Why the "Worst First" Approach to Road Maintenance isn't Always the Best

Posted: August 30, 2017
Tagged As: Asset Management, Municipal Infrastructure, Roads Assessment

The 2016 Canadian Infrastructure Report Card indicates that over 37% of Canadian roads are in fair to very poor condition. The total replacement value of all those road assets amount to over $123 Billion. In Ontario alone, the province faces a $30B road investment gap over the next 10 years. Municipalities today are challenged with aging infrastructure leading to an increase in operational cost, yet municipal budgets face more and more pressure due to fiscal shortfalls. The Smart City of today must make well-informed data driven decisions in order to ensure capital and operating budgets are allocated appropriately.
 
In 2016, the University of Waterloo, in partnership with industry experts, undertook a Canada-wide study of municipal road maintenance practices.  This study surveyed 171 participants across the country representing approximately 45,000km of paved road and 15% of Canada’s population.  The study established that 98% of respondents see preventative maintenance (PM) as an important and cost-effective approach to servicing asphalt, yet they do not apply PM treatments properly, and their understanding of when these treatments should be applied widely varies.  In fact, the study found that less than 20% of municipal road networks are actually being maintained in accordance to the best practices identified by respondents. 
 
When it comes to road networks, many municipalities today adopt the “Worst Roads First” approach.  Maintenance is often performed on a reactive basis and does not take into account the lifespan of the asset, amounting to poor fiscal policy. Fixing the worst roads first often means rebuilding because at that point, the asset has reached its end of life. This option also carries the highest cost. Maintenance on the other roads is subsequently delayed and their conditions worsen over that same period.  This leads to a spiral effect on the roads network and deteriorating levels of service over time.  Municipalities dig themselves into a deeper financial hole using the “Worst First” Strategy as each year, more kilometers of roads are added to the list of “worst” that need rebuilding. Incorporating preventative maintenance strategies into the decision making process reduces overall long-term operating costs and increase the average pavement condition index (PCI) rating of the municipality over time.  It is estimated that spending $1 on preventive maintenance at the correct time will extend the road life and could eliminate spending $8-$10 on rehabilitation in the future.

Pavement Condition Index vs. Repair Cost Over Time Graph
 
Pavement Management can be defined as a systematic decision making process to maintain the road infrastructure in a cost effective manner. This is achieved by regularly collecting objective road condition data on the entire road network, which is then analyzed to evaluate repair or preservation strategies and suggest cost effective solutions to maintain road conditions.  An engineering study which follows best practices will take into account the road’s deterioration model, along with a municipality’s fluctuating annual capital budgets, shifting objectives, minimum levels of service, services access, and safety considerations.  Effective roads maintenance planning must incorporate both the short-term needs and the long term goals of the municipality.
 
Being able to predict when a pavement needs to be repaired before the pavement fails is an integral part of any successful Pavement Management System. Pavement infrastructure deterioration is an aggregated impact from traffic loading, environmental condition, and pavement structural integrity. The behavior of a pavement under these factors depends on the characteristics of its structure (materials and thickness of each pavement layer) and subgrade (bearing capacity and presence of water). Each factor causes certain distresses on the pavement. Prediction of pavement deterioration influences the quality of many Pavement Management components such as planning long-term cost-effective maintenance activities.
 
Utilizing StreetScan’s web-based Pavement Management software (PaveMON), Ontario municipalities now have access to a robust, customizable decision tree that instantly calculates funding strategies in a GIS environment. Responsible repair & preservation strategies take into consideration traffic volumes, cost benefit ratio, condition of the road, local deterioration models & customizable inputs such as planned water main/sewer projects and school zones. The end result is proactive decision-making instead of a costly reactive repair.
 
PaveMON evaluates different strategies over the life cycle of pavements to minimize the overall cost for
 municipalities. For example, in City of Newton, MA, PaveMON evaluated the following strategies:
  1. Strategy 1: Allocating 15-20% each year to preventive repairs, rest to rehabilitation and reconstruction.
  2. Strategy 2: Allocating 15-20% each year to rehabilitation repairs, rest to reconstruction.
  3. Strategy 3: Only doing reconstruction and applying the ‘worst-first’ approach.
Graph Showing Cost Comparison for Different Repair StrategiesPaveMON revealed that by not performing preventive repairs, the city would end up paying 6 times more per square yard of their roads, an amount that would add up to millions of dollars in saving by following PaveMON’s maintenance strategies.
 
As you work on your roads budgets for the coming year, consider how you might stretch your dollar to best align with your future plans.
 
About the Authors
StreetScan’s current core business is an end-to-end pavement inspection and management service to the public sector that is fast, objective, efficient, and affordable, to be used city-wide on a frequent basis, ensuring that repair decisions are based on up-to-date and complete data. 
 
Ralf Birken, Ph.D.– CEO & Co-Founder– Dr. Ralf Birken is a near-surface geophysicist and founder of StreetScan Inc.  He was a Research Assistant Professor of Civil and Environmental Engineering at Northeastern University from 2009 until the summer of 2015.  Dr. Birken received his Ph.D. in Geophysical and Geological Engineering from the University of Arizona in 1997 and a MS in Geophysics from the University of Cologne, Germany in 1992. In 2000, he completed a Post-Doc with the Lamont-Doherty Earth Observatory of Columbia University.  He has over 18 years of research and engineering experience in industry and academia in near-surface geophysical mapping, designing new measurement systems, dealing with Big Data sets, and sensor technology mainly for civil infrastructure health monitoring applications.
 
Salar (Sal) Shahini Shamsabadi – Data Scientist & GIS Developer – As a Data Scientist & GIS Developer at StreetScan, Sal works on integrating and leveraging information from large geospatial datasets for developing pavement management, sensor fusion & life-cycle cost analysis models. He received his B.S. in Geomatics Engineering from the University of Tehran in 2012 & his M.S. in Civil Engineering in 2014 from Northeastern University where he developed StreetScan’s GIS web application for pavement monitoring & management.

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