CHINO LRSP 2023

City of Chino

Local Roadway Safety Plan (LRSP)

March 2023

FINAL - Revised

Prepared By:

Executive Summary The City of Chino has created a Local Roadway Safety Plan (LRSP), which identifies a framework to identify, analyze, and develop traffic safety enhancements on the City’s roadway network. The LRSP was developed in response to local issues and needs. Through the analysis, this report has identified emphasis areas to inform and further guide safety evaluation and planning for the City’s transportation network. The LRSP also analyzes collision data on an aggregate basis as well as at specific locations to identify high-crash locations, high-risk locations, and citywide trends and patterns. The analysis of collision history on the City’s transportation network allows for opportunities to: 1) identify factors in the transportation network that inhibit safety for all roadway users, 2) improve safety at specific high-collision locations, and 3) develop safety measures using the 5E’s of transportation safety: Engineering, Enforcement, Education, Emergency Services, and Emerging Technologies, to encourage safer driver behavior and better severity outcomes.

Chino has been taking steps to enhance traffic safety throughout the City but can take additional steps in improving roadway safety citywide. This is demonstrated in its California Office of Traffic Safety (OTS) rankings which identify the City as belonging to the 30th percentile for safety compared to peer cities in most categories, with the City performing better than 30% of its peer cities. The City is continuing these safety efforts through this plan by identifying areas of emphasis and opportunities for system improvement that can be implemented to enhance safety. This LRSP analyzes the most recent range of collision data (January 1, 2016 to December 31, 2020) and recent roadway improvements to assess historic trends, patterns, and areas of concern.

During the LRSP development process, the City has drafted a vision for traffic safety and outlined the goals that will help mark plan success. The vision is to enhance the transportation network to achieve zero traffic fatalities and serious injury related collisions. The goals were identified as:

Identify areas with a high risk for collisions.

Illustrate the value of a comprehensive safety program and the systemic process.

Plan future safety improvements for near-, mid- and long-term implementation.

Define safety projects for Highway Safety Improvement Program (HSIP) and other program funding consideration.

Chino’s collision history was analyzed to identify locations with elevated risk of collisions either through their collision histories or their similarities to other locations that have more active collision patterns. Using a network screening process, locations within the City that will most likely benefit from safety enhancements were identified. Using historic collision data, collision risk factors for the entire network were derived. The outcomes informed the identification and prioritization of engineering and non-infrastructure safety measures that address certain roadway characteristics and related behaviors that contribute to motor vehicle collisions with active transportation users. The figure below shows the results of collision analysis, including the number of crashes that occurred at each intersection and along each roadway segment in the City.

Number of Collisions at Intersections and along Roadways in Chino (2016-2020)

Emphasis areas were developed by revisiting the vision and goals developed at the onset of the planning process and comparing them with the trends and patterns identified in the crash analysis. Where these areas aligned, or major challenges were observed, the following emphasis areas were developed:

1. Commercial Vehicles

2. Aggressive Driving

3. Vulnerable Road Users (Pedestrians and Bicyclists)

4. Intersection Improvements

5. Impaired Driving

The LRSP identified countermeasures for both infrastructure and non- infrastructure improvements. The report then applies Crash Modification Factors (CMFs), which are used to estimate the safety effects of safety improvements to compare and prioritize the improvements. This provides a planning level cost/benefit estimate that the City can use to prioritize improvements.

Site-specific opportunities for improvement were identified for the following 16 case study locations. The case study locations were chosen to be representative of the corridor and intersection designs throughout the City.

1. Segment: Riverside Drive (4th St to Telephone Ave)

2. Segment: Ramona Avenue (Walnut St to Riverside Dr)

3. Segment: Philadelphia Street (Telephone Ave to Central Ave)

4. Segment: Central Ave (Francis Ave to Philadelphia St)

5. Segment: Pipeline Ave (Edison Ave to Eucalyptus Ave)

6. Segment: Roswell Avenue (Schaefer Ave to Grand Ave)

7. Segment: Mountain Avenue (EB SR-60 Ramp to Walnut Ave)

8. Signalized Intersection: Central Ave & Riverside Dr

9. Signalized Intersection: Pipeline Ave & Edison Ave

10. Unsignalized Intersection: Central Ave & Jefferson Ave

11. Unsignalized Intersection: East End Ave & Schaefer Ave

The report also identifies opportunities that can be implemented systemically throughout the City. These opportunities were assembled into the “countermeasure toolbox” shown below and include both engineering-based and non-engineering countermeasures.

Additionally, this information can be used to help the City apply for grants and other funding opportunities to implement these safety improvements.

Citywide Countermeasure Toolbox (Engineering Opportunities)

LRSM/C

MF ID Potential Countermeasures

Crash Reduction

Factor

Per Unit Cost Unit

NS03 Install signals 30% $270,000 per intersection

NS05 Convert intersection to roundabout (from stop or yield control on minor road) 35% $750,000 per intersection

NS07 Upgrade intersection pavement markings (NS.I.) 25% $22,000 per intersection

NS09 Install flashing beacons as advance warning (NS.I.) 30% $20,000 per beacon NS14 Install raised median on approaches (NS.I.) 25% $30,000 per approach

NS15 Create directional median openings to allow (and restrict) left-turns and u-turns (NS.I.) 50% $45,000 per structure

NS17 Install right-turn lane (NS.I.) 20% $55,000 per location R01 Add segment lighting 35% $50,000 per mile R04 Install Guardrail 25% $50,000 per location R26 Install dynamic/variable speed warning signs 30% $16,000 per sign R28 Install edge-lines and centerlines 15% $60,000 per linear mile

R32PB Install bike lanes 35% $45,000 per mile R33PB Install Separated Bike Lanes 45% $250,000 per mile

S02 Improve signal hardware; lenses, back plate with retroreflective borders, mounting, size, and number 15% $24,000 per intersection

S03 Improve signal timing (coordination, phases, red, yellow, or operation) 15% $8,000 per intersection

S04 Provide Advanced Dilemma Zone Detection for high-speed approaches 40% $34,000 per intersection

S09 Install raised pavement markers and striping (Through intersection) 10% $7,667 per intersection

S18PB Install pedestrian crossing (S.I.) 25% $50,000 per intersection

S18PB Install pedestrian crossing/crosswalk (S.I.) 25% $50,000 per intersection

S21PB Modify signal phasing to implement a Leading Pedestrian Interval (LPI) 60% $7,667 per intersection

Non-Engineering Safety Strategy Countermeasures:

The identified non-engineering countermeasures below were derived from the collision analysis and build on the actions the City is undertaking. These relate to the additional Es of Traffic Safety outside of Engineering. This includes Enforcement, Education, Emergency Services and Emerging Technologies.

