PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Limonite Gap Closure
PROJECT DESCRIPTION: Project will connect from 2,450 LF east of Hellman Ave to Archibald Avenue. The total length of the proposed project is approximately 3,200 LF including a bridge over the Cucamonga Creek. Both road and bridge will serve 4 lanes of traffic including bicycle and pedestrian facilities. A separate pedestrian bridge over the Cucamonga Creek little south of the proposed vehicular bridge, as shown on the below map, is also part of this project.
PROJECT STATUS: 95% plans and specifications under review.
Construction Management service procured.
Working with various agencies to obtain necessary permits.
PROJECT SCHEDULE: Estimated 100% design - January 2023 PROJECT MAP:
Proposed Limonite Ave Bridge
Proposed Pedestrian Bridge
269
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Improvement of Bike Network Connectivity/ATP Trails PROJECT DESCRIPTION: Project will design and construct nearly 5 miles of trails running along Scholar Way and Harrison Avenue. The project will provide dedicated space for people to bike and walk from north Eastvale to the Santa Ana River Trail on the south.
PROJECT STATUS: Design contract was awarded to Mark Thomas. 30% plans and specifications have been delivered. Currently working with Caltrans to approve scope change to change from Class IV with lane reduction to Class I with no lane reduction.
PROJECT SCHEDULE: Mark Thomas is going to start Phase 2 efforts consisting of developing construction documents.
PROJECT MAP:
PROJECT TYPE: Capital Improvements Project
270
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT NAME: Schleisman Road Safety and Connectivity Project PROJECT DESCRIPTION: Project will design and construct dedicated space for people to bike and walk along Schleisman Road between Hamner Avenue and Sumner Avenue.
PROJECT STATUS: Conceptual development contract was awarded to Conceptual Design & Planning Company.
PROJECT SCHEDULE: Once conceptual plan is completed, City will solicit proposals for development of plans and specifications.
PROJECT MAP:
271
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Limonite Avenue Signal Synchronization
PROJECT DESCRIPTION: Project will design and install necessary equipment to synchronize traffic signals along Limonite Avenue.
PROJECT STATUS: Construction contract was awarded to Belco on May 11, 2022 to install necessary infrastructure to synchronize the traffic signals, and construction is underway.
PROJECT SCHEDULE: There is a long lead time on the necessary materials to connect the traffic signals with fiber-optic. As an interim solution, City has successfully synchronized the traffic signal using wireless radios. The construction to install fiber communications has started and expected to be completed in January 2023.
PROJECT MAP:
272
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Citywide Retroreflective Backplate on Traffic Signal Indicator PROJECT DESCRIPTION: Project will design and install retroreflective backplate borders along backplates of traffic signal indicators at 39 signalized intersections to improve the visibility of signals.
PROJECT STATUS: Construction contract was awarded on January 11, 2023 Council meeting, and construction management service has been procured.
PROJECT SCHEDULE: The construction is estimated to commence in February 2023.
PROJECT MAP:
273
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Traffic Signal Dilemma Zone Detection and Mitigation PROJECT DESCRIPTION: Project will install advanced dilemma zone detection system and associated equipment in existing traffic signal cabinets at 16 signalized intersections to modify signal timing to improve safety for motorists approaching intersections.
PROJECT STATUS: CON allocation was approved by Caltrans. Preparing bid package to advertise the project for construction bid.
PROJECT SCHEDULE: The construction is estimated to commence in mid 2023.
PROJECT MAP:
274
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: ADA Transition Plan
PROJECT DESCRIPTION: Program includes preparation and implementation of an ADA Self Evaluation Plan as required under the Americans with Disabilities Act (ADA). Future year funding will support removal of ADA barriers as identified in the Plan. Annual program to provide improvements focusing on ADA accessibility, including curb ramps and sidewalks throughout the City.
PROJECT SCHEDULE: This is an on-going project. Currently, field work to identify ADA barriers on City streets including curb ramps and sidewalks is on hold.
275
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Traffic Sign Inventory
PROJECT DESCRIPTION: The project will improve roadway safety and traffic through upgrades to existing and/or adding new high-visibility traffic signs.
PROJECT SCHEDULE: Inventory of traffic sign has been completed. Field work to collect reflectivity of signs to meet MUTCD has been completed.
276
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Capital Improvements Project
PROJECT NAME: Archibald Avenue/Limonite Avenue Widening Project PROJECT DESCRIPTION: Street widening and safety project for Archibald Avenue from the City of Ontario limits south of the SCE easement, including the intersection at Limonite Avenue and portions of Limonite Avenue east and west of the intersection. The project looks to improve safety and overall circulation in conjunction with the improvements associated with the Homestead and Merge developments, and Limonite Gap Project. Components of the project include, but are not limited to, coordinating with SCE to relocate SCE high-tension support structures.
PROJECT STATUS: • City approved the proposed design plan from SCE on July 14, 2021. • Installation of new transmission poles is completed.
• Construction is estimated to be completed in early 2023 for all overhead lines.
PROJECT MAP:
LIMONITE AVE
ARCHIBALD AVE
277
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Residential Development
PROJECT NAME: Prado (TR 35751)
PROJECT LOCATION: Southeast corner of Schleisman Road and Cucamonga Flood Channel PROJECT DESCRIPTION: Improvements include a development of a gated community of 243 attached and detached single-family homes on approximately 19 acres.
PROJECT STATUS: Improvements have been completed. Project close-out task is remaining before city council accepts the project as complete.
PROJECT MAP:
SCHLEISMAN RD
278
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: The Merge
PROJECT LOCATION: Northeast corner of Limonite Avenue and Archibald Avenue PROJECT DESCRIPTION: Improvements includes 26 gross acres.
PROJECT STATUS: Onsite and offsite improvements ongoing PROJECT MAP:
ARCHIBALD AVE
LIMONITE AVE
279
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: The Ranch by Transwestern
PROJECT NUMBER: PW19-11322
PROJECT LOCATION: East end of Limonite Avenue west of the Cucamonga Creek PROJECT DESCRIPTION: Improvements include 20 gross acres including 2 light industrial warehouses.
PROJECT STATUS: Onsite and offsite improvements have been completed, the City and Developer are working together to close out the project.
PROJECT MAP:
CUCAMONGA CREEK
HELLMAN AVE
280
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: Homestead
PROJECT NUMBER: PW20-10052
PROJECT LOCATION: Northwest corner of Limonite Avenue and Archibald Avenue PROJECT DESCRIPTION: Improvements include 55.86 gross acres consisting of six industrial buildings
PROJECT STATUS: Onsite and offsite improvements ongoing PROJECT MAP:
LIMONITE AVE
ARCHIBALD AVE
281
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: Vantage Point Church
PROJECT NUMBER: PW15-1174
PROJECT LOCATION: Northeast corner of Archibald Avenue and Prado Basin Park Road PROJECT DESCRIPTION: Improvements include development of an approximate ly 85,000 sq. ft. church which includes a sanctuary, classrooms, cafe, and a bookstore on 10.43 acres.
PROJECT STATUS: Onsite improvement ongoing
Phase 2 anticipated to start in 2023 which will include the widening of Archibald Avenue
PROJECT MAP:
282
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: Hamner Place
PROJECT NUMBER: PW18-10712
PROJECT LOCATION: East of Hamner Avenue and Schleisman Road PROJECT DESCRIPTION: Improvements include 21.48 gross acres.
PROJECT STATUS: Onsite improvement ongoing
PROJECT MAP:
HAMNER AVE
283
EASTVALE PUBLIC WORKS
PROJECT UPDATES
PROJECT TYPE: Commercial Development
PROJECT NAME: The Ranch (Parcel 14)
PROJECT NUMBER: PW20-10007
PROJECT LOCATION: East of Limonite Avenue west of the Cucamonga Creek PROJECT DESCRIPTION: Improvements include the development of 61,000 square foot industrial building.
PROJECT STATUS: Grading started in December 2022
PROJECT MAP:
CUCAMONGA CREEK
284
AGENCY GRANT NAME PROJECT NAME GRANT AWARD MATCH DUE DATE STATUS CTC/
Caltrans
Active Transportation Project Improvement of Bike Network Connectivity
$ 6,471,000.00 $ 1,620,000.00 6/30/2025 Under design CTC/
Caltrans
Local Partnership Program Limonite Gap Closure Project 9,475,000.00$ - $ Award construction by late 2023
Grant request has been
approved. Allocation for
construction funds will be
requested in June 2023.
CTC/
Caltrans
Active Transportation Project Southeast Eastvale Safe Routes to School Gap Closures
1,420,000.00$ - $ Construction in FY22/23
Grant request has been
approved. Extension request
will be submitted.
Caltrans
Highway Safety Improvement
Program (HSIP) Cycle 10
Advanced Dilemma Zone
Detection
712,800.00$ - $ Under design Caltrans
Highway Safety Improvement
Program (HSIP) Cycle 10
Retroflective Backplate for
Signals
278,100.00$ - $ Under Construction CalRecycle Rubberized Pavement Grant
TRP 13
Annual Overlay Project $ 174,999.00 $ - April 1, 2023 Grant request has been approved. Extension request
submitted.
RCTC SB821 Bicycle and Pedestrian Safety
Enhancement on Citrus St,
Sumner Ave and River Rd
$ 432,500.00 $ 469,953.00 Under construction as part of the Annual Overlay Project
CAL FIRE Resource Management Grant City of Eastvale Urban Foresty Management
$ 249,925.00 $ 60,024.00 March 30, 2024 Under design Caltrans
Highway Safety Improvement
Program (HSIP) Cycle 11
Systemic Roadway and
Intersection Safety
Improvement
2,375,640.00$ 263,960.00 $ September 12, 2022 Grant application has been submitted
Caltrans
Highway Safety Improvement
Program (HSIP) Cycle 11
Traffic Signal Coordination and
Raised Pavement Markers
589,000.00$ 589,000.00 $ September 12, 2022 Grant application has been submitted
PUBLIC WORKS GRANTS SUMMARY
AWARDED GRANTS
FUTURE GRANTS
285
AGENDA STAFF REPORT
City Council Meeting
CONSENT CALENDAR
Agenda Item No. 11.6
February 22, 2023
City of Eastvale Crime Statistics – December 2022
Prepared By:
Eva Terekhova, Emergency Management Specialist
Recommended Action(s)
Staff recommends that the City Council receive and file the Eastvale Crime Sta s
cs for December
2022.
Summary
The City Council requested staff to collaborate with the Riverside County Sheriff’s Department to develop a crime sta
s
cs document that would reflect selected Part I and Part II crime data for the City of Eastvale. Intended to show month-to-month crime sta s
cs, the document will assist in
determining appropriate staffing levels for law enforcement services.
Background
In May 2017, City Council directed staff to coordinate with the Riverside County Sheriff’s Department to request and obtain monthly crime sta
s
cs for the City of Eastvale. The primary
intent of the request was to determine appropriate staffing levels during the City’s contract nego
a
ons with the Sheriff’s Department. Over several weeks, the city manager and staff worked collabora
vely with Riverside County Sheriff’s Department administra on and management to
obtain crime statistics that could be shared with the public on a regular basis.
Upon receiving the data, the Riverside County Sheriff’s Department advised staff that the data provided would be reflec
ve of the previous month, or thirty days behind the current month; and that the report would need to include a disclaimer identifying the data as preliminary and raw.
At the July 26, 2017 mee
ng, City Council recommended that staff add columns reflec ve of felony 12363 Limonite Avenue | Suite 910 | Eastvale, CA 91752 951.361.0900 |
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286
and misdemeanor arrests. During the September 26, 2017 mee ng, City Council recommended staff
add traffic viola
ons/cita
ons data and the total calls for service broken down per month. Crime sta
s
cs that were released in the
me that passed since the last mee
ng of the City Council are
attached.
