by Age and Gender

Figure 4.7 Pedestrian Crashes At-Fault vs. As Victim

Figure 6.1 Top Roadway Segments Map (EPDO)

Figure 6.2 Proposed Roadway Segment Countermeasures

Figure 6.3 Proposed Intersections Countermeasures

Figure 6.4 Crash Statistics – Calabasas Road

Figure 6.5 Crash Statistics – Las Virgenes Road

Figure 6.6 Crash Statistics – Las Virgenes Road

Figure 6.7 Crash Statistics – Calabasas Road

Figure 6.8 Crash Statistics – Agoura Road

Figure 6.9 Crash Statistics – Calabasas Road & Parkway Calabasas

Figure 6.10 Recommended Improvements – Calabasas Road & Parkway Calabasas

Figure 6.11 Crash Statistics – Las Virgenes Road and Agoura Road

Figure 6.12 Recommended Improvements – Las Virgenes Road and Agoura Road

Figure 6.13 Crash Statistics – Mulholland Highway and Old Topanga Canyon Road

Figure 6.14 Crash Statistics – Las Virgenes Road and Mureau Road

Figure 6.15 Recommended Improvements – Las Virgenes Road and Mureau Road

Figure 6.16 Recommended Improvements – Parkway Calabasas and Park Granada

Figure 6.17 Recommended Improvements – Parkway Calabasas and Park Granada

Figure 6.18 Crash Statistics – Lost Hills Road and Calabasas Hills Road

Figure 6.19 Recommended Improvements – Lost Hills Road and Calabasas Hills Road

Figure 6.20 Crash Statistics – Las Virgenes Road and Lost Hills Road

Figure 6.21 Recommended Improvements – Las Virgenes Road and Lost Hills Road

Figure 6.22 Crash Statistics – Lost Hills Road and Agoura Road

Figure 6.23 Recommended Improvements – Lost Hills Road and Agoura Road

Figure 6.24 Crash Statistics – Calabasas Road and Park Granada

Figure 6.25 Recommended Improvements – Calabasas Road and Park Granada

Figure 6.26 Crash Statistics – Mulholland Highway and Paul Revere Drive

Figure 6.27 Recommended Improvements – Mulholland Highway and Paul Revere Drive

Figure 6.28 Crash Statistics – Parkway Calabasas and Camino Portal

Figure 6.29 Recommended Improvements – Parkway Calabasas and Camino Portal

Figure 7.1 DUI Crashes as per Age Group

LIST OF TABLES

Table 4.1 Crashes by Facility Type

Table 4.2 Crash Types by Facility Type

Table 4.3 Street Lighting by Facility Type

Table 4.4 Primary Crash Factor by Facility Type

Table 4.5 Automobile Right-of-Way due to Broadside Crashes by Facility Type

Table 4.6 Improper Turning due to Broadside Crashes by Facility Type

Table 4.7 Automobile Right-of-Way with Head-On and Sideswipe Crashes by Facility Type

Table 4.8 Total Crash Comparison, Calabasas vs. Los Angeles County

Table 4.9 KSI Crash Comparison, Calabasas vs. Los Angeles County

Table 4.10 Crash Type Comparison, Calabasas vs. Los Angeles County

Table 4.11 PCF Comparison, Calabasas vs. Los Angeles County

Table 4.12 2019 OTS Ranking, Calabasas

Figure 5.1 Map of Pedestrian and Bicycle Crashes

Table 6.1 Common Causes and Countermeasures-Citywide Crashes

Table 6.2 Safety Countermeasures Applied to City of Calabasas LRSP

Table 6.3 Systemic Safety Countermeasures Applied to City of Calabasas LRSP

Table 7.1 Transportation Safety Funding Sources Summary

Table 7.2 Young Driver Program Funding Sources

Table 7.3 Rear-end and Speeding Program Funding Sources

Table 7.4 Improper Turning/Hit Object/Sideswipe Crash Program Funding Sources

Table 8.1 Recommended Safety Project Scopes

Table 8.2 Benefits/Cost Ratio Analysis by Recommended Safety Project

Table 8.3 Benefits/Cost Ratio Analysis by Systemic Safety Project

Table 8.4 Benefits/Cost Ratio Analysis by Recommended Safety Projects

Table 8.4: Transportation Safety Funding Sources Summary

CITY OF CALABASAS | LRSP PAGE 5

1.0 EXECUTIVE SUMMARY

The California Department of Transportation (Caltrans) established a program for cities to prepare a Local

Roadway Safety Plan (LRSP) to identify safety needs and recommend projects to address these needs. This document serves as the LRSP for the City of Calabasas.

Overview

An LRSP analyzes crash data, assesses infrastructure deficiencies through an inventory of roadway system elements, and identifies roadway safety solutions on a citywide basis. Caltrans created the statewide LRSP program to help local agencies develop safety projects that can be submitted for funding by the Highway

Safety Improvement Program (HSIP). HSIP Cycle 11, expected around April 2022, and subsequent cycles will require an LRSP or equivalent plans such as a Vision Zero Plan or System Safety Analysis Report.

This report has been prepared per Caltrans LRSP guidelines and the Caltrans Local Roadway Safety Manual

(LRSM) version 1.6 dated April 2022. The general content of this LRSP report follows this outline:

● Crash data source and analysis techniques

● Crash data analysis results and highest occurring crash types

● High-risk corridor and intersection analysis and safety countermeasures

● Cost estimates of recommended improvements

● Prioritization of projects based on cost-benefit ratio and effectiveness of safety improvement

● Strategies for safety project implementation

● Traffic safety enforcement size analysis based on Office of Traffic Safety (OTS) data

The LRSP fulfills the following purposes:

● Identify the highest occurring crash types and the roadway characteristics contributing to the crashes.

● Identify high-risk corridors and intersections.

● Propose safety countermeasures to address the safety issues.

● Prioritize safety improvement projects based on benefit/cost ratio and other considerations.

