California Department of Transportation

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Pavement Management

Office of Pavement Management

2389 Gateway Oaks Drive, Suite 200
Sacramento, CA 95833

The primary functions of the Office of Pavement Management are to:

  • Manage, operate, develop, and maintain the Caltrans’ Pavement Management System (PaveM)
  • Collect, analyze, and manage automated pavement condition survey (APCS) data
  • Develop and publish the State of the Pavement report (SOP)
  • Update and maintain statewide approved program (SAP) and pavement project as-built data

PaveM utilizes pavement history, current pavement condition, SAP, traffic, and climate data to predict future pavement conditions and recommend pavement repair needs using the right strategy at the right time with optimized funding and effectiveness.

APCS data is a critical input for PaveM to determine pavement condition, predict pavement performance, and identify future pavement improvement needs.  APCS data is collected at highway speeds using specialized vehicles with inertial profilers, transverse laser systems, and high resolution cameras.  All lanes of the entire state highway system (SHS) are collected and analyzed following the Caltrans linear referencing system.  APCS data is collected annually in compliance with the Moving Ahead for Progress in the 21st Century Act (MAP-21). 

Starting in 2016, SOP reports pavement condition statewide and by districts based on the latest pavement condition information from PaveM.  Past SOPs, based on manual pavement condition surveys, can be accessed below:

2016 (being developed)

SOP Archive

2015 2013 2011 2007 2005 2004 2003 2002

1999 1997 1995 1992 1990 1988 1986

SAP and Pavement Project As-Built Data

SAP contains hard-wired projects from all Caltrans’ districts for scenario analyses using the most recent pavement condition data in PaveM.  Pavement project as-built data currently includes more than 18,000 records from 1968 to present and is being continually updated and uploaded into PaveM.  This data is used to track pavement condition and improve pavement performance prediction models in PaveM.


Last updated 10/4/2017.