Environmental
Crime sta
s
cs are not a project pursuant to the California Environmental Quality Act (CEQA) and no environmental review is required.
Strategic Plan Action - Priority Level: N/A
| Target #: N/A
| Goal #: N/A
Not Applicable.
Fiscal Impact
This request has no fiscal impact.
Prior City Council/Commission Action
July 25, 2017: Approved by the Public Safety Commission September 26, 2017: Approved by City Council
Attachment(s)
Attachment - December 2022 Eastvale Crime Statistics
12363 Limonite Avenue | Suite 910 | Eastvale, CA 91752
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287
▪
▪
▪
▪
288
AGENDA STAFF REPORT
City Council Meeting
CONSENT CALENDAR
Agenda Item No. 11.7
February 22, 2023
Citywide Pavement Management System (PMS) Update
Prepared By:
Jimmy Chung, City Engineer
Recommended Action(s)
Staff recommends that the City Council receive and file the Citywide Pavement Management System (PMS) Report.
Summary
In February 2021, the City hired Stantec through an RFP process to conduct a citywide pavement condi(on assessment and to implement PMS to develop cost effec(ve work programs that the City can implement over the next 5 years.
The full scope of work included the following tasks:
Conduct a semi-automated pavement surface distress and roughness survey on the City's paved roads.
Conduct non-destruc(ve structural tes(ng on Arterial roads using Falling Weight Deflectometer (FWD) equipment to determine the structural capacity of the pavement and the condition of the subgrade soils.
Conduct Ground Penetra(ng Radar (GPR) non-destruc(ve tes(ng on Arterial roads to determine layer thickness information.
Implement RoadMatrix PMS to host the City's road inventory and condition data.
Conduct present status and budget analyses to determine the current condi(on of the road network and to develop 5-year cost effective work programs for various budget scenarios.
Provide a final report outlining the field-tes(ng procedures, network present status results, recommended work programs, and project conclusions and recommendations. 12363 Limonite Avenue | Suite 910 | Eastvale, CA 91752 951.361.0900 |
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The report is complete, and a copy of the final report is attached (Attachment No. 1) for reference.
Background
A Pavement Management System (PMS) is a tool that assists the City in making cost-effec(ve decisions related to the maintenance and rehabilita(on of roadway pavements. A PMS allows the City to maximize the use of limited funding for pavement improvements by taking a comprehensive approach to managing the City’s pavements instead of a “worst-first” pavement plan. The PMS considers pavement life cycle costs in determining what work should be completed. This involves applying the right treatment to the right pavement at the right (me to maximize a pavement’s service life at the lowest cost. This is known as “preventative maintenance.”
Data Collection and Present Status
The exis(ng surface condi(on data was collected using the advanced semi-automated survey equipment, Road Tester 3000 (RT3000), which uses downward imaging technology. It was then used to identify the Present Status of the road network in terms of four (4) performance indicators:
1. Ride Comfort Index (RCI) - Represents the smoothness (ride quality) of the road.
2. Surface Distress Index (SDI) - Represents the surface condition of the road (cracking, rutting, etc.)
3. Structural Adequacy Index (SAI) - Represents the structural adequacy of the road.
4. Pavement Quality Index (PQI) - Overall condition index, a function of the above-noted indices.
Each indicator is presented on a scale of 0-100 with 0 represen(ng the worst possible condi(on. The initial survey resulted in the following observations:
The City's road network is in "Fair" condition in 2021 with the overall network PQI of 63.
Arterial sections have a "Satisfactory" overall performance rating with PQI of 80.
Collector roads showed "Poor" overall condition rating with PQI of 51.
Analysis
Op(mal rehabilita(on strategies and implementa(on years for each sec(on were established according to the selected analysis method and the sec(ons' decision tree. A decision tree is a user- defined matrix which is used to determine feasible rehabilita(on strategies for each sec(on requiring maintenance or rehabilita(on during the programming period. A unique decision tree was developed for each combina(on of pavement type and func(onal class (i.e. Arterial). Factors such as previous rehabilita(on type, bus route, truck route, heavy traffic, etc. were all considered within the trees to generate work programs that are tailored to the local conditions and practices of the City.
A unique analysis method was used to develop the work program. The City was divided into 110 unique maintenance areas, and a unique iden(fica(on number was assigned to each area. Arterial and Collector roads have been given their own maintenance area iden(fica(on numbers. It was to priori(ze work in areas (called Maintenance Areas) with the highest area-weighted cost- effec(veness (CE) factor with a goal to aggregate the recommended work within certain areas (zones) in the City to minimize the mobilization costs.
The analysis was performed for three (3) budget scenarios: $2.5M/yr, $3.5M/yr, and $4.5M/yr. For each scenario, the predicted network PQI and network deficiency percentage were determined. 12363 Limonite Avenue | Suite 910 | Eastvale, CA 91752
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Recommendations
It is recommended that the City con(nue to priori(ze preven(ve maintenance-- it is much more cost-effec(ve to keep good roads in good condi(on as opposed to spending the majority of the available funds on roads that have already deteriorated past the preven(ve maintenance threshold.
Staff will con(nue to u(lize this tool when programming and implemen(ng the paving projects with a goal of optimized spending and keeping the City roads in good condition.
Environmental
No ac(on is being taken and no environmental analysis is required by the California Environmental Quality Act (CEQA).
Strategic Plan Action - Priority Level: 3
| Target #: 6
| Goal #: 2
Evaluate the pavement management cycle
Fiscal Impact
There is no fiscal impact for the recommended ac(on. The FY Budget includes $1,000,000 in funding for Residen(al Slurry Seal Project and $2,500,000 in funding for Annual Overly Project for next 5 years. Staff will continue to seek funding opportunities.
Prior City Council/Commission Action
On February 24, 2021 the City Council approved a professional services contract with Stantec to prepare the Citywide Pavement Management System (PMS) Report.
Attachment(s)
Attachment No. 1 - Eastvale PMS Report
12363 Limonite Avenue | Suite 910 | Eastvale, CA 91752
951.361.0900 |
eastvaleca.gov
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City of Eastvale, CA 2021
Citywide Pavement Condition
Assessment and PMS
Implementation – Final Report
August 3, 2022
Prepared for:
City of Eastvale
12363 Limonite Ave, suite 910
Eastvale, Ca 91752
Prepared by:
Stantec Consulting Services Inc.
3133 West Frye Road, Suite 300
Chandler, AZ 85226
292
CITY OF EASTVALE, CA 2021 CITYWIDE PAVEMENT CONDITION ASSESSMENT AND PMS IMPLEMENTATION – FINAL REPORT
ca \\ca0004-ppfss04\01620\active\174500434\phase\report\final\rpt_eastvale_20220803_fin.docx
This document entitled City of Eastvale, CA 2021 Citywide Pavement Condition Assessment and PMS Implementation – Final Report was prepared by Stantec Consulting Services Inc. (“Stantec”) for the account of the City of Eastvale (the “Client”). Any reliance on this document by any third party is strictly prohibited. The material in it reflects Stantec’s professional judgment in light of the scope, schedule and other limitations stated in the document and in the contract between Stantec and the Client. The opinions in the document are based on conditions and information existing at the time the document was published and do not take into account any subsequent changes. In preparing the document, Stantec did not verify information supplied to it by others. Any use which a third party makes of this document is the responsibility of such third party. Such third party agrees that Stantec shall not be responsible for costs or damages of any kind, if any, suffered by it or any other third party as a result of decisions made or actions taken based on this document.
Project Manager
(signature)
Fadi Jadoun, Ph.D., P.E.
Senior Reviewer
(signature)
Al Cepas, M.A.Sc.
293
CITY OF EASTVALE, CA 2021 CITYWIDE PAVEMENT CONDITION ASSESSMENT AND PMS IMPLEMENTATION – FINAL REPORT
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Table of Contents
ABBREVIATIONS .......................................................................................................................................................... I EXECUTIVE SUMMARY ............................................................................................................................................... II
1.0 PROJECT OVERVIEW ................................................................................................................................. 1.1
1.1 BACKGROUND ............................................................................................................................................ 1.1
1.2 PROJECT SCOPE AND OBJECTIVES ........................................................................................................ 1.1
1.3 REPORT ORGANIZATION ........................................................................................................................... 1.2
2.0 DATA COLLECTION.................................................................................................................................... 2.1
2.1 2021 FIELD SURVEY SCOPE ..................................................................................................................... 2.1
2.2 DATA COLLECTION METHODOLOGY ....................................................................................................... 2.1
2.2.1 Roughness Data Collection ..................................................................................................... 2.1
2.2.2 Surface Distress Data Collection ............................................................................................. 2.2
2.2.3 Laser - Transverse Profile / Rutting Data Collection ................................................................ 2.4
3.0 ROADMATRIX ANALYSIS MODELS .......................................................................................................... 3.1
3.1 PAVEMENT PERFORMANCE INDICES ...................................................................................................... 3.1
3.1.1 Roughness – Ride Comfort Index (RCI) .................................................................................. 3.1
3.1.2 Surface Distress – Surface Distress Index (SDI) ..................................................................... 3.1
3.1.3 Structural Adequacy Index (SAI) ............................................................................................. 3.1
3.1.4 Pavement Quality Index (PQI) ................................................................................................. 3.2
3.2 PAVEMENT DETERIORATION MODELS .................................................................................................... 3.2
3.2.1 Deterioration Curves ............................................................................................................... 3.2
3.3 MAINTENANCE AND REHABILITATION ANALYSIS .................................................................................. 3.3
3.3.1 Needs Assessment Analysis ................................................................................................... 3.3
3.3.2 Recommended Treatments Analysis ....................................................................................... 3.3
3.4 BUDGET ANALYSIS .................................................................................................................................... 3.9
3.4.1 Overview ................................................................................................................................. 3.9
3.4.2 Area-Weighted Cost Effectiveness Customized Analysis ...................................................... 3.10
4.0 INITIAL DATABASE SETUP ....................................................................................................................... 4.1
5.0 ANALYSIS RESULTS .................................................................................................................................. 5.1
5.1 PRESENT STATUS RESULTS .................................................................................................................... 5.1
5.1.1 Lane-Length Weighted Performance ....................................................................................... 5.1
5.1.2 Ride Comfort Index (RCI) ........................................................................................................ 5.2
5.1.3 Surface Distress Index (SDI) ................................................................................................... 5.5
5.1.4 Pavement Quality Index (PQI) ................................................................................................. 5.8
5.1.5 Structural Adequacy Index (SAI) ........................................................................................... 5.11
5.2 BUDGET ANALYSIS RESULTS ................................................................................................................. 5.12
5.2.1 Annual Budget Network Performance Results ...................................................................... 5.14
5.2.2 Budget Recommended Rehabilitations ................................................................................. 5.16
6.0 CONCLUSIONS ........................................................................................................................................... 6.1
6.1 PRESENT STATUS ...................................................................................................................................... 6.1
6.2 BUDGET ANALYSIS .................................................................................................................................... 6.1
7.0 RECOMMENDATIONS ................................................................................................................................ 7.1 294
CITY OF EASTVALE, CA 2021 CITYWIDE PAVEMENT CONDITION ASSESSMENT AND PMS IMPLEMENTATION – FINAL REPORT
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LIST OF TABLES