Prominent Crash Pattern

Six years of crash records were utilized from January 2015 to December 2020, adhering to the maximum period permitted by the HSIP for a safety infrastructure project application for federal funding. The crashes were categorized by severity, crash type, Primary Crash Factor (PCF), involved parties, lighting conditions, and facility type (signalized intersections, non-signalized intersections, and mid-block locations). A total of

797 crashes were recorded from 2015 to 2020. The following summarizes the crash patterns within the City:

● Most common crash types were rear end, sideswipe, and broadside.

● Unsafe speed-related crashes accounted for approximately twenty percent of total crashes, one percent of severe injury crashes, and sixty-one percent of property damage crashes.

● Rear-end crash related to unsafe speeding is one of the prominent crash patterns.

EXECUTIVE SUMMARY

CITY OF CALABASAS | LRSP PAGE 6

Safety Measures

The following transportation safety emphasis areas were identified based on the crash data analysis:

● Improper Turning, Hit Object, and Sideswipe Crashes

● Pedestrian Crashes

● Crashes at signalized Intersections

● Speeding and Rear-End Crashes

The LRSP recommends engineering countermeasures derived based on discussions with the Public Works

Department and the Traffic and Transportation Commission to identify emphasis areas, and crash patterns.

In addition to infrastructure improvements, non-engineering safety measures address traffic safety concerns through education and enforcement. The emphasis areas were utilized to identify non-engineering programs. Several state and federal grant programs offer funds for non-engineering programs, such as:

a) Advanced Transportation and Congestion Management Technologies Deployment Program

b) Active Transportation Program

c) Sustainable Communities Grant Program

d) Office of Traffic Safety Grants

INTRODUCTION

CITY OF CALABASAS | LRSP PAGE 7

2.0 INTRODUCTION

The City of Calabasas has retained KOA Corporation (KOA) to develop a Local Roadway Safety Plan (LRSP).

Traditionally, agencies have selected safety projects based on historical crash records, focusing on sites with a concentration of recent severe crashes. By contrast, the LRSP shares a similar framework with the

California Statewide Strategic Highway Safety Plan (SHSP), which focuses on engineering and non-engineering solutions to roadway safety issues. The LRSP identifies the most common crash categories across a roadway network to target projects that address the factors associated with those categories. The

LRSP allows agencies to assess risks before a crash by focusing on causal factors rather than crashes.

Systemic improvements target broader geography than the traditional spot location improvements. The systemic project selection favors the broad implementation of cost-effective countermeasures.

2.1 FIVE E’S OF TRANSPORTATION SAFETY

The LRSP not only focuses on engineering improvements to mitigate crashes. The LRSP also addresses the other safety improvements in other areas such as enforcement, education, and emergency services.

According to the SHSP 2020-2024, two-thirds of all crashes are the result of aggressive driving. Male drivers are more likely to be at fault in aggressive driving-related crashes regardless of age. Making roadways safer requires the Four E’s: Engineering, Enforcement, Education, and Emergency Services. Working together with the Four E’s at the city level will help make city roads safer. Recently, Federal and State agencies have also considered Emerging Technologies and Equity as additional E’s to improve traffic safety. For instance, considering the use of emerging technologies such as “smart” traffic signal equipment can serve to connect vehicle and traffic control systems to enhance traffic safety.

2.2 PURPOSE OF THE LRSP

The LRSP systematically identifies and analyzes safety problems and recommends safety improvements.

Preparing the LRSP facilitates collaboration by developing partnerships between Calabasas and stakeholders, which includes the Los Angeles County Sheriff’s Department and the Los Angeles County Fire

Department. The results of the LRSP are summarized with a prioritized list of improvements and actions.

The LRSP offers a proactive approach to addressing roadway safety needs in Calabasas.

2.3 CITY OF CALABASAS

Calabasas is a city in western Los Angeles County. According to the 2010 census, the Calabasas had a population of 23,058 the US Census estimated the 2020 population at 23,2411.

Based on the Statewide Integrated Traffic Records System (SWITRS) database, between January 2015 and

December 2020 there were 797 crashes in Calabasas, of which 9 crashes resulted in severe injuries. Figure

2.1 illustrates a map of the crashes citywide.

1 Source: United States Census Bureau

CITY OF CALABASAS | LRSP PAGE 8

Figure 2.1 Calabasas Citywide Crash Severity Map (2015-2020)

CITY OF CALABASAS | LRSP PAGE 9

2.4 LRSP OVERVIEW

The LRSP project includes six primary tasks. The following sections include a brief description of the tasks associated with this project, with a more detailed description of each task in subsequent sections of this document.

2.4.1 Data Collection

A comprehensive Geographic Information Systems (GIS) project database was developed by utilizing the following data, which was provided by Calabasas:

● Six-years (1/1/2015 to 12/31/2020) of crash data collected via the SWITRS crash databases

● Location of signalized intersections

2.4.2 Safety Data Analysis

Following the development of the comprehensive Geodatabase, the crash data was analyzed for Calabasas.

Crashes were compared to the safety emphasis areas as defined in the California SHSP. The safety data analysis is summarized in Section 4 of this document. The transportation emphasis areas are identified based on the crash data analysis and are discussed in Section 5 of this document.

2.4.3 Identify Safety Measures

In coordination with city staff, a list of engineering-related safety countermeasures and non-engineering safety measures were developed for use as recommendations in this LRSP. These countermeasures are discussed in Section 6 and Section 7 of this document.

2.4.4 Develop Safety Projects And Cost Estimates

Roadways and intersections were ranked based on EPDO (Equivalent Property Damage Only), and the crash frequency. The top 11 locations of interest will be investigated for further evaluation and potential safety improvements. The improvements include signal hardware improvement, additional warning signage, and bikeway-related features. Planning-level cost estimations are provided for each safety project. The list of safety projects are prioritized based on the following considerations:

● Benefit/Cost Ratio (for engineering solutions only)

● Funding availability for engineering and non-engineering programs

● Other factors recommended by city staff

The safety projects and cost estimates are discussed in Section 8 of this document.