Citywide Countermeasure Toolbox (Non-Engineering Opportunities)

PROPOSED

COUNTERMEASURE

POTENTIAL PARTNERS

EXAMPLES OF

COUNTERMEASURE

ENFORCEMENT

Police traffic services to enhance enforcement and compliance with impaired driving and other traffic laws

Local law enforcement

Selective enforcement which includes DUI check points and monitor hot spot locations. Grant funding OTS California Office of Traffic Safety

Safe routes to school for a safe and accessible commute to walk/bike to school for students and parents.

SCAG, local law enforcement, local school districts

Active Transportation Programs (ATP), educational programs, SRTS Action Plans

EDUCATION

Educational programs for all ages to enhance their skills on traffic regulations and behavior impacts

Local school districts, Local law enforcement, CHP, Office of Traffic Safety

Interactive programs at local schools and involvement from parents, teachers, and community to mentor traffic safety, OTS California Office of Traffic Safety.

Safety campaigns to raise awareness and eliminate traffic fatalities and injuries (aggressive driving, distracted driving, impaired driving, ped/bike safety)

Local law enforcement, SCAG

Series of campaigns on multiple platforms with efforts to improve behaviors and safety on the roads, OTS California Office of Traffic Safety.

Safety programs targeted to reduce bike and pedestrians’ collisions

SCAG, local school districts, local law enforcement

SCAG Kit of Parts, testing temporary safety improvements and receive feedback from participants

EMERGENCY SERVICES

Traffic Management Plans/Temporary Traffic Control to move motorist through work zone effectively and safety.

Local law enforcement, Caltrans, and fire department

Timely project-related information through multiple platforms and scheduled passages through roadway construction zones, Caltrans

Involvement of emergency services as actives roles in projects and interdepartmental communication among city and emergency services.

Local law enforcement, public health agencies, and fire departments

Incorporate emergency services agencies as stakeholders in projects.

PROPOSED

COUNTERMEASURE

POTENTIAL PARTNERS

EXAMPLES OF

COUNTERMEASURE

EMERGING TECHNOLOGY

Emergence of new technology to ensure safety, and accessibility

City Public Works, City Engineering Department, Caltrans

Using data as benefit for digital maps, safety analysis, signals, and micro-mobility

Implementing new and best possible countermeasures for safety improvement for motorist, bicyclist, and pedestrians

City Public Works, City Engineering Department, Caltrans

Utilization of advanced technology to improve safety

An evaluation and implementation plan were created that identifies actionable items that will help the City achieve the goals and vision set out in this report. This section laid out next steps for the City to continue to capitalize on the analysis and information provided in this report.

Table of Contents

INTRODUCTION 1

VISION AND GOALS 2

PROCESS 3

3.1 Guiding Manuals 3

3.2 Analysis Techniques 5

SAFETY PARTNERS 9

4.1 Stakeholder Meeting #1 9

4.2 Stakeholder Meeting #2 9

4.3 Public Meeting Regarding East End Ave/Schaefer Ave Intersection 9

EXISTING EFFORTS 9

DATA SUMMARY 10

6.1 Roadway Network 10

6.2 Intersections 10

6.3 Count Data 10

6.4 Collision Data 10

CRASH SAFETY TRENDS 14

7.1 All Crashes 14

7.2 Fatalities 14

7.3 Injury Levels 15

7.4 Cause of Collisions 16

7.5 Vulnerable Users 17

7.6 Significant Trends for Passenger Vehicles 19

7.7 Initial Findings 19

7.8 Statewide Comparison 25

EMPHASIS AREAS 25

OPPORTUNITIES 28

9.1 Infrastructure Improvements 28

9.2 Non-Infrastructure Improvements 29

9.3 General Citywide Countermeasure Toolbox 32

EVALUATION & IMPLEMENTATION 37

10.1 Evaluation 37

10.2 Implementation 37

10.3 Funding 38

10.4 Next Steps 40

Figure 1: Critical Crash Rate Formula Figure 2 – Probability of Specific Crash Types Exceeding Threshold Proportion Figure 3: Functional Classification (2016-2020) Figure 4: Fatal and Severe Injury Collisions (2016-2020) Figure 5: Density of all Crashes at Intersections and Segments (2016-2020) Figure 6: Collision Type by Year (2016-2020) Figure 7: Collisions by Injury Levels (2016-2020) Figure 8: Cause of Crashes (2016-2020) Figure 9: : Pedestrian & Bicycle Collisions (2016-2020)

Table of Tables Table 1: Fatal Cras hes Categorized by Modes Involved (2016-2020) Table 2: Analysis Rankings – Intersections Table 3: Analysis Rankings - Segments Table 4: Comparison of Statewide and Chino Fatal & Severe Injury Crashes Table 5: Summary of Programs, Policies, and Practices for the City of Chino Table 6: Citywide Safety Project Opportunities (Countermeasure Toolbox) Table 7: Non-Engineering Safety Strategy Countermeasures

Introduction Chino is a community in San Bernardino County known for its diversity of attractions and growing population. Chino’s top employment sectors are contributed to construction, warehousing, manufacturing, transportation, and retail. The current population is around 103,416 residents with a median age of 37 years old. With a mixture of recreational, educational, and cultural sites the City has numerous traffic safety needs.

This Local Roadway Safety Plan (LRSP) identifies emphasis areas to focus and guide further safety enhancement to the City’s transportation network. The LRSP analyzes crash data on an aggregate basis as well as at specific locations to identify high-crash locations, high-risk locations, and citywide trends and patterns. The analysis of crash history throughout the City’s transportation network provided the opportunity to: 1) identify factors in the transportation network that inhibit safety for all roadway users, 2) improve safety at specific high-crash locations, and 3) develop safety measures using the five E’s of safety: Engineering, Enforcement, Education, Emergency Services, and Emerging Technologies to encourage safer driver behavior and reduced collision severities.

The process and analysis performed for the City’s LRSP is described in this document. The plan includes a vision and associated goals for safety, crash history analysis, and specific emphasis areas that represent the most challenge for safety in the City. The plan provides a foundation for decision making and prioritization for safety countermeasures and projects that enhance safety for all modes.