Table ES.1: 2021 Present Status Results – City Maintained Sections .......................................................................... iii Table ES.2: Budget Analysis Results 2022 – 2026 – City Maintained Sections ............................................................. v Table 2.1: Distress Types - Asphalt ............................................................................................................................ 2.3 Table 3.1: City of Eastvale – 2021 M&R Treatments Summary .................................................................................. 3.5 Table 5.1: 2021 Present Status Analysis Results – City Maintained Sections ............................................................ 5.1 Table 5.2: RCI Distribution; City Maintained Sections ................................................................................................. 5.2 Table 5.3: RCI Distribution; City Maintained Sections – 2021 by Functional Class ..................................................... 5.4 Table 5.4: SDI Distribution; City Maintained Sections ................................................................................................. 5.5 Table 5.5: SDI Distribution; City Maintained Sections – 2021 by Functional Class ..................................................... 5.7 Table 5.6: PQI Distribution; City Maintained Sections ................................................................................................. 5.8 Table 5.7: PQI Distribution; City Maintained Sections – 2021 by Functional Class ................................................... 5.10 Table 5.8: SAI Distribution; Arterial Sections* ........................................................................................................... 5.11 Table 5.9: Budget Analysis Results 2022 – 2026 – City Maintained Sections .......................................................... 5.13 Table 5.10: $2.5M/Year (Scenario 1) Budget Scenario Results ................................................................................ 5.14 Table 5.11: $3.5M/Year (Scenario 2) Budget Scenario Results ................................................................................ 5.14 Table 5.12: $4.5M/Year (Scenario 3) Budget Scenario Results ................................................................................ 5.14
LIST OF FIGURES
Figure ES.1: 2021 Present Status Map (PQI) ............................................................................................................... iv Figure 3.1: Rehabilitation Benefit on Performance Curve ........................................................................................... 3.3 Figure 3.2: Arterial-Flexible Pavement Decision Tree ................................................................................................. 3.7 Figure 3.3: Collector-Flexible Pavement Decision Tree .............................................................................................. 3.8 Figure 3.4: Local-Flexible Pavement Decision Tree Budget Analysis ......................................................................... 3.8 Figure 3.5: City of Eastvale Pavement Maintenance Areas ...................................................................................... 3.11 Figure 5.1: RCI 2021 Distribution; City Maintained Sections ....................................................................................... 5.2 Figure 5.2: SDI 2021 Distribution; City Maintained Sections ....................................................................................... 5.5 Figure 5.3: PQI 2021 Distribution; City Maintained Sections ....................................................................................... 5.8 Figure 5.4: SAI 2021 Distribution; Arterial Sections .................................................................................................. 5.11 Figure 5.5: Funding Impact on Network Predicted Average PQI ............................................................................... 5.15 Figure 5.6: Funding Impact on Network Predicted % Deficiency............................................................................... 5.15 Figure 5.7: $2.5M/Year (Scenario 1) Recommended Rehabilitations by Treatment ................................................. 5.16 Figure 5.8: $3.5M/Year (Scenario 2) Recommended Rehabilitations by Treatment ................................................. 5.17 F
igure 5.9: $4.5M/Year (Scenario 3) Recommended Rehabilitations by Treatment ................................................. 5.18
LIST OF APPENDICES
APPENDIX A RIDE COMFORT INDEX MAP ............................................................................................... A.1 APPENDIX B SURFACE DISTRESS INDEX MAP ...................................................................................... B.1 APPENDIX C PAVEMENT QUALITY INDEX MAP ...................................................................................... C.1 APPENDIX D SERIOUSLY POOR OR FAILED SECTIONS LIST ............................................................... D.1 APPENDIX E FIVE YEAR WORK PROGRAM (SCENARIO 1 - $2.5M/YEAR) ........................................... E.1 APPENDIX F FIVE YEAR WORK PROGRAM (SCENARIO 2 - $3.5M/YEAR) ........................................... F.1 APPENDIX G FIVE YEAR WORK PROGRAM (SCENARIO 3 - $4.5M/YEAR) ........................................... G.1 295
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ABBREVIATIONS
ABC Aggregate Base Course
ACP Asphalt Concrete Pavement
ALG Alligator Cracking
CL-MI Centerline Miles
FDR Full Depth Reclamation
FWD Falling Weight Deflectometer
GPR Ground Penetrating Radar
IRI International Roughness Index
LL-PQI Lane-Length Weighted PQI
LL-Def. Lane-Length Weighted Deficiency
LN-MI Lane Miles
Lon/TCr Longitudinal /Transverse Cracking
M&R Maintenance and Rehabilitation
MR Subgrade Soil Resilient Modulus
OL Overlay
PCC Portland Cement Concrete
PMS Pavement Management System
PQI Pavement Quality Index
RCI Ride Comfort Index
SAI Structural Adequacy Index
SDI Surface Distress Index
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EXECUTIVE SUMMARY
The City of Eastvale is responsible for the administration of a roadway network of approximately 173 centerline-miles (CL-MI) or 415 lane-miles (LN-MI). This network forms a valuable asset to be managed in a cost-effective manner. Providing a desirable level of service to the stakeholders is also important.
The City selected Stantec Consulting Services Inc. (Stantec) through an RFP process in 2021 to conduct a citywide pavement condition assessment and to implement Stantec’s RoadMatrix Pavement Management System (PMS) to develop cost effective work programs that the City can implement over the next 5 years. This report was prepared based on the 2021 data collection effort. A key component of an effective pavement management system is to regularly assess the condition of the road network, which can then be used to assess the performance of the network over time.
The 2021 scope of work included the following tasks:
• Conduct a semi-automated pavement surface distress and roughness survey on 173 centerline- miles of the City’s paved roads.
• Conduct non-destructive structural testing on Arterial roads using Falling Weight Deflectometer (FWD) equipment to determine the structural capacity of the pavement and the condition of the subgrade soils.
• Conduct Ground Penetrating Radar (GPR) non-destructive testing on Arterial roads to determine layer thickness information.
• Implement Stantec’s RoadMatrix PMS to host the City’s road inventory and condition data. • Conduct present status and budget analyses to determine the current condition of the road network and to develop 5-year cost effective work programs for various budget scenarios. • Provide a final report outlining the field-testing procedures, network present status results, recommended work programs, and project conclusions and recommendations.
The condition data that was collected was used to identify the Present Status of the road network in terms of four (4) performance indicators:
• Ride Comfort Index (RCI) – Represents the smoothness (ride quality) of the road. • Surface Distress Index (SDI) – Represents the surface condition of the road (cracking, rutting, etc.) • Structural Adequacy Index (SAI) – Represents the structural adequacy of the road. • Pavement Quality Index (PQI) – Overall condition index, a function of the above-noted indices.
Each of the aforementioned indices is presented on a scale of 0-100. A value of 0 represents a pavement section in the worst possible condition, whereas an index value of 100 represents the best possible condition. The SAI ratings are evaluated based on the mid-point of 50. Sections with an SAI ≥ 50 are considered adequate to carry the anticipated traffic loading, including commercial traffic, whereas pavement sections with a calculated SAI < 50 are considered inadequate to carry the anticipat ed traffic loading and will require structural enhancements.
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The results of the 2021 Present Status Analysis, weighted by lane-miles are presented below in Table ES.1 and on the following page in Figure ES.1.
Table ES.1: 2021 Present Status Results – City Maintained Sections Functional
Class
No. of
Sections
Length
(Cl-MI)
Lane Length
(LN-MI) RCI SDI SAI PQI
Arterial 112 23.2 92.4 69 68 88 80
Collector 114 17.0 57.0 63 57 -- 51
Local 1,892 133.2 265.1 60 68 -- 60
All Sections 2,118 173.4 414.5 62 66 88 63
Present Status Results
The following observations can be made based on the present status results:
• The City’s road network is in “Fair” condition in 2021 as noted by the overall network LL-weighted PQI of 63. Similarly, the network is rated as “Fair” for both ride quality (RCI) and pavement surface condition (SDI).
• Arterial sections have a “Satisfactory” overall performance rating and the best performance (LL- weighted PQI of 80) amongst all functional classes.
• The collector roads network LL-weighted PQI of 51 indicates a “Poor” overall condition rating and the worst overall performance amongst all functional classes. • The local roads network LL-weighted PQI of 60 indicates a “Fair” overall performance rating. • The surface distress index (SDI) results indicate that arterials and locals share a similar “Fair” rating as indicated by the LL-weighted SDI of 68. On the other hand, the collector network exhibits a “Poor” surface distress rating as indicated by the LL-weighted SDI of 57. • The ride comfort index (RCI) results indicate that arterials offer the best ride quality (RCI = 69) followed by collectors (RCI = 63) and locals (RCI = 60). All functional classes offer a “Fair” ride quality rating.
• The structural adequacy index (SAI) results indicate that the arterial pavement struct ures (the only functional class that was tested for structural adequacy) are on average adequate (SAI ≥ 50) to carry the anticipated traffic loading.
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Figure ES.1: 2021 Present Status Map (PQI)
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Budget Analysis Results
A summary of the budget analysis results for the three (3) scenarios that were analyzed as part of this project along with their predicted performance results are presented below in Table ES.2 for the 5-year analysis period from 2022 to 2026.
The summary shows the total cost for each budget scenario over the 5-year analysis period, as well as the predicted network lane-length weighted PQI (LL-PQI) and network lane-length lane-length-weighted deficiency percentage (LL-Def.) in 2022 and 2026. Deficiency is the percentage of road mileage with a PQI less than the minimum acceptable level. These minimum acceptable levels (PQI Min) are customizable and have been set in the City’s RoadMatrix database as follows: PQI = 60 for Arterial roads.
A PQI = 55 for Collector roads and a PQI of 50 for Local roads.
Table ES.2: Budget Analysis Results 2022 – 2026 – City Maintained Sections Analysis
Scenario
Annual
Spending
Total Cost Over 5 years
(Avg. Annual Spending)
LL-PQI1 LL-Def.2 (%)
2022 2026 2022 2026
Scenario 1
($2.5M/Year)
$2.45M in 2022
$2.35M in 2023
$4.47M in 2024
$2.67M in 2025
$2.51M in 2026
$ 14,443,035
($2.9M/Year) 64 63 34 40
Scenario 2
($3.5M/Year)
$2.45M in 2022
$3.36M in 2023
$5.47M in 2024
$3.64M in 2025
$3.52M in 2026
$18,437,030
($3.7M/Year) 64 70 34 30
Scenario 3
($4.5M/Year)
$2.45M in 2022
$4.33M in 2023
$6.47M in 2024
$4.63M in 2025
$4.50M in 2026
$22,380,372
($4.5M/Year) 64 78 34 18
1 LL-PQI = Lane-Length weighted PQI
2 LL-Def. = Lane-Length weighted deficiency
The following observations can be made based on the information presented in the table above:
• The “$2.5M/Year” budget results indicates that the overall network predicted PQI will reach 64 by the end of 2022 and will decline by 1 point by the end of 2026. The predicted deficiency will increase from 34 % at the end of 2022 to 40 % in 5 years, by the end of 2026. • The “$3.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 70 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 30 % by the end of 2026.
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• The “$4.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 78 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 18 % by the end of 2026.
RECOMMENDATIONS
The following recommendations are developed based on our understanding of the City’s network condition and current practices:
• It is recommended that the City survey the road network once every 3 years (industry standard), in order to ensure accurate condition data and to validate the benefits of maintenance and rehabilitation (M&R) programs completed by the City.
• It is recommended that the City continues to prioritize preventive maintenance for it is much more cost-effective to keep good roads in good condition as opposed to spending the majority of the available funds on roads that have already deteriorated past the preventive maintenance threshold.
RoadMatrix decision trees have been customized for the City to allow them to do just that - focus on preventive maintenance.
• It is recommended that the City assess the structural capacity of samples of local and collector roads, which have not been included in the 2021 study. This can be done non-destructively using Falling Weight Deflectometer (FWD) equipment. Aside from obtaining the structural adequacy of the pavement and incorporating that into the M&R decision making process, the results from FWD testing include subgrade stiffness and effective structural number (SN eff), which can be used for asphalt
overlay thickness design.