CITY OF CALABASAS | LRSP PAGE 10

3.0 METHODOLOGY

3.1 CRASH DATA SOURCE

The crash data drew from SWITRS. The crash trend data was derived between 2015 and 2020 from the

California Highway Patrol’s Statewide Integrated Traffic Records System (SWITRS) database. SWITRS is a database that collects and processes data gathered from a crash scene.

3.1.1 SWITRS

The California Highway Patrol’s SWITRS database contains data on statewide crashes. The SWITRS application provides geographically- and temporally-targeted crash reports in an electronic format. KOA used SWITRS to evaluate data on Calabasas crashes between 2015 and 2020, both in aggregate and classified by control type (signalized, non-signalized, and midblock locations).

3.1.2 TIMS

UC Berkeley Safe TREC’s Transportation Injury Mapping System (TIMS) database contains geocoded crashes included in the SWITRS database. TIMS geocodes SWITRS crashes that involve either an injury or fatality (i.e., excluding property damage-only crashes). Thus, TIMS provides local agencies with an efficient and straightforward tool to conduct geographic analysis. KOA utilized TIMS data from 2015 to 2020 to compare Calabasas with Los Angeles County at large to identify prominent transportation safety issues in the City.

3.2 IDENTIFYING LOCATIONS FOR ENGINEERING COUNTERMEASURES

Crash data analysis for this LRSP was conducted using crash data from the SWITRS crash database. The crash records include a variety of information about each crash, including the location, date, time of the day, crash type, crash severity, primary violation category, transportation mode of the involved parties, and movement of the involved parties prior to the crash. Per California state law, motor vehicle crashes must be reported when vehicle or property damage exceeds $1,000 or when any of the parties suffer an injury or fatality. Crashes with no injured parties or minor property damage might not be reported and, therefore, are not included in the crash database.

Caltrans’ Local Roadway Safety, A Manual for California’s Local Road Owners, Version 1.6, April 2022 (LRSM) encourages a pro-active rather than reactive approach to safety issue identification. Traditionally, agencies using a reactive approach have located and implemented safety projects solely based on recent crashes, specific crash concentrations, or safety issues raised by stakeholders. A pro-active approach is preferred, according to the LRSM, because with traditional methods, “crash concentrations and crash trends may be missed if local agencies rely exclusively on these identifiers for their roadway safety effort.” A proactive approach would identify safety improvements by analyzing the safety of the entire roadway network. For this document, the process for identifying candidate locations for safety improvements considers any one of the following three factors:

● An extensive crash history at high-crash frequency locations provides insight into which roadway characteristics are associated with certain types of crashes

SYSTEMIC SAFETY ANLAYSIS – CRASH TREND AND PATTERNS

CITY OF CALABASAS | LRSP PAGE 11

● Professional engineering judgment regarding the availability of feasible engineering countermeasures to fix the safety issues

● Applicability of the engineering countermeasures at other locations with roadway characteristics associated with similar types of crashes regardless of their crash history.

The LRSM guidelines require analyzing at least three to five years of the most recent crash data. Six years-worth of crash data from January 2015 to December 2020 was reviewed for the Calabasas LRSP. Six years of crash data usage adheres to the maximum threshold permitted by the Highway Safety Improvement

Program (HSIP) for a safety infrastructure project application for federal funding.

3.2.1 Ranking Function

A candidate intersection or roadway segment for safety improvements does not necessarily need to demonstrate a history of high or severe crashes to be considered for further evaluation. However, locations with high numbers of crashes are often good starting points for safety analysis due to the rich information provided by the crash history. EPDO ranking methods were utilized to identify high crash frequency intersections and roadway segments.

3.2.2 Average Crash Frequency

Average Crash Frequency is the most basic method for assessing crash incidence. The analysis tallies the numbers of crashes at each location in the roadway network, both in aggregate and by a category of interest (e.g. level of severity, crash type, and others). The analysis then ranks intersections or roadway segments based on the crashes’ frequency.

3.2.3 Crash Rate

The Crash Rate method goes a step beyond average crash frequency, normalizing facilities’ crash frequency by the amount of vehicle traffic or travel. This method divides the number of crashes (or crashes in a particular category) by the quantity of Million Entering Vehicles (for intersections) or 100 Million Vehicle

Miles Traveled (for roadway segments). While the Crash Rate method accounts for differences in facilities’ length and traffic volume, it may instead unduly favor low-volume and low-crash roadways where countermeasures produce the lowest net benefit for travelers.

3.2.4 EPDO Scores

Equivalent Property Damage Only (EPDO) scores assign weighting factors to crashes by severity relative to property damage only (PDO) crashes. The weight generally reflects an order of magnitude difference between the cost of fatal/severe injury crashes and non-severe injury crashes. The weights by crash severity come from the 2020 Local Roadway Safety Manual.

● Fatal and Severe Injury at signalized intersections – $1,590,000

● Fatal and Severe Injury at non-signalized intersections – $2,530,000

● Fatal and Severe Injury at Roadway – $2,190,000

● Other Visible Injury – $142,300

● Compliant of Pain – $80,900

● PDO – $13,300

CITY OF CALABASAS | LRSP PAGE 12

EPDO scores are useful for a benefit-to-cost analysis as crash costs can be translated into measurable benefits from installing improvements that reduce the crashes in question. However, EPDO scores may place undue weight on the injury outcomes of previous crashes rather than overall trends suggested by crash patterns regardless of injury outcome. Furthermore, a location’s EPDO score could be inflated by a fatal or severe crash caused by DUI.

3.3 STAKEHOLDER OUTREACH

In addition to using analytical methods to identify locations for treatments and make recommendations, the LRSP also focuses on partnerships with the public agency and community to offer input into this process and provide feedback on areas that the LRSP should focus on. Stakeholders are contacted after completing the crash analysis but before emphasis areas and specific infrastructure improvements or programs are finalized. Stakeholders are asked to provide feedback about traffic safety issues they have observed through their work and possible approaches to resolving these issues. For the Calabasas LRSP, input and feedback were provided by Public Works staff and A.C. Stelle Middle School via on-site/in-field surveys, as well as the Traffic & Transportation Commission via two (2) public virtual meetings.