Chino has been successful at taking steps to enhance safety for all modes throughout the City.

This is supported by their California Office of Traffic Safety rankings identifying it amongst the top 30% tier for safety as compared to peer cities in most categories. The City is continuing these safety efforts through this plan by identifying areas of emphasis and opportunities for system improvement that can be implemented to enhance safety. This LRSP analyzes the most recent 5-year period of available crash data (January 1, 2016 – December 31, 2020) and roadway improvements to assess historic trends, patterns, and areas of elevated collision activity.

The intent of the LRSP is to:

Create a greater awareness of road safety and risks

Reduce the number of fatal and severe-injury crashes

Develop lasting partnerships

Support for grant/funding applications, and

Help prioritize investments in traffic safety.

Vision and Goals The Chino LRSP evaluates the transportation network as well as non-infrastructure programs and policies within the City. Mitigation measures are evaluated using criteria to analyze the safety of road users (drivers, bicyclists, and pedestrians), the interaction of modes, influences on the roadway network from adjacent municipalities, and the potential benefits of safety countermeasures. This effort is intended to use historical data to identify trends and develop a toolbox of countermeasures applicable to conditions in the City that can be used for proactive identification and implementation of opportunities, without relying solely on a reaction and response to crashes as they occur.

LRSPs have been effective across the country as part of the effort to reduce fatal and severe-injury crashes because they provide a locally developed and customized roadmap to directly address the most common safety challenges in the given jurisdiction. Consistent with these findings, the following Vision, Goals, and Objectives have been established for this project.

VISION:

To enhance the transportation network to achieve zero traffic fatalities and serious injury related crashes.

Goal #1: Identify areas with a high risk for collision.

Objectives:

Identify intersections and segments that would most benefit from mitigation.

Identify areas of interest with respect to safety concerns for vulnerable users (pedestrians and bicyclists).

Goal #2: Illustrate the value of a comprehensive safety program and the systemic process.

Objectives:

Demonstrate the systemic process’ ability to identify locations with higher risk for collisions based on present characteristics closely associated with severe collisions.

Demonstrate, through the systemic process, the gaps and data collection activities that can be improved upon.

Goal #3: Plan future safety improvements for near-, mid- and long-term.

Objectives:

Identify safety countermeasures for specific locations (case studies).

Identify safety countermeasures that can be applied citywide.

Goal #4: Define safety projects for future HSIP and other program funding consideration.

Objectives:

Create the outline for a prioritization process that can be used in this and forth-coming cycles to apply for funding.

Use the systemic process to create Project Case Studies.

Use Case Studies to apply for HSIP funding consideration.

Demonstrate the correlation between the proposed safety countermeasures with the

Vision Zero Initiative and the California State Highway Safety Plan.

Process Providing safe, sustainable, and efficient mobility choices for residents and visitors is a primary goal for the City and its safety partners. The City will continue its collaboration with safety partners to identify and discuss safety issues within the community through the development of the LRSP and its implementation.

Guidance on the LRSP process is provided at both the national (FHWA) and state (Caltrans) level.

FHWA encourages:

The establishment of a working group (Stakeholders) to participate in developing an

LRSP.

Review crash, traffic, and roadway data to identify areas of concern.

Establish goals, priorities, and countermeasures to identify opportunities for improvements at spot locations, systemically, and comprehensively.

Caltrans guidance includes:

Establish leadership Analyze the safety data Determine emphasis areas Identify strategies Prioritize and incorporate strategies Evaluate and update the LRSP

This LRSP documents the results of data and information obtained, including the preliminary vision and goals for the LRSP, existing safety efforts, initial crash analysis, and resulting emphasis areas. The identification of opportunities to enhance safety presented in this LRSP are connected to the five E's of traffic safety defined by the California Strategic Highway Safety Plan (SHSP): Engineering, Enforcement, Education, Emergency Response, and Emerging Technologies throughout its process.

3.1 Guiding Manuals

The following section describes the analysis process undertaken to evaluate safety within Chino at a systemic level. Using a network screening process, locations within the City that will most likely benefit from safety enhancements will be identified. Using historic crash data, crash risk factors for the entire network were documented. The outcomes will inform the identification and prioritization of engineering and non-infrastructure safety measures that address certain roadway characteristics and related behaviors that contribute to motor vehicle crashes with active transportation users.

This process uses the latest National and State best practices for statistical roadway analysis described as follows.

3.1.1 Local Roads Safety Manual

The Local Roadway Safety Manual: A Manual for California’s Local Road Owners (Version 1.5, April 2020) purpose is to encourage local agencies to pursue a proactive approach to identifying and analyzing safety issues, while preparing to compete for project funding opportunities. A proactive approach is defined as analyzing the safety of the entire roadway network through either a one-time, network wide analysis, or by routine analyses of the roadway network.1

According to the Local Roadway Safety Manual (LRSM), “The California Department of Transportation (Caltrans) – Division of Local Assistance is responsible for administering California’s federal safety funding intended for local safety improvements.”

To provide the most benefit and to be competitive for funding, the analysis leading to countermeasure selection should focus on both intersections and roadway segments and be considerate of roadway characteristics and traffic volumes. The result should be a list of locations that are most likely to benefit from cost-effective countermeasures, preferably prioritized by benefit/cost ratio. The manual suggests using a mixture of quantitative and qualitative measures to identify and rank locations that considers both crash frequency and crash rates. These findings should then be screened for patterns such as crash types and severity to aid in the determination of issues causing higher numbers of crashes and the potential countermeasures that could be most effective. Qualitative analysis should include field visits and a review of existing roadway characteristics and devices. The specific roadway context can then be used to assess what conditions may increase safety risk at the site and systematic level.

Countermeasure selection should be supported using Crash Modification Factors (CMFs).

These factors are the peer reviewed product of before and after research that quantifies the expected rate of crash reduction that can be expected from a given countermeasure. If more than one countermeasure is under consideration, the LRSM provides guidance on how to apply CMFs appropriately.

3.1.2 Highway Safety Manual

“The AASHTO Highway Safety Manual (HSM), published in 2010, presents a variety of methods for quantitatively estimating crash frequency or severity at a variety of locations.”2 This four-part manual is divided into Parts: A) Introduction, Human Factors, and Fundamentals, B) Roadway Safety Management Process, C) Predictive Method, D) Crash Modification Factors.