• It is recommended that the City consider validating the layer thickness information for local and collector roads by using either as-built drawings or doing more GPR testing on samples of local and collector roads, which were not included in the 2021 study. GPR is used to determine the layer thickness information non-destructively. It is worth noting that the layer thickness information will need to be determined only once, provided that the City keeps updating the work history annually as needed. Furthermore, layer thickness information, along with traffic levels and subgrade stiffness, is used within RoadMatrix to determine the rate of pavement performance deterioration. This allows for the prediction of pavement performance over time, which in turn affects the selection and planning of short and long term projects.
• Traffic data, as mentioned above, is one of the elements that help determine the performance deterioration rate. It is recommended that the City continue to validate traffic data, including % commercial traffic, and update as needed.
• M&R treatment unit costs should be validated on an annual basis and updated as needed to reflect any changes to the unit costs. Unit cost information is used within RoadMatrix to determine the work programs based on available funding.
• Treatment inflation rates, found under the RoadMatrix Analysis module, should be reviewed and updated, if needed, to reflect anticipated future increases in treatment unit costs. The % Inflation is currently set to 2.0 % for all treatment types. RoadMatrix allows for individual treatments to have their own inflation rates, if needed. Similarly, the Discount Rate, also found in the Analysis module, should 301
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be reviewed as well. The Discount Rate, currently set to 1.0 %, is used in the calculations of cost effectiveness (CE) based on first year equivalent present value. • Pavement management analysis is a network-level analysis that optimizes spending over the entire road network. It is therefore important that recommended treatments are field-verified before implementation to ensure suitability and to consider project-specific conditions, if applicable. 302
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1.0 PROJECT OVERVIEW
1.1 BACKGROUND
The City of Eastvale is located in northwestern Riverside County, California. The City is committed to fund infrastructure sustainability to improve the quality of life and economic development for its community.
The City is responsible for the administration of a roadway network of approximately 173 centerline- miles (CL-MI) or 415 lane-miles (LN-MI). This network forms a valuable asset to be managed in a cost-effective manner. Providing a desirable level of service to the stakeholders is also important.
Through a competitive bidding process, the City selected Stantec Consulting Services Inc. (Stantec) in 2021 to collect pavement condition data on the City’s road network and to implement Stantec’s RoadMatrix Pavement Management System (PMS). This report was prepared based on the 2021 data collection effort. A key component of an effective pavement management system is to regularly assess the condition of the road network, which can then be used to assess the performance of the network over time.
1.2 PROJECT SCOPE AND OBJECTIVES
The project scope for 2021 included the following main tasks:
• Semi-automated Pavement surface distress and roughness survey on approximately 173 survey - miles of the City’s paved road network, excluding private roads. • Structural testing using Falling Weight Deflectometer (FWD) equipment (Arterial Only). • Ground Penetrating Radar (GPR) survey to determine layer thickness information (Arterials Only). • RoadMatrix PMS Implementation including the RoadMatrix-ArcGIS Add-in. • Decision Trees development workshop, one-day onsite.
• Pavement Width Measurements from Satellite images.
• RoadMatrix training, 2-days onsite.
• A final report outlining the field-testing procedures, network present status results, recommended work programs, a list of any untested road sections with the associated reasons, and project conclusions and recommendations.
The condition data that was collected was used to identify the Present Status of the road network in terms of three performance indicators:
• Ride Comfort Index (RCI) – Represents the smoothness (bumpiness) of the road. • Surface Distress Index (SDI) – Represents the surface condition of the road (cracking, rutting, etc.) • Structural Adequacy Index (SAI) – Represents the structural integrity of the pavement structure. • Pavement Quality Index (PQI) – Overall condition index, a function of the above-noted indices.
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Each of the aforementioned indices is presented on a scale of 0-100. A value of 0 represents a pavement section in the worst possible condition, whereas an index value of 100 represents a pavement section in the best possible condition. The SAI ratings are evaluated based on the mid-point of 50. Sections with an SAI ≥ 50 are considered adequate to carry the anticipated traffic loading, including commercial traffic, whereas pavement sections with a calculated SAI < 50 are considered inadequate to carry the anticipated traffic loading and will require structural enhancements.
The significance of each of these indices is discussed further below under Section 3.1.
1.3 REPORT ORGANIZATION
This report is made up of the following seven (7) sections:
• Section 1.0 provides an introduction and overview of the project scope and objectives. • Section 2.0 summarizes the data collection efforts completed as part of this project. • Pavement performance models are described in Section 3.0. • Section 4.0 provides a summary of any parametric updates that were completed. • RoadMatrix analysis results are presented in Section 5.0. • Conclusions are provided in Section 6.0.
• Recommendations are provided in Section 7.0.
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2.0 DATA COLLECTION
2.1 2021 FIELD SURVEY SCOPE
The 2021 field survey scope consisted of the following:
• Roughness and pavement surface distresses on approximately 173 centerline-miles (209 survey miles) of paved roads. Condition data was collected between 3/24/2021 and 3/30/2021. • Structural testing using FWD was completed on Arterial roads (approximately 23 centerline miles) between 3/28/2021 and 3/31/2021. A total of 708 tests were completed and loaded into the City’s RoadMatrix database.
• GPR testing was completed on Arterial roads on 3/26/2021. Approximately 23 centerline miles were surveyed, and the corresponding layer thickness information was loaded into the City’s RoadMatrix database.
2.2 DATA COLLECTION METHODOLOGY
A Stantec RT-3000 unit equipped with accelerometers, laser sensors, cameras, and inertial global position system (IGPS) was used to conduct the 2021 pavement condition survey for surface distress and roughness. The following subsections summarize the data collection methodologies.
The survey was generally conducted in the outer-most lane of each road segment, with the direction of travel referenced in the observed data, through lane codes: “P” lanes indicate the direction defined in the network definition was followed during the survey; whereas the “M” lanes indicate the survey was conducted in the opposite direction of the network definition limits. Road sections with four or more traffic lanes, and/or divided road sections, if any, were tested in both directions of travel. The RT-3000 unit was operated at a minimum speed of 15 mph to ensure reliable profile data was being collected.
2.2.1 Roughness Data Collection
The roughness (ride quality) of each section was measured using a specialized profile measurement system, mounted on the front bumper of the RT-3000 vehicle. The system in the front bumper is equipped with accelerometers and laser sensors which were used to measure the longitudinal profile of the pavement surface in each wheel path of the survey travel lane. The profile data was then used to calculate an International Roughness Index (IRI), in units of inches/mile, summarized at 100-ft intervals.
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The profiler is certified according to ASTM E950 as a Class I profilometer. The collection of longitudinal profile of roughness data is fully automated. The specialized profile measurement system employs two sensing devices:
1. Laser height sensors that measure the distance between the vehicle and the pavement surface, while the vehicle is traveling at up to posted speed limits; and
2. An accelerometer that measures the vertical acceleration of the vehicle as it bounces in response to the pavement surface profile.
These two measurements are combined during post-processing, to eliminate the effects of vertical vehicle motion, and thereby define the vertical profile of the pavement surface. The RT-3000 is also equipped with a distance measurement instrument (DMI) to provide a reference measurement of the vehicle as it traverses the road. This measurement provides stationing references for the profile data.
The IRI measurements obtained from the RT-3000 system have been correlated with those obtained from other valid profilometers, as well as IRI-calculated values from rod and level, and dipstick surveys.
The IRI data is further converted into a Ride Comfort Index (RCI) within the City’s RoadMatrix pavement management system (PMS) for each road section.
2.2.2 Surface Distress Data Collection
Pavement surface condition is evaluated based on the type, severity, and extent of pavement surface distresses. Each surface distress is evaluated based on two components:
• Severity: defined as ‘How bad is the defect?’ and is
expressed in terms of the width or degree of wear
associated with a particular pavement condition. An
example of a severity measurement includes the opening
width of a crack.
• Extent: or ‘How much is there?’ is expressed in terms of the quantity of the surface that a particular defect or distress covers. Examples of measures used for extent would include the number and length of transverse cracks, length of longitudinal cracking, or the pavement area affected by an alligator cracking.
The data collection used for this assignment uses the following RT-3000 sub-systems:
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2.2.2.1 Laser Crack Measuring System (LCMS)
All physical pavement cracks were collected utilizing our RT-3000’s Laser Crack Measuring systems (LCMS) and downward imaging technology.
Stantec’s LCMS uses laser line projectors, high speed cameras, and advanced optics, to acquire high resolution 3D profiles of the road. This unique 3D vision technology allows for automatic pavement condition assessments of asphalt, porous asphalt, chip seal, and concrete surfaces.
The LCMS acquires both 3D and 2D image data of the road surface with 1mm resolution, over a 13-foot lane width, at survey speeds up to 60 mph. This data collection technique does not impact road users as the vehicle travels at posted speeds.
The pavement imagery captured by the RT-3000 is subsequently post- processed through Stantec’s Imaging Workstation. This system was specifically designed for pavement surface analysis, using both the 3D and 2D pavement imagery components of the LCMS, as well as the collected ROW images. The Imaging Workstation expedites the distress rating process with built-in tools and synchronized images, from multiple cameras. The software is used to detect and analyze cracks, lane markings, ruts, macro-texture, patches, raveling, and potholes. As a result, each distress is measured , not estimated, and tagged with a linear reference and corresponding GPS coordinates. The distress data is collected continuously and summarized at 100-foot intervals.
Trained technicians categorized, rated, and measured all pavement distress information from the linescan imagery captured in the driven pavement lane. Each distress is tagged with a linear reference and corresponding GPS coordinates. The distress data is collected continuously, then processed and summarized at 100-foot intervals.
Thirteen (13) distresses were inventoried as part of the 2021 field distress survey as shown below in Table 2.1. It is worth mentioning that a number of pavement surface deficiencies have been collected visually using a special keyboard inside the vehicle. These deficiencies, e.g., raveling, are proven to be difficult to accurately measure with automated techniques.
Table 2.1: Distress Types - Asphalt
Flexible Pavement Distresses
• Patching
• Rippling & Shoving
• Raveling/Streaking
• Flushing & Bleeding
• Distortion
• Excessive Crown
• Progressive Edge Cracking
• Alligator Cracking
• Potholes
• Block/Map Cracking
• Longitudinal Cracking
• Transverse Cracking
• Wheel Track Rutting
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2.2.3 Laser - Transverse Profile / Rutting Data Collection Rutting data is simultaneously collected along with surface distress and roughness data. The RT-3000 measures transverse profile and rut depths, using a minimum of five high-precision, laser-based height-measuring sensors. The two lasers on either end of the rut bar are angled, to provide a full width transverse profile across the traveled lane. From the laser measurements, the average rut depths are computed for each wheel path for upload to RoadMatrix. Calculations of rut depth simulate the straight edge method and are made in accordance with ASTME E
1703E/1703M-95 “Standard Test Method for Measuring Rut Depth of Pavement Surface Using a Straightedge”.
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3.0 ROADMATRIX ANALYSIS MODELS
3.1 PAVEMENT PERFORMANCE INDICES
3.1.1 Roughness – Ride Comfort Index (RCI)
One of the primary operating characteristics of a road, from the user’s perspective, is the rideability, or the Ride Comfort Index (RCI). The RCI represents the traveling public’s opinion of the pavement’s smoothness and, hence, the quality of service it provides. Rating panels composed of drivers/citizens were used at the onset of the initial implementation of pavement management systems 30+ years ago, to calibrate the public’s perspective of ride quality against the roughness measurements obtained from a profiler. The RT-3000 unit was used to determine the longitudinal profile of the pavement surface, reported as an IRI value (inches/mile).
The RCI Analysis within RoadMatrix is used to calculate the sectional RCI from IRI measurements that were collected in the field.