3.4 PROPOSING ENGINEERING COUNTERMEASURES

After ranking the intersections and roadway segments, and evaluating comments received through public stakeholder outreach, the following steps were used to propose engineering countermeasures:

● Make citywide crash maps for dominant crash types such as rear-end crashes, broadside crashes, bicycle and pedestrian crashes, and crashes due to unsafe speed. Identify high-risk locations by crash type.

● Review crash details (party involved, movement before the crash, primary crash factor, violation code, time of the day, and others) at high-risk locations. Obtain detailed police reports from the City and reviewed for all the fatal and severe injury crashes.

● Manually create crash diagrams for high-risk locations. Review field conditions through physical site visits in the City. Assess the nature of prevalent crash types with respect to the intersection’s control type, geometrical features, and signal phasing/timing.

● Review current conditions and recent historical conditions via Google Map Street View, whenever necessary, to check whether any geometry, signal, or signage changes have been made in the past few years.

● Evaluate and screen countermeasures from the LRSM or Crash Modification Factor (CMF)

Clearinghouse (http://www.cmfclearinghouse.org/), a searchable database that can be easily queried to identify CMFs and Crash Reduction Factors (CRFs).

● Identify intersections/roadway segments that do not have a demonstrated crash history but resemble other locations with documented crash history and risk factors or were identified through public outreach. Once identified, these locations can also be analyzed through the steps mentioned above.

CITY OF CALABASAS | LRSP PAGE 13

4.0 SYSTEMIC SAFETY ANALYSIS – CRASH TREND AND

PATTERNS

4.1 TOTAL CRASHES AND KSI CRASHES

The crash trend analysis draws from the six years of data obtained from the SWITRS database. From 2015 to 2020, a total of 797 crashes occurred on Calabasas’s roadways. Nine crashes resulted in fatal or severe injuries (KSI), as shown in Figure 4.1. Figure 4.2 shows that the annual number of crashes increased substantially, from around 113 to 179 crashes between 2015 and 2017. Crashes decreased slightly, from

179 to 124 crashes between 2017 and 2019, and experienced a sharp drop to 96 crashes between 2019 and 2020.

In contrast, bicycle and pedestrian crashes display an upward trend across the six years of data, as shown in Figure 4.2. The annual number of bicycle crashes decreased from four in 2015 to one in 2020, while the annual number of pedestrian crashes remain same through 2015 to 2020. The number of KSI crashes decreases from three crashes in 2015 to one crash in 2020.

Figure 4.1 Crash Severity

Source: SWITRS, 2015-2020

Complaint of Pain

25.72%

Property Damage

Only

60.73%

Severe Injury

1.13%

Visible Injury

12.42%

TOTAL CRASHES: 797

CITY OF CALABASAS | LRSP PAGE 14

Figure 4.2 Total Crashes by Year

Figure 4.3 breaks down the total and KSI crashes by crash type. Broadside accounted for the largest category, comprising 28 percent of total crashes Rear End (24 percent of total) and Sideswipe (20 percent of total) made up the second- and third-largest crash categories. Among the KSI crashes, Broadside (23 percent), Head-On (22 percent), Hit Object (22 percent), and Vehicle-Pedestrian (11 percent) crashes were the four most-frequently-occurring categories. Overall, the data attest to the high frequency of rear-end, sideswipe, and broadside crashes in Calabasas.

Figure 4.3 Crashes by Type, Total Crashes vs. KSI Crashes

2 2

2 2

2015 2016 2017 2018 2019 2020

T o ta l

C ra sh e s

Bicycle

Pedestrian

KSI

Total

Broadside

28%

Head-On

6%

Hit Object

14%Unknown

3%

Other

2%

Overturned

1%

Rear End

24%

Sideswipe

20%

Veh/Ped

2% Broadside

23%

Head-On

22%

Hit Object

22%

Other

11%

Overturned

11%

Veh/Ped

11%

Total KSI Crashes: 9

CITY OF CALABASAS | LRSP PAGE 15

Figure 4.4 summarizes the Primary Crash Factor (PCF) for all the crashes in the past five years. PCF is the leading cause of a crash based on the opinion of the police officer who conducted the investigation.

Among the total set of crashes, unsafe speed (20.45%), automobile right of way (19.7%), and improper turning (16.44%) were the top three PCFs. For KSI crashes, the top four PCF categories were unsafe speed

(33%), improper turning (22%), automobile right-of-way (11%), and driving or bike under influence (11%).

The other improper driving and pedestrian violation PCFs occurred more frequently among KSI crashes than among total crashes. The latter instance of over-representation reflects the prevalence of vehicle-pedestrian crashes among severe injury crashes.

Figure 4.4 Crashes by Primary Crash Factor (PCF), Total Crashes vs. KSI Crashes

0.13%

0.13%

0.13%

0.25%

0.38%

0.38%

0.50%

0.63%

1.13%

1.25%

2.01%

5.40%

4.64%

5.02%

5.52%

6.90%

9.03%

16.44%

19.70%

20.45%

11%

11%

11%

22%

11%

33%

Brakes

Impeding Traffic

Other Improper Driving

Hazardous Parking

Other Equipment

Pedestrian Violation

Other Hazardous Violation

Pedestrian Right of Way

Other Than Driver/Ped

Improper Passing

Wrong Side of Road

Unknown

Unsafe Strating or Backing

Unsafe Lane Change

DUI

Traffic Signals and Signs

Following Too Closely

Improper Turning

Automobile ROW

Unsafe Speed

KSI Collisions All Collisions

CITY OF CALABASAS | LRSP PAGE 16

Figure 4.5 illustrates how the most-frequently-occurring PCFs correlate with the four largest crash types.