Chapter 4 of Part B of the HSM discusses the Network Screening process. The Network Screening Process is a tool for an agency to analyze their entire network and identify/rank locations that (based on the implementation of a countermeasure) are most likely to realize a reduction in the frequency of crashes.

The HSM identifies five steps in this process:3

1. Establish Focus: Identify the purpose or intended outcome of the network screening analysis. This decision will influence data needs, the selection of performance measures and the screening method that can be applied.

1 Local Roadway Safety Manual (Version 1.5) 2020. Page 5.

2 AASHTO, Highway Safety Manual, 2010, Washington D.C., http://www.highwaysafetymanual.org/Pages/About.aspx 3 AASHTO. Highway Safety Manual. 2010. Washington, DC. Page 4-2.

2. Identify Network and Establish Reference Populations: Specify the types of sites or facilities being screened (i.e., segments, intersections, geometrics) and identify groupings of similar sites or facilities.

3. Select Performance Measures: There are a variety of performance measures available to evaluate the potential to reduce crash frequency at a site. In this step, the performance measure is selected as a function of the screening focus and the data and analytical tools available.

4. Select Screening Method: There are three principle screening methods (ranking, sliding window, peak searching). Each method has advantages and disadvantages; the most appropriate method for a given situation should be selected.

5. Screen and Evaluate Results: The final step in the process is to conduct the screening and analysis and evaluate the results.

The HSM provides several statistical methods for screening roadway networks to identify high risk locations based on overall crash histories. In addition to identifying the total number of crashes, this study uses a method referred to as Critical Crash Rate to analyze the data.

3.2 Analysis Techniques

3.2.1 Crash and Network Screening Analysis

Intersections and roadways were analyzed using four crash metrics:

Number of Crashes Critical Crash Rate (HSM Ch. 4) Probability of Specific Crash Types Exceeding Threshold Proportion (HSM Ch. 4) Equivalent Property Damage Only (HSM Ch. 4)

The initial steps of the crash analysis established sub-populations of roadway segments and intersections that have similar characteristics. For this study, intersections were grouped by their control type (Signalized, Unsignalized, Roundabout) and segments by their roadway category (Arterial, Collector, Minor Collector, Local). Individual crash rates were calculated for each sub-population. The population level crash rates were then used to assess whether a specific location has more or fewer crashes than expected. These sub-populations were also used to determine typical crash patterns to help identify locations where unusual numbers of specific crash types are seen.

The network screening process ranks intersections and roadway segments by the number of crashes that occurred at each one over the analysis period, and then identifies areas that had more of a given type of crash than would be expected for that type of location. These crash type factors were 1) crash injury (fatal, serious injury, other visible injury, complaint of pain, property damage only), 2) crash type (broadside, rear-end, sideswipe, head-on, hit object, overturned, bicycle, pedestrian, other), 3) environmental factors (lighting, wet roads), and 4) driver behavior (impaired, aggressive, distracted driving). With these additional factors, the locations were further analyzed.

From the results of the network screening analyses, a short-list of locations was chosen based on crash activity, crash severity, crash patterns, location type, and area of the City of Chino to provide the greatest variety of locations covering the widest range of safety opportunities for toolbox development. The intent is to populate the safety toolbox with mitigation measures that will be applicable to most of the crash activity in the City. Ten locations will ultimately be selected for mitigation analysis.

3.2.2 Critical Crash Rate (CCR) Analysis

Reviewing the number of collisions at a location is a good way to understand the cost to society incurred at the local level but does not give a complete indication of the level of risk for those who use that intersection or roadway segment daily. The Highway Safety Manual describes the Critical Crash Rate method, which provides a statistical review of locations to determine where risk is higher than that experienced by other similar locations. It is also the first step in analyzing for patterns that may suggest systemic issues that can be addressed at that location, and proactively at others to prevent new safety challenges from emerging.

The Critical Crash Rate compares the observed crash rate to the expected crash rate at a particular location based on facility type and volume using a locally calculated average crash rate for the specific type of intersection or roadway segment being analyzed. Based on traffic volumes and a weighted citywide crash rate for each facility type, a critical crash rate threshold is established at the 95% confidence level to determine locations with higher crash rates that are unlikely to be random. The threshold is calculated for each location individually based on its traffic volume and the crash profile of similar facilities. A negative CCR differential value indicates that there are less collisions than expected for a location while a positive CCR differential value means there are more collisions than expected.

Figure 1: Critical Crash Rate Formula

Source: Highway Safety Manual

Data Needs

CCR can be calculated using:

Daily entering volume for intersections, or vehicle miles traveled (VMT) for roadway segments, Intersection control types to separate them into like populations, Roadway functional classification to separate them into like populations, Collision records in GIS or tabular form including coordinates or linear measures.

Strengths

Reduces low volume exaggeration Considers variance Establishes comparison threshold

3.2.3 CCR Methodology

The Process of analyzing the CCR and comparing locations (separately by intersections and segments) is a multi-step process. The following is a high-level description of the process undertaken to develop the initial ranking of locations.

The first step in the process was to establish a citywide crash rate for each facility population.

These populations are broken into two categories with sub-categories:

Intersection:

o Signalized o Unsignalized

Roadway Classification:

o Major Arterial o Primary Arterial o Secondary Arterial o Collector Arterial o Local

The individual crash rate for each location was then calculated based on the associated traffic volume. This volume was either collected through data count resources or calculated based on the roadway classification. The next step was to establish a Significance Threshold. This Threshold was used to determine what level of exceedance (how much the crash rate exceeded the critical crash rate) a location must have based on traffic volume to provide a high level of confidence that the collision occurring at the location is not random. For this study, a confidence level of 95% was used. The local crash rates were then compared to Significance Threshold to see if each location exceeded the expected CCR and if so, by how much. After this analysis was completed, the locations were ranked by their categories according to that level of exceedance.

3.2.4 Probability of Specific Crash Types Exceeding Threshold Proportion The Highway Safety Manual describes the methodology for determining the probability that crash type is greater than an identified threshold proportion. This helps to identify locations where a crash type is more likely to occur.

Data Needs

The probability of a specific crash type can be determined using collisions records with location data, and classifications of the locations (intersections or segments) studied.