The RCI value for each section ranges from zero (0) to 100, where 100 is indicative of an extremely smooth pavement and an index of zero is indicative of an extremely rough/bumpy pavement.
3.1.2 Surface Distress – Surface Distress Index (SDI)
The Surface Distress Index (SDI) is a performance measure of the physical pavement surface cracking, deformations, and surface defects, collectively referred to as surface distresses. SDI provides an excellent indicator of material deficiency, rate of deterioration, structural adequacy, environment, and subgrade-related issues. The SDI is, therefore, a key indicator of pavement performance. The SDI is assessed by identifying and rating the type, severity, and extent of the 13 surface distresses listed above in Table 2.1 at 100-ft intervals. The SDI ratings for each station were then combined into sectional SDI values ranging from zero (0) to 100.
An SDI index of 100 indicates a pavement surface in the best possible condition, whereas an index of zero (0) indicates a pavement surface in the worst possible condition.
3.1.3 Structural Adequacy Index (SAI)
The Structural Adequacy Index (SAI) is a performance measure of the pavement structural adequacy to withstand the anticipated traffic loading. SAI is calculated from the pavement deflections measured using the Falling Weight Deflectometer (FWD), as well as the traffic loading represented by the Average Annual Daily Traffic (AADT) and the percentage of commercial traffic.
An SAI index that is equal or larger than 50 indicates a pavement structure that is adequate to withstand the traffic loading. An SAI value that is smaller than 50 indicates a pavement structure that is inadequate to withstand the anticipated traffic loading.
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3.1.4 Pavement Quality Index (PQI)
Pavement Quality Index (PQI) is an overall performance index for the pavement section and is a function of the sectional RCI, SDI and SAI values. The SAI (Structural Adequacy Index) was only evaluated for Arterial roads as per the agreement with the City. An SAI value of 50 was assumed for all collector and local road sections with null SAI values.
Two different RoadMatrix default PQI models were implemented for the City’s performance analysis:
PQI = f (SDI, RCI, SAI); where SDI has the highest weight in the calculation of PQI PQI = f (RCI, SDI, SAI); where RCI has the highest weight in the calculation of PQI The first model was used to calculate PQI for all collector and local sections since the surface condition is more critical on these slower roadways.
The second model was used to calculate PQI for all arterial roads since ride quality is more pronounced on roads with higher posted speeds.
3.2 PAVEMENT DETERIORATION MODELS
3.2.1 Deterioration Curves
The PQI/RCI/SDI/SAI values of a pavement typically decrease over time. In order to estimate future rehabilitation requirements of a pavement network, it is necessary to model the deterioration of PQI/RCI/SDI/SAI values. While the rate of deterioration depends on multiple factors, it can be demonstrated that the principal factors are the traffic loading conditions, the properties and thickness of the pavement structure layers, and the stiffness of the underlying subgrade. The factors used to model pavement performance within the RoadMatrix PMS are:
• Structure: expressed in Equivalent Granular Thickness (EGT) - 3 levels (thin, medium, thick) • Traffic: AADT - 3 levels (low, medium, high)
• Subgrade: Subgrade strength - 2 levels (weak/fair, strong) A Deterioration Curve is defined for each combination of thickness/subgrade/traffic. There are 18 thickness/subgrade/traffic combination (classes); therefore, there are 18 Deterioration Curves for each Pavement Type.
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3.3 MAINTENANCE AND REHABILITATION ANALYSIS
3.3.1 Needs Assessment Analysis
The Needs Assessment Analysis is used to determine the optimal rehabilitation strategy for each section in the need year, based on PQI trigger and according to its decision tree. The need year is determined by the appropriate deterioration curve, and the PQI trigger level, while the treatment is chosen based on the selected decision tree. A decision tree is defined in RoadMatrix PMS for each combination of pavement type and functional class.
3.3.2 Recommended Treatments Analysis
The Recommended Treatment Analysis determines the optimal rehabilitation strategies and implementation years for each section, according to the selected analysis method and the section’s decision tree.
The optimal rehabilitation strategy is determined using life cycle economic analysis techniques, which involves an assessment of both the effectiveness of each strategy (area between the After-Rehabilitation performance curve and the Do Nothing performance curve) and an estimate of the capital cost to implement the strategy (refer to Figure 3.1 below). The ratio of treatment benefit to cost produces a cost- effectiveness (CE) number (or more accurately a net benefit/cost number), which allows rehabilitation strategies to be compared to each other on a relative basis. Traffic level is also a factor that is considered in the calculation of the CE factor. The higher the AADT, i.e., more users, the higher the CE factor.
Figure 3.1: Rehabilitation Benefit on Performance Curve
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The economic analysis procedure analyzes each potential rehabilitation strategy recommended by the decision trees (also including committed/overridden strategies) for each section in the current network subset. Each strategy is, in turn, analyzed for each possible implementation year since, due to budgetary or performance constraints, it may not be possible to implement a strategy in the implementation year determined from the decision tree.
It should be noted that the “implementation” need year distribution varies from the traditional / PQI need year distribution, since the selected treatment for any road segment can potentially occur before or after the actual need year. The PQI need year is based on the appropriate performance curve and minimum acceptable PQI level defined for each functional class, while the implementation year is based on the analysis methods and the triggers setup through the decision trees. The implementation year will generally occur prior to PQI reaching the PQI Trigger Value when attempting to incorporate pavement preventive maintenance treatments in the recommended work programs.
3.3.2.1 Maintenance and Rehabilitation (M&R)
The rehabilitation setup within RoadMatrix PMS defines treatment strategies (i.e., maintenance or rehabilitation activities), unit cost of an activity, and the benefit levels (increase/reset/hold values) f or each performance index (RCI/SDI/SAI/EGT) as a result of implementing the treatment. Table 3.1 provides a summary of the maintenance and rehabilitation treatments, costs, and benefits (structural and performance) established in the City’s RoadMatrix database. The City provided updated local unit costs for each of these treatments. The list of treatments was established and finalized as part of the decision trees workshop that was held at City offices.
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Table 3.1: City of Eastvale – 2021 M&R Treatments Summary Code Full Description Category Unit Cost
($/ft2)
Base
Year
EGT
Increase
EGT
Value
Increases Max Value Hold Years
RCI SDI SAI RCI SDI SAI RCI SDI SAI
0 Do Nothing 0.00 2021 85 100 100
5 Crack Seal GM 0.06 2021 5 85 100 100 1
6 PCC Grinding GM 8.54 2021 15 25 85 100 100
10 Patch Full Depth GM 6.70 2021 10 85 85 100 100 1 1 15 Patch 2" GM 6.70 2021 10 85 85 100 100 1 1
20 HDMB PM 6.70 2021 15 35 85 100 100 2 1 1
25 Slurry Seal Type I PM 0.11 2021 4 35 85 100 100 1 1 30 Slurry Seal Type II - Rubberized PM 0.40 2021 4 35 85 100 100 2 2 1 35 Slurry Seal Type II PM 0.25 2021 4 35 85 100 100 1 1 1 40 Microsurface Type II - Rubberized PM 0.45 2021 4 45 85 100 100 2 2 1 45 Microsurface Type II PM 0.28 2021 4 45 85 100 100 1 1 1 50 Cape Seal [Chip 1/4" + Slurry II] PM 0.78 2021 8 50 85 100 100 1 1 1 55 Cape Seal [Chip 1/4" + Micro II] PM 0.81 2021 8 50 85 100 100 1 2 1 60 Hot Chip [Chip 3/8" + 1/2" HMA] PM 1.39 2021 10 100 85 100 100 1 1 1 65 Edge Mill + HMA OL 1.5" RE 0.90 2021 1.5 29 80 5 85 100 100 70 Edge Mill + HMA OL 2.0" RE 1.13 2021 2 38 100 7 85 100 100 75 Edge Mill + RHMA OL 2.0" RE 1.25 2021 2 38 100 7 85 100 100 1 1 1 80 Edge Mill + HMA OL 2.5" RE 1.35 2021 2.5 48 100 8 85 100 100 85 Edge Mill + RHMA OL 2.5" RE 1.50 2021 2.5 48 100 8 85 100 100 1 1 1 90 Full Mill + HMA OL 1.5" RE 0.90 2021 0.8 34 80 2 85 100 100 95 Full Mill + HMA OL 2.0" RE 1.13 2021 1 46 100 3 85 100 100 96 Full Mill + FIBER HMA OL 2.0" RE 1.3 2021 1 46 100 3 85 100 100 1 1 1 100 Full Mill + RHMA OL 2.0" RE 1.25 2021 1 46 100 3 85 100 100 1 1 1 313
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($/ft2)
Base
Year
EGT
Increase
EGT
Value
Increases Max Value Hold Years
RCI SDI SAI RCI SDI SAI RCI SDI SAI
105 Full Mill + HMA OL 2.5" RE 1.35 2021 1.3 57 100 3 85 100 100 110 Full Mill + RHMA OL 2.5" RE 1.50 2021 1.3 57 100 3 85 100 100 1 1 1 111 Full Mill + RHMA OL 4.0" RE 2.25 2021 2 91 100 5 85 100 100 1 1 1 115 HMA OL 1.5" RE 0.68 2021 3 29 86 8 85 100 100
120 HMA OL 2.0" RE 0.90 2021 4 38 100 10 85 100 100
125 Edge Mill + SMA OL 2.0" RE 1.36 2021 2 38 100 8 85 100 100 1 1 130 Edge Mill + SMA OL 2.5" RE 1.63 2021 2.5 48 100 9 85 100 100 1 1 135 Full Mill + SMA OL 2.0" RE 1.36 2021 1 46 100 4 85 100 100 1 1 140 Full Mill + SMA OL 3.0" RE 1.92 2021 1.5 69 100 5 85 100 100 1 1 145 Hot-in-Place Recycle (HIR) RE 0.89 2021 6.5 70 100 60 85 100 100 150 Cold-in-Place Recycle (CIR) RE 0.72 2021 8 70 100 60 85 100 100 155 Full Depth Reclamation (FDR) RE 1.89 2021 18 70 100 70 85 100 100 160 Full Reconstruction LOC - 4" HMA+6" AB CO 4.50 2021 14 85 100 100 85 100 100 165 Full Reconstruction COL - 5" HMA+8" AB CO 5.70 2021 18 85 100 100 85 100 100 170 Full Reconstruction ART - 6" HMA+10" AB CO 7.01 2021 22 85 100 100 85 100 100 175 Full Reconstruction - 9" PCC Slab
Replacement CO 12.10 2021 33 85 100 100 85 100 100
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3.3.2.2 Decision Trees
RoadMatrix uses a decision trees approach to determine technically feasible rehabilitation strategies for each section requiring maintenance or rehabilitation during the programming period. The decision trees are completely user-defined to ensure that they accurately model the decision process employed by the Agency. RoadMatrix allows for a unique decision tree to be developed for each combination of pavement type and functional class. RoadMatrix evaluates the cost-effectiveness (ratio of treatment benefit to cost) to select the most cost-effective treatment and timing.
The decision trees used in this analysis were customized based on the outcome of a full day workshop that was held at the City on June 15, 2022. Factors such as previous rehabilitation type, bus route, truck route, heavy traffic, etc. were all utilized within the trees to generate work programs that are tailored to the local conditions and practices of the City.
The City’s decision trees are illustrated below in Figure 3.2 for “Arterial-Flexible Pavement”, Figure 3.3 for “Collector-Flexible Pavement”, and in Figure 3.4 for “Local-Flexible Pavement”. Simplified decision trees were also created for Portland Cement Concrete (PCC) pavements and can be viewed in the City’s RoadMatrix database.