PCF of unsafe speed and following too closely was mostly associated with rear-end crashes. Rear-end crashes often result from a motorist traveling so fast to be unable to decelerate swiftly or not maintain a proper distance from the vehicle ahead of them. Improper turning, unsafe lane changes, and unsafe speed were most frequently associated with sideswipe crashes. Automobile right-of-way, traffic signal and signs, and improper turning were the three most common PCFs for broadside crashes. And unsafe speed, improper turning, and DUI PCFs were responsible for the significant number of hit object crashes (although hit object crashes only comprised a range of crashes in the DUI category). Rear-end and broadside crashes were the second-most-common crash types associated with unsafe speed and automobile right-of-way violations, respectively.

Figure 4.5 Primary Crash Factor vs. Top 4 Crash Types

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Brakes

Impeding Traffic

Hazardous Parking

Other Equipment

Pedestrian Violation

Other Hazardous Violation

Pedestrian Right of Way

Other Than Driver/Ped

Improper Passing

Wrong Side of Road

Unknown

Unsafe Strating or Backing

Unsafe Lane Change

DUI

Traffic Signals and Signs

Following Too Closely

Improper Turning

Automobile ROW

Unsafe Speed

Broadside

Rear End

Sideswipe

Hit Object

CITY OF CALABASAS | LRSP PAGE 17

At-fault drivers in crashes in Calabasas tended to be young males, as shown in Figure 4.6. Nearly 33 percent of drivers were 20-24 and nearly 66 percent of drivers between the ages of 15 and 24. Section 7.2.1 discusses potential education programs directed at this demographic. This age range accounts for the largest share of at-fault motorists, with the number of at-fault motorists decreasing as the age groups grow older. In most age groups, men accounted for more of the at-fault motorists.

Figure 4.6 At-Fault Parties by Age and Gender

.1

.0

.5

.7

.4

.9

.9

.2

.0

.2

.5

.4

.6

.2

.9

.5

.3

.9

.3

.0

% 9 .3

.3

.6

.3

.7

.0

.7

.0

.0

% 3 .0

.7

Under 15 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80 and

Older

Unknown

T o ta l

C ra sh e s

Age

Male Female

CITY OF CALABASAS | LRSP PAGE 18

KOA also analyzed the age and at-fault status of pedestrian parties in pedestrian crashes. Figure 4.7 shows that while pedestrian parties were somewhat evenly distributed across age groups. All but one party under

15 years old were deemed as a victim. Although the single crash identified at fault in the youngest group may be statistically insignificant the City should continue to monitor this data trend. A lack of familiarity with pedestrian safety laws and practices in younger pedestrian and/or inadequate crossing accommodations may contribute to inconsistent crossing behavior.

Figure 4.7 Pedestrian Crashes At-Fault vs. As Victim

50% 50%

6% 19%

13%

6% 6%

13% 13% 13%

6% 6%

Under 15 15-19 20-24 25-29 35-39 40-44 50-54 60-64 70-74 80 and

Older

Unknown

T o ta l

C ra sh e s

Age

Pedestrian at Fault Pedestrian as Victim

CITY OF CALABASAS | LRSP PAGE 19

4.2 CRASHES BY FACILITY TYPE

Crash patterns were analyzed by facility type (intersections vs. mid-block locations) using the most recent six years of crash data (2015 to 2020). This analysis allowed for the determination of the effect of access control and intersection geometry on crash frequency. The analysis classifies crashes by facility type as follows:

● Crashes that occurred within 250 feet of signalized intersections are considered signalized intersection crashes;

● Crashes that occurred within 150 feet of non-signalized intersections are considered non-signalized intersection crashes;

● Crashes that occur more than 250 feet away from any signalized intersection and more than 150 feet away from any non-signalized intersection are classified as mid-block crashes.

Table 4.1 shows the total number of crashes associated with each type of facility, 34 percent of all crashes took place at signalized intersections, 28 percent of all crashes took place at non-signalized intersections, and 36 percent of crashes took place at mid-block locations. Both bicycle and pedestrian crashes showed similar patterns, with most crashes occurring at midblock locations (67 percent for bicycle crashes and 58 percent for pedestrian crashes).

The majority of signalized intersections among crash locations reflect limited intersection density and driveway access on arterial roadways like Parkway Calabasas, Las Virgenes Road and Calabasas Road. These three roadways alone account for over 50 percent of all crashes in Calabasas.

Table 4.1 Crashes by Facility Type

Crash

Grouping

Signalized

Intersection

Non-Signalized

Intersection Midblock Locations Grand Total

Crashes % Crashes % Crashes % Crashes %

Total Number of Crashes 275 34.5% 229 28.7% 293 36.8% 797 100%

Bicycle

Crashes 2 16.7% 2 16.7% 8 66.6% 12 100%

Pedestrian

Crashes 2 16.7% 3 25% 7 58.3% 12 100%

Table 4.2 shows how the crash type varies by location. Broadside crashes comprise the largest share of crashes at signalized and non-signalized intersections locations (32 percent and 24 percent, respectively).

Rear-end and Sideswipe crashes are the second- and third-most-common crash types (27 percent and 19 percent of the total) at signalized intersections.

Broadside crashes are the dominant category at non-signalized intersections (24 percent). Hit-object and

Sideswipe crashes are the second- and third-most-common crash types (23 and 21 percent) at non-signalized intersections. Rear-end crashes comprised a substantially-larger share of crashes at midblock locations (29 percent). Vehicle-pedestrian related crashes that occurred at midblock locations accounted for 6 out of the 11 total vehicle-pedestrian crashes.

CITY OF CALABASAS | LRSP PAGE 20

Table 4.2 Crash Types by Facility Type

Signalized

Intersections

Non-Signalized

Intersections Midblock Grand Total

Crash

Type Crashes % Crashes % Crashes % Crashes %

Broadside 89 32.4% 56 24.5% 76 25.9% 221 27.7%

Head-On 23 8.4% 19 8.3% 8 2.7% 50 6.2%

Hit Object 22 8.0% 53 23.1% 38 13.0% 113 14.1%

Unknown 12 4.4% 4 1.7% 10 3.4% 26 3.2%

Other 1 0.4% 7 3.1% 7 2.4% 15 1.8%

Overturned 0 0.0% 3 1.3% 4 1.4% 7 0.87%

Rear End 74 26.9% 35 15.3% 85 29.0% 194 24.3%

Sideswipe 53 19.3% 48 21.0% 59 20.1% 160 20%

Vehicle/Ped 1 0.4% 4 1.7% 6 2.0% 11 1.38%

Total 275 100% 229 100% 293 100% 797 100%

Table 4.3 shows the relationship between street lighting conditions and facility type. More than 90 percent of crashes occurred in the presence of lighting (i.e. either in daylight or night-time with street-lighting) at all three location types. Only 2 percent of all crashes took place in the dark with no street lighting, with this figure ranging from 0.7 percent at signalized intersections to 2.4 percent at midblock locations.