Strengths

Can be used as a diagnostic tool Considers variance in data

Not affected by selection bias

The HSM methodology first determines the frequency of a specific collision type at an individual location, then determines the observed proportion of that collision type relative to all collision types at that location. A threshold proportion is then determined for the specific collision type;

HSM suggests utilizing the proportion of the collision type observed in the entire reference population (e.g. throughout the entire City of Chino).

These proportions are then utilized to determine the probability that the proportion of a specific crash type is greater than the long-term expected proportion of that crash type.

Figure 2 – Probability of Specific Crash Types Exceeding Threshold Proportion

Source: Highway Safety Manual

3.2.5 Equivalent Property Damage Only (EPDO)

The equivalent property damage only (EPDO) method is described in the Highway Safety Manual. This method assigns weighting factors to crashes based on injury level (severe, injury, property damage only) to develop a property damage only score. In this analysis, the injury crash costs were calculated for each location (based on the latest Caltrans injury costs). This figure is then divided by the injury cost for a property damage only crash. The resulting number is the equivalent number of property damage only crashes at each site. This figure allows all locations to be compared based on injury crash costs. (Highway Safety Manual, Chapter 4).

Safety Partners As part of the LRSP, local stakeholders were included in the process to ensure that a diverse set of local perspectives were consistently involved in this planning effort. In addition to the Project Team which included City Staff from the Public Works Department, a stakeholder group was organized. This group consisted of the City’s Traffic Advisory Council (TAC), which includes members from the Chino Police Department, local school districts, and City Public Works.

These leaders in the City were called together to offer insight on the safety issues present in the City’s transportation network. After the initial network screening and safety analysis, the stakeholder group met to discuss potential countermeasures and challenge areas. The summary of the stakeholder meetings are outlined below.

4.1 Stakeholder Meeting #1

The first stakeholder meeting was conducted in person at the monthly TAC meeting on January 13, 2022. At the meeting, stakeholders were introduced to the project and provided an overview of the data used, the required outputs, and the potential outcomes of the study. In addition to the overview, Stakeholders were shown potential emphasis areas.

4.2 Stakeholder Meeting #2

At the monthly TAC meeting on February 16, 2022, the stakeholder group were introduced to 12 site locations. During this meeting collision diagrams were provided to the stakeholders which listed observations and potential countermeasures.

Stakeholders were asked for their opinions and were encouraged to discuss the locations for additional insight to include in the LRSP.

4.3 Public Meeting Regarding East End Ave/Schaefer Ave

Intersection

A Traffic Advisory Council meeting was made open to the public on March 16th, 2022. At this meeting City staff and members of the public discussed safety issues at East End Avenue and Schaefer Ave, as well as any potential countermeasures that can be implemented at this location. The feedback and countermeasures identified are included in this report. Kimley-Horn staff was not present at this meeting.

Existing Efforts Existing plans, policies, and projects that were recently completed, planned, or are on-going within the City of Chino were compiled at the start of the LRSP process to gain perspective on the existing efforts for transportation-related improvements within the City. High-level key points regarding transportation improvements and safety-related topics were identified to inform decision making in this LRSP. Information reviewed included the following:

City of Chino General Plan (2025 – Chino): A long-range plan that outlines City’s transportation network, including functional classification, existing volumes/LOS for roadways.

City of Chino Policy on Accessible Pedestrian Facilities (2019 – Chino): A strategic plan that outlines City’s policy on providing Accessible Pedestrian Facilities with a focus on universal design for pedestrian facilities.

City of Chino Bicycle and Pedestrian Master Plan (2016– Chino): A plan that outlines existing and planned active transportation facilities.

City of Chino Climate Action Plan (2020-2030 – Chino): A strategic plan that establishes goals and policies to manage the City’s Greenhouse Gas (GHG) emissions.

Data Summary As a data driven process, utilizing the most recent and accurate data is crucial. The following section describes the data inputs used for the analysis process of this LRSP.

6.1 Roadway Network

The Caltrans California Road System (CRS) GIS database was used to build the base roadway network used for this analysis. Functional Classifications were then imported from the City’s General Plan. Traffic volumes and signal locations were provided by the City and were included in the analysis network. Intersections and roadway segments were divided into control and classification categories so that each set could have its own crash rates and be evaluated against similar facilities. Figure 3 illustrates Chino’s roadway network and illustrates Chino’s intersections as classified for this study.

6.2 Intersections

The collision analysis requires each intersection be classified by type: Signalized or Unsignalized. The safety analysis compares intersection safety performance to locations with similar control types. Figure 3 shows the locations of signalized intersections within the City.

6.3 Count Data

Vehicular count data is used as part of the analysis process to evaluate the impact of traffic and understand the natural hierarchy of the roadway network. Count data utilized for this project was pulled from the 2021 Engineering and Traffic Survey. For locations without volume or count data, a reasonable assumption was made based upon available roadways with similar classifications.

The traffic volume information allowed the team to assess locations for risk to a given roadway user as well as reviewing locations with the highest number of collisions

6.4 Collision Data

Collision data was collected from Crossroads Software for the period from January 1, 2016 through December 31, 2019. Five years of data are utilized instead of the standard three years to provide more history to evaluate trends or patterns. Analysis of the raw collision data is the first step in understanding the specific and systemic challenges faced throughout the City.

Analyzing the five years of data provided insight on the following collision trends and patterns.

The locations of fatal and severe injury collisions are displayed in Figure 4, and the number of collisions per intersections and roadway segments are shown in Figure 5.

Figure 3: Functional Classification (2016-2020)

Figure 4: Fatal and Severe Injury Collisions (2016-2020)

Figure 5: Density of all Crashes at Intersections and Segments (2016-2020)

Crash Safety Trends The following section breaks down the collision data by a variety of factors and user types. This information will be used to highlight areas of concern for the City.

7.1 All Crashes

This report utilized collision data for a five-year period to provide a better understanding of trends and to reflect the patterns in crashes that have occurred on City streets. New data is added to the system in an ongoing basis which means that each time the City updates the analysis, a full 5-year draw from the database, rather than just adding records from the last query should be standard practice. Data used for this report were extracted from Crossroads Software analytics on November 11, 2021 and was current as of that date. Collision data from January 1, 2016 through December 31, 2020 as reported to Crossroads from the local enforcement indicated that during this time there were 4,505 collisions recorded within Chino

During this time, the most common occurring collision types were Broadsides (31%) and Rear-ends (30%). The total number of collisions varied throughout the study period, with a peak in 2018 and a considerable drop in 2020.