Figure 3.2: Arterial-Flexible Pavement Decision Tree
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Figure 3.3: Collector-Flexible Pavement Decision Tree
Figure 3.4: Local-Flexible Pavement Decision Tree Budget Analysis 316
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3.4 BUDGET ANALYSIS
3.4.1 Overview
In a perfect world, pavement sections would be maintained and/or rehabilitated whenever required. In other words, the optimal rehabilitation strategy determined by Economic Analysis would be implemented in the “need year”. In the real world, however, budgetary constraints and coordination issues determine the implementation of maintenance and rehabilitation (M&R) strategies. To accommodate this real-world requirement, RoadMatrix offers various budget and performance-based analysis options to prioritize the implementation of M&R strategies in the most cost-effective manner through a virtually unlimited number of user-defined scenarios that users can create.
Below are the several analysis types available within RoadMatrix:
1. Budget Limits – used to define specific budget limits for a given subset.
2. Weighted Deficiency – used to define a network performance target based on deficiency (percentage less than PQI minimum acceptable level) weighted by the area, lane-length, length, vehicle-area, vehicle-lane-length, or vehicle-length of the sections.
3. Weighted PQI – used to define network performance target based on PQI (average PQI from all sections) weighted by the area, lane-length, length, vehicle-area, vehicle-lane-length, or vehicle- length of the sections.
4. Need-Driven (based on PQI Trigger) Rehabilitation Cost – used to determine the rehabilitation costs associated with the network needs and decision tree selections. Depending on the analysis mode used, this scenario will report needs based on either PQI trigger or cost-effective rehabilitation selections.
5. Super-Budget – used to combine the results of more than one budget scenario on different subsets.
For example, assigning specific budgets for specific functional classes.
6. Super-Budget (Dynamic) – used to combine the results of more than one budget scenario for a specific subset. This analysis type is typically used with treatment constraints. For example, assigning specific funding for specific treatment groups (e.g., preventive maintenance program, overlay program, etc.).
The City selected the Budget Limits analysis type (No. 1 in the list above) to generate three 5-year work program scenarios shown in the table below. In addition, a “Do Nothing” scenario was analyzed.
Program Year Scenario 1 Scenario 2 Scenario 3
2022 $750K (Crack Sealing + Slurry Seal + Micro Surfacing) + $1.7M Committed Projects 2023 $2.5M/Year $3.5M/Year $4.5M/Year
2024 $2.5M/Year + $1.94M
Committed Projects
$3.5M/Year + $1.94M
Committed Projects
$4.5M/Year + $1.94M
Committed Projects
2025 $2.5M/Year $3.5M/Year $4.5M/Year
2026 $2.5M/Year $3.5M/Year $4.5M/Year
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3.4.2 Area-Weighted Cost Effectiveness Customized Analysis A customized analysis was conducted based on the City’s request to prioritize work in areas (called Maintenance Areas) with the highest area-weighted cost-effectiveness (CE) factor. The goal is to aggregate the recommended work within certain areas in the City to minimize mobilization costs and potential resident dissatisfaction.
Maintenance areas were selected by the City. A map was provided to Stantec that depicted these maintenance areas. The City was divided into 110 unique maintenance areas. Arterial and Collector roads have been given their own maintenance area identification numbers (numerical values).
Neighborhoods have been further split into smaller maintenance areas where each maintenance area has been given a numerical identifier followed by a letter, e.g. (10-A), where the number 10 is the neighborhood unique identifier, and the letter “A” is the maintenance area within Neighborhood 10.
The maintenance area map is presented below in Figure 3.5.
A 5-year Maintenance and Rehabilitation (M&R) work program was created following the steps below:
• The Needs analysis (unlimited funding) scenario was first run on all sections in the “City Maintained Sections” subset.
• Committed projects take priority and have been included in the program for the noted year. • To determine which maintenance areas should be targeted first in 2022 to consume the remaining funds, the results from the Needs Analysis run were grouped for each maintenance area and were sorted from highest area-weighted CE to lowest. Treatment constraints were created for 2022 to limit the spending of the $750K funds only on crack sealing, slurry seal, and microsurfacing. These maintenance projects were prioritized based on the CE concept explained herein. • Sections needing work from the maintenance area with the highest CE were first added to the program. Sections needing work from the next maintenance area with the highest CE value were then added to the program and the process continued until the designated funds were consumed. • To determine the 2023 work program, a new set of subsets were created for each of the 3 budget scenarios. The sections that were included in the 2022 program year were excluded from the “City Maintained Sections” subset.
• The Needs Analysis scenario was run again on the newly created subset to re-prioritize the maintenance areas again to build the 2023 work program. The same process was followed to prioritize the remaining years’ programs.
It is noted that while the prioritization of the work programs is based on the area- weighted cost effectiveness (CE) approach, this methodology may not necessarily provide the best possible CE scenarios due to the fact that the selections were based on defined areas (maintenance areas) as opposed to being fully triggered by the section needs. On the other hand, this approach may potentially provide savings due to the fact that the work is confined geographically rather than being scattered across the City and thus resulting in higher mobilization costs.
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Figure 3.5: City of Eastvale Pavement Maintenance Areas 319
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4.0 INITIAL DATABASE SETUP
This section presents the RoadMatrix initial database parametric setup and sources of information for documentation purposes.
• The City’s RoadMatrix database was created following the same section definitions provided by the City in the form of a GIS Road Centerline layer. A field called “RM_NO” was added to the shapefile provided by the City to match the unique section identifier in RoadMatrix called “sect_no”. These two fields form the link between the RoadMatrix database and the GIS layer. The linkage is required to use the RoadMatrix ArcGIS Add-in. Minor changes to section definitions and street name correction were also provided by the City along the way.
• Mandatory and optional section attributes were provided by the City on May 3, 2021 using a spreadsheet template provided by Stantec. These include functional class, pavement t ype, number of lanes, divided or not, etc. Except for functional class, the rest of the mentioned information has been verified in the field by the survey crew.
• Curb presence information on both sides of the roads has been picked up by Stantec crew during the survey. For road sections with partial curb presence, the Stantec crew made a decision whether a curb is present or not based on the estimated coverage. • The majority (88.5%) of Traffic data (AADT) was assumed. Traffic % Growth and % Commercial data were assumed.
• Truck and Bus route information was provided by the City on June 22, 2021 in the form of a spreadsheet. School zone information was provided in the same spreadsheet. • Layer thickness information for Arterial roads were measured by Stantec using GPR equipment.
Layer thickness information for collector and local roads were estimated by the City. • Pavement width information was estimated by Stantec as part of this project using satellite imagery that the City provided access to.
• The Maintenance Areas base map was provided by the City on July 21, 2021 and slightly updated by the City on April 12, 2022.
• The M&R Treatments presented above in Table 3.1 were developed as part of the decision trees workshop that was held at the City offices on June 15, 2021. These treatments include treatments that the City currently use as well as new treatments that the City would like to try in the future. • Treatment unit costs were provided by the City on July 19, 2021. • An inflation rate of 2.0% was assumed for all Treatments in this analysis. This rate was reviewed with the City and can be updated when/if needed to reflect the expected rise in treatment unit costs. In addition, RoadMatrix allows for unique inflation rates to be assigned for each individual treatment type, if justified.
• Default performance deterioration curves for the western region were adopted by Stantec.
RoadMatrix allows for customized deterioration curves to be created, if needed.
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• Subgrade soils stiffness, represented by the Subgrade Resilient Modulus (MR), for Arterial roads was back-calculated using data from the FWD deflection testing. Approximately 53 % of the Arterial sections were classified as having a “Strong” subgrade, 38 % were classified as having a “Fair” subgrade stiffness, and 9 % were classified as having a “Weak” Subgrade stiffness. The subgrade soils below Collector and Local roads were all assumed to be “Strong”. It is recommended that this assumption should be validated through field investigation and/or FWD testing.
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5.0 ANALYSIS RESULTS
This section presents the present status of the City of Eastvale’s road network based on the 2021 field survey and the associated budget and predicted performance over the next five (5) years for various analysis scenarios.
5.1 PRESENT STATUS RESULTS
5.1.1 Lane-Length Weighted Performance
This section summarizes the condition of the City of Eastvale road network. A summary of the present status results for 2021 is presented below in Table 5.1.
Table 5.1: 2021 Present Status Analysis Results – City Maintained Sections Functional
Class
No. of
Sections
Length
(Cl-MI)
Lane Length
(LN-MI) RCI SDI SAI PQI
Arterial 112 23.2 92.4 69 68 88 80
Collector 114 17.0 57.0 63 57 -- 51
Local 1,892 133.2 265.1 60 68 -- 60
All Sections 2,118 173.4 414.5 62 66 88 63
The following observations can be made based on the performance results presented in Table 5.1:
• The City’s road network is in “Fair” condition in 2021 as noted by the overall network LL-weighted PQI of 63. Similarly, the network is rated as “Fair” for both ride quality (RCI) and surface condition (SDI). • Arterial sections have a “Satisfactory” overall performance rating and the best performance (LL-weighted PQI of 80) amongst all functional classes. • The collector roads network LL-weighted PQI of 51 indicates a “Poor” overall condition rating and the worst overall performance amongst all functional classes.
• The local roads network LL-weighted PQI of 60 indicates a “Fair” overall performance rating.
• The surface distress index (SDI) results indicate that arterials and locals share a similar “Fair” rating as indicated by the LL-weighted SDI of 68. On the other hand, the collector network exhibits a “Poor” surface distress rating as indicated by the LL-weighted SDI of 57. • The ride comfort index (RCI) results indicate that arterials offer the best ride quality (RCI = 69) followed by collectors (RCI = 63) and locals (RCI = 60). All functional classes offer a “Fair” ride quality rating.
• The structural adequacy index (SAI) results indicate that the arterial pavement structures (the only functional class that was tested for structural adequacy) are on average adequate (SAI ≥ 50) to carry the anticipated traffic loading.
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5.1.2 Ride Comfort Index (RCI)
A chart showing the distribution of RCI values, weighted by lane-length miles, is presented below in Figure 5.1.
Figure 5.1: RCI 2021 Distribution; City Maintained Sections
Table 5.2 below shows the distribution of the network RCI values by condition category.
Table 5.2: RCI Distribution; City Maintained Sections
RCI Ranges Ride Quality # of Sections Length (LN-MI) % of Network RCI ≤ 10 Failed 0 0 0.0
10 < RCI ≤ 25 Serious 18 1.0 0.2
25 < RCI ≤ 40 Very Poor 173 12.9 3.1
40 < RCI ≤ 55 Poor 503 67.6 16.3
55 < RCI ≤ 70 Fair 1182 259.8 62.7
70 < RCI ≤ 85 Satisfactory 236 67.2 16.2
RCI > 85 Good 5 6.0 1.5
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The network RCI results in Table 5.2 above indicate that approximately 13.9 lane miles (3.3 % of the network) exhibit “Very Poor and “Seriously poor” ride quality. There are no network sections with a “Failed” ride quality rating. Approximately 16.3 % of the network exhibit “Poor” ride quality. The majority of the roads (approximately 260 lane miles or 62.7 % of the network) exhibit “Fair” ride quality. There are approximately 73 lane miles that exhibit “Satisfactory” or “Good” ride quality.
The RCI results are presented by the RCI range on a color-coded map in Appendix A.
A summary of the 2021 RCI distribution by functional class results are provided below in Table 5.3. The results by functional class indicate that the Arterial road network has the best average ride quality rating at 69, followed by Collector roads at 63 and finally the Local roads at 60. The results are to be expected considering that roads with more traffic are usually given more attention in terms of M&R work. All functional classes are still rated as “Fair” with regards to ride quality.
The results indicate that the majority of roads in all three functional classes exhibit “Fair” ride quality.