Table 4.3 Street Lighting by Facility Type

Crash Type

Signalized

Intersections

Non-Signalized

Intersections Midblock Grand Total

Crashes % Crashes % Crashes % Crashes % Daylight 206 74.9% 153 66.8% 205 70.0% 564 70.8%

Dark - Street Lights 51 18.5% 62 27.1% 70 23.9% 183 23.0%

Dark - No Street Lights 2 0.7% 3 1.3% 7 2.4% 12 1.5%

Unknown 2 0.7% 3 1.3% 1 0.3% 6 0.8%

Dusk - Dawn 13 4.7% 8 3.5% 10 3.4% 31 3.9%

Dark - Street Lights

Not Functioning

1 0.4% 0 0.0% 0 0.0% 1 0.1%

Table 4.4 tabulates the PCFs by facility type. The three largest PCF categories included automobile right-of-way, improper turning, and unsafe speed at all three location types. The ranking order varied by location types:

• At signalized intersections, the leading PCFs were automobile right-of-way, unsafe speed and improper turning (comprising roughly 26 percent, 15 percent, and 14 percent of the total).

CITY OF CALABASAS | LRSP PAGE 21

• At non-signalized intersections, unsafe speed, improper turning, and automobile right-of-way violations were the dominant PCFs (comprising 27 percent, 18 percent, and 14 percent of the total).

• At midblock locations, the most frequent PCFs were unsafe speed, automobile right-of-way, and improper turning violations were the dominant PCFs (comprising 20 percent, 18 percent, and 17 percent of the total).

Table 4.4 Primary Crash Factor by Facility Type

Crash Type

Signalized

Intersections

Non-Signalized

Intersections Midblock Grand Total

Crashes % Crashes % Crashes % Crashes %

Brakes 1 0.4% 1 0.4% 0 0.0% 1 0.1%

Impeding Traffic 1 0.4% 0 0.0% 0 0.0% 1 0.1%

Other Improper

Driving 0 0.0% 1 0.4% 0 0.0% 1 0.1%

Hazardous Parking 0 0.0% 0 0.0% 2 0.7% 2 0.3%

Other Equipment 1 0.4% 0 0.0% 2 0.7% 3 0.4%

Pedestrian Violation 0 0.0% 2 0.9% 1 0.3% 3 0.4%

Other Hazardous

Violation 0 0.0% 3 1.3% 1 0.3% 4 0.5%

Pedestrian Right of

Way 1 0.4% 2 0.9% 2 0.7% 5 0.6%

Other Than Driver/Ped 0 0.0% 3 1.3% 6 2.0% 9 1.1%

Improper Passing 3 1.1% 3 1.3% 4 1.4% 10 1.3%

Wrong Side of Road 0 0.0% 6 2.6% 10 3.4% 16 2.0%

Unknown 15 5.5% 12 5.2% 15 5.1% 46 4.6%

Unsafe Starting or

Backing 13 4.7% 9 3.9% 15 5.1% 37 5.4%

Unsafe Lane Change 22 8.0% 11 4.8% 7 2.4% 40 5.0%

DUI 10 3.6% 15 6.6% 19 6.5% 44 5.5%

Traffic Signals and

Signs 33 12.0% 15 6.6% 7 2.4% 55 6.9%

Following Too Closely 22 8.0% 10 4.4% 40 13.7% 72 9.0%

Improper Turning 40 14.5% 41 17.9% 50 17.1% 131 16.4%

Automobile ROW 72 26.2% 32 14.0% 53 18.1% 157 19.7%

Unsafe Speed 41 14.9% 63 27.5% 59 20.1% 163 20.5%

As mentioned earlier, broadside crashes were the most-frequently-occurring crash type in Calabasas.

Automobile right-of-way was the most-common PCF in the City and the leading cause of broadside crashes. Improper turning was the third-most common PCF and second-largest PCF associated with broadside crashes. Approximately 50 percent of broadside crashes from 2015 to 20120 resulted from automobile right-of-way, while roughly 17 percent of broadside crashes during this period were caused by improper turning.

CITY OF CALABASAS | LRSP PAGE 22

Table 4.5 breaks down Broadside crashes caused by automobile right-of-way by facility type. Table 4.6 breaks down broadside crashes caused by improper turning by facility type. The broadside crashes caused by automobile right-of-way ranged from 37 percent at non-signalized intersections to 57 percent at signalized intersections. Likewise, the percentage of broadside crashes caused by improper turning ranged from 21 at percent non-signalized intersections to 9 percent at signalized intersections.

The greater incidence of broadside crashes induced by automobile right-of-way- and improper turning at signalized intersections suggests that the poor singing and striping, and low signalized intersection density on the city’s arterial roads lead many motorists to decelerate improper turning or mislead right-of-way as the approach to signalized intersections.