7.2 Fatalities

During the study period, 29 fatal collisions and 69 severe injury collisions occurred during the study period, as seen in Figure 4. Table 1 outlines the fatal and severe injury collisions categorized by modes involved.

2016 2017 2018 2019 2020

N o.

o f C ol lis io ns

Study Years

Broadside

Rear-End

Sideswipe

Hit Object

Head-On

Vehicle - Pedestrian

Other

Overturned

Not Stated

Figure 6: Collision Type by Year (2016-2020)

Table 1: Fatal Crashes Categorized by Modes Involved (2016-2020)

Involved With # of Fatal Collisions

# of Severe Injury Collisions

Other Motor Vehicle 7 40

Pedestrian 8 11

Fixed Object 9 10

Bicycle 3 3

Parked Motor Vehicle - 2

Other - 3

7.3 Injury Levels

63% of the collisions reported during the time-period resulted in property damage only. Fatalities and severe injuries totaled 1.9% of all collisions.

Figure 7: Collisions by Injury Levels (2016-2020)

63%

22%

12%

1.5% 0.6%

Property Damage Only

Complaint of Pain

Other Visible Injury

Severe Injury

Fatal

7.4 Cause of Collisions

The highest recorded cause of collisions in Chino during the study period is Unsafe Speed at 27.5%, followed by Improper Turning at 19.1% and Auto Right-of-Way Violation at 17.9%.

Issues with Drivers Ignoring Traffic Signals and Signs also had a substantial impact on the City, comprising 8.7% of the collisions.

27.46%

19.11%

17.98%

8.75%

7.90%

3.75%

3.15%

2.86%

1.42% 1.35% 1.22% 1.20% 1.02%

0.75%

0.69%

0.64%

0.58%

0.09%

0.04%

0.02%

Unsafe Speed

Improper Turning

Auto R/W Violation

Traffic Signals and Signs

Driving Under Influence

Unknown

Unsafe Starting or Backing

Unsafe Lane Change

Following Too Closely

Improper Passing

Wrong Side of Road

Other

Other Than Driver or Ped

Other Improper Driving

Pedestrian Violation

Ped R/W Violation

Other Hazardous Movement

Other Equipment

Hazardous Parking

Impeding Traffic

Figure 8: Cause of Crashes (2016-2020)

7.5 Vulnerable Users

7.5.1 Pedestrians

88 pedestrian involved collisions occurred during the study period, resulting in 8 fatal collisions, 11 severe injuries, and 67 collisions with some form of reported injury or pain. Figure 9 shows the locations of pedestrian collisions during the study period.

7.5.2 Bicycle

During the study period, 89 collisions involving bicycles were reported. Of these, 3 were fatal, and 3 resulted in severe injuries. Figure 9 shows the location of bicycle collisions during the study period.

Figure 9: : Pedestrian & Bicycle Collisions (2016-2020)

7.6 Significant Trends for Passenger Vehicles

7.6.1 Other Significant Trends

31% of collisions occurred at night or during the dusk/dawn hours.

Drivers aged 16-20 were at fault in 12.2% of all collisions.

Drivers aged 65+ were at fault in 6.5% of all collisions

7.7 Initial Findings

Through the initial crash and network screening analysis, an initial ranking of locations of interest was developed. The intersections and roadway segments by sub-population are identified in Table 2 and Table 3. Locations were only considered if they had three or more crashes to be statistically relevant.

Table 2: Analysis Rankings – Intersections (Top 10 Locations Per Type)

In te rs ec tio n

Cr as he s

Lo ca l C

CR

D iff er en tia l1

EP

D

O

Fa ta l

Se rio us In ju ry

O th er V is ib le In

Co m pl ai nt o f P ai n

PD

Br oa ds id e

Si de sw ip e

Re ar

E nd

H ea d O n

H it

O bj ec t

O ve rt ur ne d

O er

Pe de st ria n

Bi cy cl e

Ag gr es si ve

D is tr ac te d

Im pa ire d

D ar k

W et

Signalized Intersections

Central Ave. & Riverside Dr 57 2.10 449 0 2 3 7 45 12 13 16 10 10 0 2 3 1 13 0 2 11 3

Central Ave. & Philadelphia St 55 5.70 190 0 0 4 19 32 12 14 22 2 2 0 0 3 2 16 0 3 21 3

Euclid Ave. (SR-83) & Kimball Ave. 47 0.05 141 0 0 5 9 33 7 9 27 1 1 2 0 0 0 25 0 0 12 2

Ramona Ave. & Riverside Dr. 47 0.22 370 0 1 8 16 22 19 8 8 0 0 0 1 1 5 12 0 0 11 3

Ramona Ave. & Schaefer Ave. 46 0.23 353 0 1 8 13 24 26 3 5 0 0 0 0 0 0 4 0 1 16 1

Central Ave. & Walnut Ave 41 4.03 126 0 0 3 11 27 7 6 24 2 2 1 0 1 1 20 0 3 14 6

Benson Ave. & Riverside Dr. 37 0.31 315 0 1 6 11 19 18 6 8 0 0 0 1 2 0 5 0 2 12 1

Central Ave. & Columbus Ave. 35 0.36 269 0 1 2 10 22 15 7 10 1 1 0 0 1 2 7 0 2 6 0

Monte Vista Ave. & Edison Ave. 35 0.15 482 1 1 6 12 15 20 2 5 2 2 0 1 0 0 5 0 1 5 2

Pipeline Ave. & Edison Ave 34 1.54 113 0 0 5 6 23 12 10 5 3 3 1 0 1 2 4 0 3 11 3

Unsignalized Intersections Monte Vista Ave. & Walnut Ave. 26 0.52 66 0 0 2 4 20 11 3 4 5 5 0 1 1 0 5 0 3 10 1