There are no Arterial or Collector roads with any “Failed” or “Seriously Poor” ride quality rat ing.
Approximately 1 lane mile (18 road sections) of Local roads have a “Seriously Poor” ride quality. Over 91 % of the Arterial roads have “Fair” to “Good” ride quality. This is compared to approximately 89 % of the Collector roads and 75 % of the Local roads with “Fair” to “Good” ride quality rating.
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Table 5.3: RCI Distribution; City Maintained Sections – 2021 by Functional Class Functional
Class
LL – Weighted
Average RCI RCI Ranges Ride Quality # of
Sections
Length
(LN-MI)
% of Functional
Class
Arterial 69
RCI ≤ 10 Failed 0 0 0.0
10 < RCI ≤ 25 Serious 0 0 0.0
25 < RCI ≤ 40 Very Poor 1 0.06 0.1
40 < RCI ≤ 55 Poor 11 8.0 8.6
55 < RCI ≤ 70 Fair 60 49.1 53.1
70 < RCI ≤ 85 Satisfactory 34 29.3 31.7
RCI > 85 Good 5 6.0 6.5
Collector 63
RCI ≤ 10 Failed 0 0 0.0
10 < RCI ≤ 25 Serious 0 0 0.0
25 < RCI ≤ 40 Very Poor 1 0.15 0.3
40 < RCI ≤ 55 Poor 19 6.3 11.0
55 < RCI ≤ 70 Fair 74 42.3 74.3
70 < RCI ≤ 85 Satisfactory 20 8.2 14.4
RCI > 85 Good 0 0 0.0
Local 60
RCI ≤ 10 Failed 0 0 0.0
10 < RCI ≤ 25 Serious 18 1.0 0.4
25 < RCI ≤ 40 Very Poor 171 12.7 4.8
40 < RCI ≤ 55 Poor 473 53.3 20.1
55 < RCI ≤ 70 Fair 1,048 168.4 63.5
70 < RCI ≤ 85 Satisfactory 182 29.7 11.2
RCI > 85 Good 0 0 0.0
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5.1.3 Surface Distress Index (SDI)
A chart showing the distribution of SDI values, weighted by lane-length miles, is presented below in Figure 5.2.
Figure 5.2: SDI 2021 Distribution; City Maintained Sections
Table 5.4 below shows the distribution of the network SDI values by condition category.
Table 5.4: SDI Distribution; City Maintained Sections
SDI Ranges Surface Distress # of Sections Length (LN-MI) % of Network SDI ≤ 10 Failed 7 1.7 0.4
10 < SDI ≤ 25 Serious 13 5.7 1.4
25 < SDI ≤ 40 Very Poor 117 32.7 7.9
40 < SDI ≤ 55 Poor 417 93.4 22.5
55 < SDI ≤ 70 Fair 598 106.3 25.6
70 < SDI ≤ 85 Satisfactory 542 90.2 21.8
SDI > 85 Good 423 84.5 20.4
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The network SDI results in Table 5.4 above indicate that there are seven (7) road sections (1.7 lane miles) with a “Failed” pavement surface condition rating. Approximately 38.4 lane miles (9.3 % of the network) exhibit “Very Poor and “Seriously poor” pavement surface condition rating. Approximately 22.5 % of the network exhibit “Poor” pavement surface condition. Approximately 25.6 % of the network (approximately 106.3 lane miles) exhibit “Fair” pavement surface condition and a good portion of the network (42.2 % or 174.7 lane miles) exhibit “Satisfactory” or “Good” pavement surface condition rating.
The SDI results are presented by the SDI range on a color-coded map in Appendix B.
A summary of the 2021 SDI distribution by functional class results are provided below in Table 5.5. The results by functional class indicate that the Arterial and Local Road networks share a similar average pavement surface condition rating index of 68. The Collector network on the other hand has a lower surface condition rating average of 57. All functional classes are still rated as “Fair” with regards to the pavement surface condition rating.
The results of SDI indicate that Arterial roads have the highest percentage of roads (35.9 %) that exhibit a “Good” surface condition rating. On the other hand, the highest percentage of Collector and Local roads (35.1 % and 28.8 %, respectively) exhibit a “Fair” surface condition rating.
There are two (2) Arterial road sections and five (5) Collector road sections that exhibit a “Failed” or “Seriously Poor” pavement surface condition rating. None of the Local roads exhibited a “Failed” surface condition rating and only one (1) Local road section that exhibited a “Seriously Poor” condition rating.
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Table 5.5: SDI Distribution; City Maintained Sections – 2021 by Functional Class Functional
Class
LL – Weighted
Average SDI SDI Ranges Ride Quality # of
Sections
Length
(LN-MI)
% of Functional
Class
Arterial 68
SDI ≤ 10 Failed 2 0.35 0.4
10 < SDI ≤ 25 Serious 7 3.4 3.7
25 < SDI ≤ 40 Very Poor 15 12.9 13.9
40 < SDI ≤ 55 Poor 21 19.1 20.7
55 < SDI ≤ 70 Fair 10 10.0 10.8
70 < SDI ≤ 85 Satisfactory 13 13.5 14.6
SDI > 85 Good 43 33.2 35.9
Collector 57
SDI ≤ 10 Failed 5 1.4 2.5
10 < SDI ≤ 25 Serious 5 2.1 3.7
25 < SDI ≤ 40 Very Poor 9 4.3 7.6
40 < SDI ≤ 55 Poor 32 18.1 31.8
55 < SDI ≤ 70 Fair 36 20.0 35.1
70 < SDI ≤ 85 Satisfactory 17 7.0 12.3
SDI > 85 Good 10 4.0 7.0
Local 68
SDI ≤ 10 Failed 0 0 0.0
10 < SDI ≤ 25 Serious 1 0.15 0.1
25 < SDI ≤ 40 Very Poor 93 15.4 5.8
40 < SDI ≤ 55 Poor 364 56.2 21.2
55 < SDI ≤ 70 Fair 552 76.3 28.8
70 < SDI ≤ 85 Satisfactory 512 69.7 26.3
SDI > 85 Good 370 47.3 17.8
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5.1.4 Pavement Quality Index (PQI)
A chart showing the distribution of PQI values, weighted by lane-length miles, is presented below in Figure 5.3.
Figure 5.3: PQI 2021 Distribution; City Maintained Sections
Table 5.6 below shows the distribution of the network PQI values by condition category.
Table 5.6: PQI Distribution; City Maintained Sections
PQI Ranges Overall Performance # of Sections Length (LN-MI) % of Network PQI ≤ 10 Failed 5 1.4 0.4
10 < PQI ≤ 25 Serious 19 4.3 1.0
25 < PQI ≤ 40 Very Poor 200 36.0 8.7
40 < PQI ≤ 55 Poor 614 108.3 26.1
55 < PQI ≤ 70 Fair 641 111.6 26.9
70 < PQI ≤ 85 Satisfactory 452 93.4 22.5
PQI > 85 Good 186 59.5 14.4
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The network PQI results in Table 5.6 above indicate that there are five (5) road sections (1.4 lane miles) with a “Failed” overall condition rating. Approximately 40.3 lane miles (9.7 % of the network) exhibit “Very Poor and “Seriously poor” overall condition rating. Approximately 26.1 % of the network exhibit “Poor” overall condition rating. Approximately 26.9 % of the network (approximately 111.6 lane miles) exhibit “Fair” pavement surface condition and more than a third of the network (36.9 % or 152.9 lane miles) exhibit “Satisfactory” or “Good” overall condition rating.
The PQI results are presented by the PQI range on a color-coded map in Appendix C.
A list with the 24 road sections that are classified as “Seriously Poor” or “Failed” (approx. 1.4 % of the network) is provided in Appendix D.
A summary of the 2021 PQI distribution by functional class results are provided below in Table 5.7. The results by functional class indicate that the Arterial road network exhibits a “Satisfactory” overall performance rating with an average PQI of 80. The Local road network exhibits a “Fair” overall condition rating with an average PQI of 60. The Collector road network exhibits a “Poor” overall condition rating with an average PQI of 51.
The results indicate that Arterial roads have the highest percentage of roads (42.1 %) that exhibit a “Good” overall condition rating. On the other hand, the highest percentage of Collector roads (42.9 %) exhibit a “Poor” overall condition rating. The highest percentage of Local roads (30.5 %) exhibit a “Fair” overall condition rating.
There are five (5) Collector road sections that exhibit a “Failed” overall condition ra ting, i.e., an average PQI score less than ten (10). None of the Arterial or Local roads exhibited a “Failed” overall condition rating. The “Failed” Collector roads are listed in Appendix D.
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Table 5.7: PQI Distribution; City Maintained Sections – 2021 by Functional Class Functional
Class
LL – Weighted
Average SDI SDI Ranges Ride Quality # of
Sections
Length
(LN-MI)
% of Functional
Class
Arterial 80
PQI ≤ 10 Failed 0 0 0.0
10 < PQI ≤ 25 Serious 2 0.3 0.3
25 < PQI ≤ 40 Very Poor 1 0.1 0.1
40 < PQI ≤ 55 Poor 6 3.4 3.7
55 < PQI ≤ 70 Fair 20 18.0 19.5
70 < PQI ≤ 85 Satisfactory 37 31.7 34.3
PQI > 85 Good 45 38.9 42.1
Collector 51
PQI ≤ 10 Failed 5 1.4 2.5
10 < PQI ≤ 25 Serious 6 2.4 4.2
25 < PQI ≤ 40 Very Poor 17 8.7 15.2
40 < PQI ≤ 55 Poor 40 24.5 42.9
55 < PQI ≤ 70 Fair 28 12.8 22.4
70 < PQI ≤ 85 Satisfactory 14 5.7 10.0
PQI > 85 Good 4 1.6 2.8
Local 60
PQI ≤ 10 Failed 0 0 0.0
10 < PQI ≤ 25 Serious 11 1.6 0.6
25 < PQI ≤ 40 Very Poor 182 27.2 10.3
40 < PQI ≤ 55 Poor 568 80.5 30.4
55 < PQI ≤ 70 Fair 593 80.9 30.5
70 < PQI ≤ 85 Satisfactory 401 56.0 21.1
PQI > 85 Good 137 18.9 7.1
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5.1.5 Structural Adequacy Index (SAI)
A chart showing the distribution of SAI values, weighted by lane-length miles, is presented below in Figure 5.4. The SAI values were calculated only for Arterial roads where FWD deflection testing was completed. An SAI value larger or equal to 50 indicates a road structure that is adequate to carry the anticipated traffic loading. An SAI value of less than 50 indicates a pavement structure that is inadequate to carry the anticipated traffic loading.
Figure 5.4: SAI 2021 Distribution; Arterial Sections
Table 5.8 below shows the distribution of the network SAI values by condition category.
Table 5.8: SAI Distribution; Arterial Sections*
PQI Ranges Overall Performance # of Sections Length (LN-MI) % of Arterial Network SAI < 50 Structurally Inadequate 2 0.4 0.4
SAI ≥ 50 Structurally Adequate 105 90.8 99.6
*There is approximately 1.2 lane miles of Arterial roads that were not tested for FWD because of construction or closures
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The SAI results indicate that almost all Arterial roads that were tested for structural adequacy are actually adequate for the anticipated traffic loading. There are 2 road sections (Milliken Ave NB from Hwy 80 Ramp to Hwy 80 Ramp (685.3 CL feet) and River Rd from Hellman Ave to River Rd Ramp (290 CL feet) that were found to be structurally inadequate to carry the anticipated traffic loading.