Table 4.5 Automobile Right-of-Way due to Broadside Crashes by Facility Type

Facility Type Total Broadside

Crashes

Broadside

Crashes due to

Automobile ROW

Percentage of

Broadside

Crashes due to

Automobile ROW

Non-signalized intersections 56 21 37.5%

Midblock locations 76 38 50%

Signalized intersections 89 51 57.3%

Total 221 110 49.7%

Table 4.6 Improper Turning due to Broadside Crashes by Facility Type

Total broadside

Crashes

Broadside

Crashes due to

Improper Turning

Percentage of

Broadside Crashes due to Improper

Turning

Non-signalized intersections 56 12 21.4%

Midblock locations 76 18 23.6%

Signalized intersections 89 8 9.0%

Total 221 38 17.2%

In Calabasas, broadside crashes are the most common crash type at non-signalized intersections. Crashes caused by automobile right-of-way, the second most commonly occurring PCF, are primarily associated with sideswipe and head-on crashes. Table 4.7 shows the percentage of crashes with an automobile right-of-way PCF classified as head-on and sideswipe crashes. Approximately 10 percent (16 crashes) of automobile right-of-way crashes were head-on crashes, and 11 percent (18 crashes) were sideswipe crashes.

CITY OF CALABASAS | LRSP PAGE 23

Most automobile right-of-way crashes associated with head-on occurred at signalized intersections. Also, most automobile right-of-way crashes are associated with sideswipes at mid-block locations. Likewise, signalized intersections had the most head-on crashes due to automobile right-of-way. However, sideswipe crashes comprised the highest percentage of automobile right-of-way crashes at non-signalized intersections.

Table 4.7 Automobile Right-of-Way with Head-On and Sideswipe Crashes by Facility Type

Automobile

Right-of-Way

Total Crashes

Head-On Crashes Sideswipe

Crashes

Crash % Crash % Non-

Signalized

Intersection

32 3 9.3% 5 15.6%

Midblock

Locations 53 4 7.5% 7 13.2%

Signalized

Intersection 72 9 12.5% 6 8.3%

Total 157 16 10.2% 18 11.4%

4.3 CALABASAS VS. LOS ANGELES COUNTY

Six years of TIMS data were used to compare the characteristics of injury and fatality crashes for the City of Calabasas with those for all of Los Angeles County. As shown in Table 4.8, from 2015 to 2020, Calabasas experienced 313 non-PDO crashes (excluding freeways). As the City had an estimated 23,241 residents in

2020, this amounted to 2,244 crashes per one million residents per year. A total of 305,653 crashes occurred in Los Angeles County during the same period, making for a significantly higher rate of 6,049 crashes per million residents per year. Thus, Calabasas had a lower normalized crash rate than the county average.

Relative to its population, the following statistics compare the results between Calabasas and LA County.

• Fatal and severe (KSI) Crashes: 1.2 percent vs. 6.1 percent,

• Pedestrian Crashes: 1.4 percent vs. 9.1 percent, and

• Bicycle Crashes: 1.5 percent vs. 6.1 percent.

CITY OF CALABASAS | LRSP PAGE 24

Table 4.8 Total Crash Comparison, Calabasas vs. Los Angeles County

Total Crashes City of

Calabasas

Los Angeles

County

Population (2020 estimates) 23,241 10,039,107

Total Crashes 313 305,653

Crash/1,000,000/Year 2,244 6,049

Fatal and Severe Crashes (KSI) 9 18,540

KSI % 1.2% 6.1%

Pedestrian Crashes 11 27,835

Pedestrian % 1.4% 9.1%

Bicycle Crashes 12 18,573

Bicycle % 1.5% 6.1%

Table 4.9 focuses on KSI crashes in Calabasas and Los Angeles County between 2015 and 2020 TIMS data.

Calabasas had a substantially lower KSI crash per million residents per year than Los Angeles County (64

vs. 367). Among KSI crashes, Calabasas had 100 percentages of severe injury (100 percent versus 81.7 percent) crashes. Bicycle crashes comprised a smaller proportion of KSI crashes in Calabasas (3 percent versus 7.6 percent for the County), while pedestrian crashes comprised a substantially higher proportion

(33.3 percent versus 27.1 percent for the County).

Table 4.9 KSI Crash Comparison, Calabasas vs. Los Angeles County

KSI Crashes City of

Calabasas

Los Angeles

County

Population (2020 estimates) 23,241 10,039,107

Fatal and Severe Crashes (KSI) 9 18,540

KSI Crash/1,000,000/Year 64 367

Fatal 0 3,386

Fatal % 0% 18.3%

Severe Injury 9 15154

Severe Injury % 100% 81.7%

Pedestrian 11 5,020

Pedestrian % 33.3% 27.1%

Bicyclist 12 1401

Bicyclist % 3.0% 7.6%

Source: SWITRS/TIMS, 2015-2020

Table 4.10 breaks down the 2015-2020 TIMS data by crash type for Calabasas and Los Angeles County. In

Calabasas broadside accounted for the highest proportion of crashes, followed by rear-end and sideswipe.

Sideswipe crashes were over-represented in Calabasas relative to the County (36 percent versus 32 percent of crashes in the respective geographies). In comparison, broadside and hit object crashes were slightly under-represented (28 percent versus 29 percent in the County and 7 percent versus 7 percent in the

County). Head-on and rear-end crashes comprised a more significant proportion of crashes in Calabasas

(6 percent and 24 percent) than in Los Angeles County (7 percent and 32 percent).

CITY OF CALABASAS | LRSP PAGE 25

Table 4.10 Crash Type Comparison, Calabasas vs. Los Angeles County

Type of Crash

City of

Calabasas

Los Angeles

County

Broadside 27.7% 29.53%

Head-On 6.3% 7.19%

Hit Object 14.2% 6.67%

Other 1.9% 2.24%

Overturned 0.9% 1.64%

Rear End 24.3% 31.7%

Sideswipe 20.1% 11.89%

Vehicle/Pedestrian 1.0% 7.82%

Unknown 3.3% 1.32%

Total % 100.0% 100.0%

Table 4.11 compares PCFs for the City and the County based on the 2015-2020 TIMS data. As with crash type, the ranking of PCF categories in Calabasas aligns with Los Angeles County. Unsafe speed, automobile right-of-way, and improper turning comprise the top three PCF categories in both geographies. Compared with the County, Calabasas had a substantially higher percentage of crashes (16 percent in Calabasas versus

11 percent in the County) caused by improper turning. In contrast, the county has a slightly higher share of automobile right-of-way and unsafe speed (19 percent and 20 percent in Calabasas and 20 percent and

29 percent in Los Angeles County).