Monte Vista Ave. & Chino Ave. 17 0.29 61 0 0 3 3 11 11 2 2 0 0 0 0 0 1 2 0 1 4 2

Central Ave. & G St 15 0.37 228 0 1 4 2 8 7 2 4 1 1 0 0 0 0 3 0 0 2 0

Central Ave. & Jefferson Ave 14 0.19 53 0 0 3 2 9 4 4 6 0 0 0 0 0 0 3 0 0 1 2

5th St & Chino Ave. 12 0.81 37 0 0 1 3 8 10 0 1 1 1 0 0 0 0 1 0 0 3 1

Twelfth St. & Riverside Dr. 12 0.45 22 0 0 0 2 10 7 3 1 0 0 0 0 1 0 1 0 0 1 1

Central Ave. & Mt Vernon Ave 12 0.13 17 0 0 0 1 11 5 4 3 0 0 0 0 0 0 2 0 1 2 1

Fern Ave. & Bickmore Ave. 10 0.93 35 0 0 0 5 5 9 1 0 0 0 0 0 0 0 0 0 0 2 3

In te rs ec tio n

Cr as he s

Lo ca l C

CR

D iff er en tia l1

EP

D

O

Fa ta l

Se rio us In er V is ib le In pl ai nt o f P ai n ds id e

Si de sw ip e

Re ar d O n

H it

O bj ec t

O ve rt ur ne d

O st ria n

Bi cy cl e

Ag gr es tr ac te d

Im pa ire d

D ar k

Monte Vista Ave. & C St 9 0.55 43 0 0 3 1 5 5 4 0 0 0 0 0 0 0 1 0 2 5 0

Oaks Ave. & Chino Ave. 8 0.26 23 0 0 1 1 6 6 0 2 0 0 0 0 0 0 1 0 1 1 0

1. Local Critical Crash Rate Differential

2. Equivalent Property Damage Only Crashes

Table 3: Analysis Rankings – Segments (Top 10 Locations Per Type)

Facility Limits

Cr as he s

Lo ca l C

CR

D iff er en tia l1

EP

D

O

Fa ta l

Se rio us In er V is ib le In pl ai nt o f P ai n ds id e

Si de sw ip e

Re ar d O n

H it

O bj ec t

O ve rt ur ne d

O st ria n

Bi cy cl e

Ag gr es tr ac te d

Im pa ire d

D ar k

Major

Central Ave.

EB 60 On Ramp - WB 60 On Ramp

65 5.10 214 0 0 7 16 42 30 10 16 3 3 1 0 2 3 17 0 3 18 2

Euclid Ave. (SR-83) Pine Ave. - NB 71 Ramp 48 -0.12 341 1 0 7 12 28 3 6 24 2 9 2 1 0 0 24 0 3 18 3

Pine Ave.

Euclid Ave. (SR-83) - Meadowhouse Ave.

37 1.25 286 0 1 2 13 21 0 2 34 0 0 0 1 0 0 34 0 0 4 0

Central Ave.

WB 60 On Ramp - Philadelphia St

34 1.56 297 1 0 5 10 18 18 7 7 1 1 0 0 1 0 8 0 1 8 2

Mountain Ave.

WB 60 On Ramp - EB 60 On Ramp

23 2.73 68 0 0 1 7 15 5 3 13 1 0 1 0 0 0 10 0 2 9 0

Euclid Ave. (Sr-83) Merrill Ave - Kimball Ave 17 -0.35 216 1 0 1 5 10 3 4 7 1 1 0 0 1 0 7 0 1 9 3

Central Ave. Carson St - Country Fair 15 0.18 74 0 0 4 4 7 5 2 4 1 1 0 0 2 2 4 0 0 2 2

Mountain Ave. Eb 60 On - Walnut Ave. 15 1.43 51 0 0 0 7 8 7 1 6 0 0 0 0 1 0 5 0 1 4 3

Riverside Dr. Monte Vista Ave. - Central Ave 13 7.67 211 0 1 2 3 7 5 1 6 0 0 0 0 0 0 6 0 1 3 2

Pine Ave.

Meadowhouse Ave. - Rincon Meadows Ave.

12 -0.12 37 0 0 1 3 8 0 1 7 1 2 1 0 0 0 9 1 1 4 1

Primary

Ramona Ave. Walnut Ave. - Riverside Dr. 16 1.35 214 0 1 2 3 10 3 4 8 0 1 0 0 0 0 8 0 3 9 0

Chino Hills Pkwy.

Ramona Ave. - Monte Vista Ave.

13 -0.03 13 0 0 0 0 13 1 3 3 2 4 0 0 0 0 5 0 0 2 2

Ramona Ave. Walnut Ave. - Roosevelt St 12 1.35 47 0 0 1 5 6 1 1 10 0 0 0 0 0 0 10 0 0 3 0

Ramona Ave. Roosevelt St - Wilson St 11 1.04 36 0 0 1 3 7 1 1 9 0 0 0 0 0 0 6 0 3 6 0

Ramona Ave. Schaefer Ave. - Edison Ave. 9 0.11 198 0 1 1 3 4 1 0 1 1 6 0 0 0 0 2 0 2 6 4

Cr as he s

Lo ca l C

CR

D iff er en tia l1

EP

D

O

Fa ta l

Se rio us In er V is ib le In pl ai nt o f P ai n ds id e

Si de sw ip e

Re ar d O n

H it

O bj ec t

O ve rt ur ne d

O st ria n

Bi cy cl e

Ag gr es tr ac te d

Im pa ire d

D ar k

Kimball Ave.

Euclid Ave. (SR-83) - Mayhew Ave

9 -0.01 520 1 2 1 2 3 1 2 1 2 1 2 0 0 1 5 0 1 4 2

Ramona Ave. Philadelphia St. - Eb 60 On 7 0.26 22 0 0 1 1 5 2 2 3 0 0 0 0 0 0 3 0 0 2 0

Schaefer Ave. Monte Vista Ave. - Central Ave. 6 -0.07 26 0 0 1 2 3 0 1 4 0 0 0 1 0 0 5 0 0 2 0

Kimball Ave. Main St - Flight Ave 6 0.12 30 0 0 2 1 3 1 0 1 0 3 1 0 0 0 0 0 2 3 0

Kimball Ave. Flight Ave - Meadow Valley Ave 6 0.14 21 0 0 1 1 4 1 0 3 1 1 0 0 0 0 4 0 0 2 1

Secondary

Kimball Ave. El Prado Rd. - Mountain Ave. 21 -0.01 75 0 0 4 3 14 0 3 15 0 1 1 1 0 0 16 0 0 5 0

Pipeline Ave. Edison Ave - Eucalyptus Ave 19 0.20 257 0 1 5 5 8 7 3 5 1 1 1 0 1 1 4 0 1 3 0

El Prado Rd. Alton St - Kimball Ave. 19 0.56 213 0 1 0 6 12 8 0 4 0 7 0 0 0 0 7 0 2 8 4

Kimball Ave.