5.2 BUDGET ANALYSIS RESULTS
To conduct the performance prediction and M&R program analyses, the City provided Stantec a list of all the M&R work that was completed in 2021 after the survey was completed. This work history was loaded into RoadMatrix and a new analysis was run to determine the 2022-2025 predicted performance. Also as mentioned earlier, the City committed a list of projects in 2022 and in 2024 that were incorporated into the budget and M&R analyses. The following bullets summarize the updates that were completed as part of this budget analysis task:
• The 2022 M&R program includes $750K that can only be spent on Crack Seal, Slurry Seal, and/or Microsurfacing treatments. This applied to all three base budget scenarios: $2.5M/year, $3.5M/Year, and $4.5M/Year.
• The 2022 M&R program includes $1.7M worth of Committed projects for the reconstruction of three (3) sections of ARCHIBALD AVE. This also applied to the three (3) aforementioned scenarios. • The 2024 M&R program includes approximately $1.94M worth of committed proje cts on the following road:” SCHLEISMAN RD, HARRISON AVE, SCHOLAR WAY, CLEVELAND AVE, and ORANGE ST.
These committed projects will have a separate funding source that will not consume the annual funding. Treatments included “Edge Mill + HMA OL 1.5” and Cape Seal.
A summary of the budget analysis results for the three (3) scenarios that were analyzed as part of this project along with their predicted performance results are presented below in Table 5.9 for the 5-year analysis period from 2022 to 2026.
The summary shows the total cost for each budget scenario over the 5-year analysis period, as well as the predicted network lane-length weighted PQI (LL-PQI) and network lane-length lane-length-weighted deficiency percentage (LL-Def.) in 2022 and 2026. Deficiency is the percentage of road mileage with a PQI less than the minimum acceptable level. These minimum acceptable levels (PQI Min) are customizable and have been set in the City’s RoadMatrix database as follows: PQI = 60 for Arterial roads.
A PQI = 55 for Collector roads and a PQI of 50 for Local roads.
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Table 5.9: Budget Analysis Results 2022 – 2026 – City Maintained Sections Analysis
Scenario
Annual
Spending
Total Cost Over 5 years
(Avg. Annual Spending)
LL-PQI1 LL-Def.2 (%)
2022 2026 2022 2026
Scenario 1
($2.5M/Year)
$2.45M in 2022
$2.35M in 2023
$4.47M in 2024
$2.67M in 2025
$2.51M in 2026
$ 14,443,035
($2.9M/Year) 64 63 34 40
Scenario 2
($3.5M/Year)
$2.45M in 2022
$3.36M in 2023
$5.47M in 2024
$3.64M in 2025
$3.52M in 2026
$18,437,030
($3.7M/Year) 64 70 34 30
Scenario 3
($4.5M/Year)
$2.45M in 2022
$4.33M in 2023
$6.47M in 2024
$4.63M in 2025
$4.50M in 2026
$22,380,372
($4.5M/Year) 64 78 34 18
1 LL-PQI = Lane-Length weighted PQI
2 LL-Def. = Lane-Length weighted deficiency
The following observations can be made based on the information presented in the table above:
• The “$2.5M/Year” budget results indicates that the overall network predicted PQI will reach 64 by the end of 2022 and will decline by 1 point by the end of 2026. The predicted deficiency will increase from 34 % at the end of 2022 to 40 % in 5 years, by the end of 2026. • The “$3.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 70 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 30 % by the end of 2026.
• The “$4.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 78 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 18 % by the end of 2026.
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5.2.1 Annual Budget Network Performance Results
The annual prioritization targets/limits in terms of budget or performance, the estimated cost, resulting LL- PQI, and the lane length-weighted deficiency percentage (LL-Def.) are provided below in Table 5.10 through Table 5.12 for each analysis scenario. The costs in the tables are rounded to the nearest $1,000 and PQI and % Deficiency are rounded to the nearest whole number.
Table 5.10: $2.5M/Year (Scenario 1) Budget Scenario Results Year Cost LL-PQI LL-Def %
2022 $ 2,444,000 64 34
2023 $ 2,346,000 63 37
2024 $ 4,469,000 64 34
2025 $ 2,672,000 64 38
2026 $ 2,512,000 63 40
Total $14,443,000.00
Table 5.11: $3.5M/Year (Scenario 2) Budget Scenario Results Year Cost LL-PQI LL-Def %
2022 $ 2,444,000 64 34
2023 $ 3,359,000 64 36
2024 $ 5,471,000 66 32
2025 $ 3,643,000 68 32
2026 $ 3,519,000 70 30
Total $18,436,000.00
Table 5.12: $4.5M/Year (Scenario 3) Budget Scenario Results Year Cost LL-PQI LL-Def %
2022 $ 2,444,000 64 34
2023 $ 4,334,000 65 35
2024 $ 6,467,000 69 29
2025 $ 4,632,000 74 25
2026 $ 4,503,000 78 18
Total $22,380,000.00
The results of the aforementioned analysis scenarios, in terms of both the network lane- length weighted PQI and the network lane-length deficiency percentages are illustrated on the next pages in Figure 5.5 and Figure 5.6, respectively.
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Figure 5.5: Funding Impact on Network Predicted Average PQI
Figure 5.6: Funding Impact on Network Predicted % Deficiency 64 65
69 74
78 64 64
66 68
70 64 63 64 64 63
55 60
65 70
75 80
85 2022 2023 2024 2025 2026
Average PQI (LL)
Program Year
Program Network Performance (PQI)
Multiple Programs
$4.5M/Year (Scenario 3)
$3.5M/Year (Scenario 2)
$2.5M/Year (Scenario 1)
34 35
29 25
18 34
36 32 32
30 34
37 34
38 40
15 20
25 30
35 40
45 50
2022 2023 2024 2025 2026
% Deficiency (LL)
Program Year
Program Network Performance (% Deficiency)
Multiple Programs
$4.5M/Year (Scenario 3)
$3.5M/Year (Scenario 2)
$2.5M/Year (Scenario 1)
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5.2.2 Budget Recommended Rehabilitations
The recommended 5-year work program listing for the three different budgets ($2.5M, $3.5M, $4.5M) are provided in Appendix E for the $2.5M/Year budget, Appendix F for the $3.5M/Year budget, and in Appendix G for the $4.5M/Year budget. A colored map showing the location and the type of recommended treatment is also provided prior to the recommended work list for each year of the program.
Figure 5.7 through Figure 5.9 below illustrate the distribution of the M&R treatments for each analysis scenario, in terms of both the lane length and total cost over the 4-year analysis period. The Figures indicate that “Edge Mill + HMA 1.5” OL” and “Slurry Seal Type II” are the top recommended treatment s in terms of lane-length.
Figure 5.7: $2.5M/Year (Scenario 1) Recommended Rehabilitations by Treatment 337
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Figure 5.8: $3.5M/Year (Scenario 2) Recommended Rehabilitations by Treatment
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Figure 5.9: $4.5M/Year (Scenario 3) Recommended Rehabilitations by Treatment
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6.0 CONCLUSIONS
As part of the 2021 City of Eastvale Pavement Condition Assessment and Pavement Management System implementation project, the entire road network, approximately 173 centerline-miles, was surveyed for roughness and surface distress. In addition, structural testing and GPR testing (to determine layer thickness information) were completed on Arterial roads only. Stantec’s RoadMatrix PMS was implemented for the City as part of this project. All collected condition data were uploaded to RoadMatrix.
Additionally, section attributes were populated based on information collected by Stantec in the field as well as information provided by the City. The following sub-sections provide a summary of this project’s findings.
6.1 PRESENT STATUS
• The City’s road network is in “Fair” condition in 2021 as noted by the overall network LL-weighted PQI of 63. Similarly, the network is rated as “Fair” for both; ride quality (RCI) and pavement surface condition (SDI).
• Arterial sections have a “Satisfactory” overall performance rating and the best performance (LL- weighted PQI of 80) amongst all functional classes.
• The collector roads network LL-weighted PQI of 51 indicates a “Poor” overall condition rating and the worst overall performance amongst all functional classes. • The local roads network LL-weighted PQI of 60 indicates a “Fair” overall performance rating. • The surface distress index (SDI) results indicate that arterials and locals share a similar “Fair” rating as indicated by the LL-weighted SDI of 68. On the other hand, the collector network exhibits a “Poor” surface distress rating as indicated by the LL-weighted SDI of 57. • The ride comfort index (RCI) results indicate that arterials offer the best ride quality (RCI = 69) followed by collectors (RCI = 63) and locals (RCI = 60). All functional classes offer a “Fair” ride quality rating.
• The structural adequacy index (SAI) results indicate that the arterial pavement structures (the only functional class that was tested for structural adequacy) are on average adequate (SAI ≥ 50) to carry the anticipated traffic loading.
6.2 BUDGET ANALYSIS
The following observations can be made based on the budget analysis results:
• The “$2.5M/Year” budget results indicates that the overall network predicted PQI will reach 64 by the end of 2022 and will decline by 1 point by the end of 2026. The predicted deficiency will increase from 34 % at the end of 2022 to 40 % in 5 years, by the end of 2026. • The “$3.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 70 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 30 % by the end of 2026.
• The “$4.5M/Year” budget results indicates that the overall network predicted PQI will increase from 64 at the end of 2022 to 78 by the end of 2026. The predicted deficiency will decrease from 34 % at the end of 2022 to 18 % by the end of 2026.
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7.0 RECOMMENDATIONS
The following recommendations are developed based on our understanding of the City’s network condition and current practices:
• It is recommended that the City survey the road network once every 3 years (industry standard), in order to ensure accurate condition data and to validate the benefits of maintenance and rehabilitation (M&R) programs completed by the City.
• It is recommended that the City continues to prioritize preventive maintenance for it is much more cost-effective to keep good roads in good condition as opposed to spending the majority of the available funds on roads that have already deteriorated past the preventive maintenance threshold.
RoadMatrix decision trees have been customized for the City to allow them to do just that - focus on preventive maintenance.
• It is recommended that the City assess the structural capacity of samples of local and collector roads, which have not been included in the 2021 study. This can be done non-destructively using Falling Weight Deflectometer (FWD) equipment. Aside from obtaining the structural adequacy of the pavement and incorporating that into the M&R decision making process, the results from FWD testing include subgrade stiffness and effective structural number (SN eff), which can be used for asphalt
overlay thickness design.
• It is recommended that the City consider validating the layer thickness information for local and collector roads by using either as-built drawings or doing more GPR testing on samples of local and collector roads, which were not included in the 2021 study. GPR is used to determine the layer thickness information non-destructively. It is worth noting that the layer thickness information will need to be determined only once, provided that the City keeps updating the work history annually as needed. Furthermore, layer thickness information, along with traffic levels and subgrade stiffness, is used within RoadMatrix to determine the rate of pavement performance deterioration. This allows for the prediction of pavement performance over time, which in turn affects the selection and planning of short and long term projects.
• Traffic data, as mentioned above, is one of the elements that help determine the performance deterioration rate. It is recommended that the City continue to validate traffic data, including % commercial traffic, and update as needed.
• M&R treatment unit costs should be validated on an annual basis and updated as needed to reflect any changes to the unit costs. Unit cost information is used within RoadMatrix to determine the work programs based on available funding.
• Treatment inflation rates, found under the RoadMatrix Analysis module, should be reviewed and updated, if needed, to reflect anticipated future increases in treatment unit costs. The % Inflation is currently set to 2.0 % for all treatment types. RoadMatrix allows for individual treatments to have their own inflation rates, if needed. Similarly, the Discount Rate, also found in the Analysis module, should be reviewed as well. The Discount Rate, currently set to 1.0 %, is used in the calculations of cost effectiveness (CE) based on first year equivalent present value. • Pavement management analysis is a network-level analysis that optimizes spending over the entire road network. It is therefore important that recommended treatments are field-verified before implementing to ensure suitability and to consider project specific conditions, if applicable. 341
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APPENDIX A
Ride Comfort Index Map
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