CITY OF CALABASAS | LRSP PAGE 26

Table 4.11 PCF Comparison, Calabasas vs. Los Angeles County

Primary Crash Factor City of

Calabasas

Los Angeles

County Automobile Right of Way 19.70% 20.46%

Brakes 0.13% 0.02%

Driving or Bicycling Under the

Influence of Alcohol or Drug 5.52% 5.30%

Following Too Closely 9.03% 3.12%

Hazardous Parking 0.25% 0.06%

Impeding Traffic 0.13% 0.06%

Improper Passing 1.25% 0.68%

Improper Turning 16.44% 11.07%

Lights - 0.01%

Other Equipment 0.38% 0.03%

Other Hazardous Violation 0.50% 0.82%

Other Improper Driving 0.13% 0.46%

Other Than Driver (or Pedestrian) 1.13% 1.08%

Pedestrian Right of Way 0.63% 3.62%

Pedestrian Violation 0.38% 2.86%

Traffic Signals and Signs 6.90% 8.90%

Unknown 4.64% 2.64%

Unsafe Lane Change 5.02% 5.07%

Unsafe Speed 20.45% 29.03%

Unsafe Starting or Backing 4.64% 1.80%

Wrong Side of Road 2.01% 2.37%

Total % 100.0% 100.0%

4.4 CALABASAS VS. CITIES OF SIMILAR SIZES

In the State of California’s OTS Crash Ranking system, Calabasas falls under Group E. This group consists of 103 cities in the state of California with a population between 10,001 and 25,000. Table 4.12 shows the

City’s 2019 crash ranking among the cities in Group E (1 being the highest or worst and 103 being the lowest or best). Overall, the City’s traffic safety performance raises concern in three areas:

● 38 DUI arrests were issued in the City in 2019. This ranked 39th compared with the 103 cities

● The City of Calabasas ranked 7th out of 103 in injury-related motorcycle crashes (9 total), compared with the 103 cities

● Total Fatal and Injury ranked in the higher 1/3 of the 103 comparable cities.

CITY OF CALABASAS | LRSP PAGE 27

Table 4.12 2019 OTS Ranking, Calabasas

Type of Crash Victims Injured and/or Killed

OTS

Ranking

Total Fatal and Injury 78 34/103

Alcohol Involved 7 44/103

Had Been Drinking Driver < 21 1 16/103

Had Been Drinking Driver 21 – 34 1 45/103

Motorcycles 9 7/103

Pedestrians 1 92/103

Pedestrians < 15 0 100/103

Pedestrians 65+ 0 102/103

Bicyclists 0 100/103

Bicyclists < 15 0 101/103

Composite 22 49/103

Type of Crash Fatal and Injury

Crashes

OTS

Ranking

Speed Related 8 49/103

Nighttime (9:00pm-2:59am) 3 69/103

Hit and Run 2 68/103

Type of Arrests Arrests

OTS

Ranking

DUI Arrests 38 39/103 Source: OTS, 2019

CITY OF CALABASAS | LRSP PAGE 28

5.0 TRANSPORTATION SAFETY EMPHASIS AREAS

Transportation safety emphasis areas provide a strategic framework for developing and implementing the

Local Roadway Safety Plan (LRSP). The emphasis areas show the City of Calabasas where to focus when developing projects and programs based on the LRSP. The implementation of the emphasis areas should directly relate to the goals, policies, and strategies of the LRSP. Based on the crash data analysis conducted for the City of Calabasas, the following transportation safety emphasis areas:

● Automobile right-of-way, Head On, and Sideswipe Crashes

● Pedestrians and Bicyclists

● Signalized Intersections

● Speeding and Broadside Crashes

● Young Drivers

5.1 AUTOMOBILE RIGHT-OF-WAY, HEAD-ON, AND SIDESWIPE CRASHES

Improper turning usually results from careless or aggressive driving. Motorists that speed through or abruptly turn at intersections are more likely to collide with other vehicles, pedestrians, or bicyclists. The first part of this memo showed that automobile right-of-way was the second-largest primary crash factor

(PCF) in Calabasas between 2015 and 2020 and was over-represented as a PCF among KSI crashes.

Calabasas has a lower proportion of crashes with automobile right of way PCFs than Los Angeles County

(according to TIMS), indicating that the City has conditions contributing to this behavior.

Sideswipe and head on crashes were the two types of crashes, most often associated with automobile right-of-way. Sideswipe was the third-most-frequent category in Calabasas between 2015 and 2020 (per

SWITRS). Hit object crashes were the fourth-most-common crash type and the second-most-common crash type among KSI crashes in Calabasas.

Given their overall frequency and association with severe crashes, the automobile right-of-way, sideswipe, and head on crashes are identified as an emphasis area. Automobile right-of-way, sideswipe, and head on crashes occurred more frequently at non-signalized intersections and mid-block locations than at signalized intersections.

5.2 PEDESTRIANS AND BICYCLISTS

Pedestrians and bicyclists are among the most vulnerable roadway users. Active transportation roadway users in suburban communities are often too young or too old to drive or lack the means to purchase a car. Wide arterial roadways, high-speed roadways, and limited crossing facilities may be uncomfortable for walking and biking and are not as safe as separated facilities or improved crossings. Based on observations in the field, the City has a relatively low volume of bicyclist using the roadways for travel. The lower volume may indicate the lack of safer bicycle and pedestrian facilities and preference for motor driven alternatives.

TRANSPORTATION SAFETY EMPHASIS AREAS

CITY OF CALABASAS | LRSP PAGE 29

Pedestrians:

While vehicle-pedestrian crashes comprised only slightly more than one percent of total crashes in

Calabasas (per the 2015-2020 SWITRS data), they accounted for nearly 11 percent of fatal and severe injury crashes (see Figure 4.3). In the 2019 OTS Rankings, Calabasas ranked 102 out of 103 among peer cities for the number of killed or injured pedestrians over 65 years of age, indicating that elderly pedestrians are not facing as many safety challenges as other comparable cities in the State of California.