San Antonio Ave. - Euclid Ave.

(SR-83)

14 0.87 39 0 0 1 3 10 3 0 10 0 0 0 1 0 0 8 0 2 4 2

Philadelphia St. Bridger Ave - Central Ave 13 2.23 53 0 0 2 4 7 8 3 0 1 0 0 0 2 1 0 0 0 6 2

Pipeline Ave. Spectrum - Edison Ave 13 0.02 211 0 1 2 3 7 3 2 3 3 2 0 0 0 1 5 0 1 1 2

El Prado Rd. Gates St - Kimball Ave. 11 0.56 51 0 0 2 4 5 4 1 5 0 0 0 1 0 0 5 0 0 2 1

Philadelphia St. Ford Dr - Ramona Ave. 9 1.34 44 0 0 2 3 4 2 0 7 0 0 0 0 1 0 6 0 0 1 1

Walnut Ave. Telephone Ave - Marshall Ave 9 1.47 14 0 0 0 1 8 3 3 3 0 0 0 0 0 0 2 0 2 4 0

Monte Vista Ave. Park St - Riverside Dr 8 1.76 52 0 0 3 3 2 1 0 5 2 0 0 0 0 0 3 0 0 2 0

Collector

Roswell Ave. Schaefer Ave - Grand Ave. 12 0.33 57 0 0 2 5 5 9 1 1 0 0 0 0 1 1 0 0 0 5 0

Ramona Ave. Riverside Dr. - Chino Ave. 9 0.27 48 0 0 3 2 4 4 1 3 1 0 0 0 0 0 3 0 0 0 0

Yorba Ave. Walnut Ave - Davis St 6 5.24 6 0 0 0 0 6 0 4 1 0 1 0 0 0 0 1 0 0 1 0

Eucalyptus Ave. Pipeline Ave - Appian Way 6 0.24 30 0 0 2 1 3 4 1 0 0 0 0 0 0 0 0 0 0 2 0

Mountain Ave. Bickmore Ave. - Flowers St 6 7.19 6 0 0 0 0 6 1 1 0 0 4 0 0 0 0 2 0 0 3 1

Cr as he s

Lo ca l C

CR

D iff er en tia l1

EP

D

O

Fa ta l

Se rio us In er V is ib le In pl ai nt o f P ai n ds id e

Si de sw ip e

Re ar d O n

H it

O bj ec t

O ve rt ur ne d

O st ria n

Bi cy cl e

Ag gr es tr ac te d

Im pa ire d

D ar k

Euclid Ave. (SR-83) Pomona Rincon Rd - Nb 71 On 6 -0.52 179 1 0 1 0 4 0 3 1 1 1 0 0 0 0 2 0 1 1 1

Yorba Ave. Wilson St - Park St 5 3.59 20 0 0 1 1 3 1 2 1 1 0 0 0 0 0 0 0 1 1 0

Yorba Ave. Murrieta St - Schaefer Ave. 5 1.27 15 0 0 0 2 3 2 1 0 0 0 0 2 0 0 0 0 0 0 0

Norton Ave. Schaefer Ave. - Edison Ave 5 0.92 15 0 0 1 0 4 3 1 0 0 1 0 0 0 0 0 0 0 1 0

Telephone Ave. Edison Ave - Lindsay Ct 5 2.45 5 0 0 0 0 5 1 2 1 0 1 0 0 0 0 2 0 0 1 1

Local

Park Pl. 13th - Benson Ave 10 7.13 45 0 0 2 3 5 2 4 2 0 1 0 0 1 0 1 0 1 2 1

Fern Ave. Kimball Ave - Bickmore Ave. 9 1.33 187 0 1 1 1 6 2 1 2 2 1 0 0 1 0 2 0 0 6 0

Jefferson Ave. Catalpa Pl - Benson St 6 23.64 16 0 0 1 0 5 2 1 0 1 1 0 0 1 0 0 0 3 3 0

G St Monte Vista Ave - 3rd St 6 14.98 16 0 0 1 0 5 3 1 2 0 0 0 0 0 1 1 0 1 1 0

Revere St Telephone Ave - Telephone Ave 5 6.13 15 0 0 1 0 4 1 4 0 0 0 0 0 0 1 0 0 0 2 0

7th St Park St - Riverside Dr 5 9.93 10 0 0 0 1 4 2 1 0 2 0 0 0 0 1 0 0 0 0 0

Park Pl. Tenth St. - 12th St 4 1.70 9 0 0 0 1 3 1 0 1 1 0 0 0 1 0 0 0 0 0 0

Tenth St. Riverside Dr. - B St 4 8.12 14 0 0 1 0 3 1 1 0 1 0 0 1 0 0 1 0 0 1 0

4th St Riverside Dr - B St 4 7.46 173 0 1 0 1 2 1 0 0 2 0 0 1 1 0 1 0 0 1 0

Vinita Ct Yorba Ave - End 4 4.52 4 0 0 0 0 4 0 0 0 0 4 0 0 0 0 0 0 0 1 0

1. Local Critical Crash Rate Differential

2. Equivalent Property Damage Only Crashes

7.8 Statewide Comparison

A comparison of fatal & severe injury collision data to the State averages were conducted for data from 2015-2018 (the most recent statewide data available). These numbers may vary slightly from those mentioned previously, due to the differences in the years of the study period.

The following are areas where Chino’s collision rates are higher or lower than those of the State. These numbers specifically compare the proportion of fatal and serious injury crashes that have the characteristics listed in Table 4.

Table 4: Comparison of Statewide and Chino Fatal & Severe Injury Crashes (2015-2018)

Challenge Area Statewide % Chino % Percentage Difference

Chino has a Higher Percentage of F&SI Crashes

Aggressive Driving 33.3% 49.0% 15.7%

Motorcyclists 21.8% 31.6% 9.8%

Young Drivers 12.3% 17.2% 4.9%

Commercial Vehicles 6.5% 10.2% 3.7% Improper Use of Occupant Protection

13.8% 16.1% 2.3%

Distracted Driving 4.7% 6.5% 1.8%

Aging Drivers (65+) 13.1% 14.3% 1.2%

Chino has a Lower Percentage of F&SI Crashes Work Zones 1.4% 1.1% -0.3%

Bicyclists 7.5% 5.1% -2.4%

Pedestrians…