Standard Practice for Computing Ride Number of Roads from Longitudinal Profile Measurements Made by an Inertial Profile Measuring Device
由惯性剖面测量装置进行的纵向剖面测量计算道路行驶次数的标准实施规程
1.1
This practice covers the mathematical processing of longitudinal profile measurements to produce an estimate of subjective ride quality, termed Ride Number (RN).
1.2
The intent of this practice is to provide the highway community a standard practice for the computing and reporting of an estimate of subjective ride quality for highway pavements.
1.3
This practice is based on an algorithm developed in National Cooperative Highway Research Project (NCHRP) 1–23
(
1
,
2
)
,
2
two Ohio Department of Transportation ride quality research projects
(
3
,
4
)
, and work presented in Refs
(
5
,
6
)
.
1.4
The computed estimate of subjective ride quality produced by this practice was named Ride Number (RN) in NCHRP Research Project 1–23
(
1
,
2
)
to differentiate it from other measures of ride quality computed from longitudinal profile.
Eq 1
of
8.2
represents the mathematical definition of Ride Number.
1.5
This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.
1.6
This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
====== Significance And Use ======
5.1
This practice provides a means for obtaining a quantitative estimate of a pavement property defined as ride quality or rideability using longitudinal profile measuring equipment.
5.1.1
The Ride Number (RN) is portable because it can be obtained from longitudinal profiles obtained with a variety of instruments.
5.1.2
The RN is stable with time because true RN is based on the concept of a true longitudinal profile, rather than the physical properties of particular type of instrument.
5.2
Ride quality information is a useful input to the pavement manage systems (PMS) maintained by transportation agencies.
5.2.1
The subjective ride quality estimate produced by this practice has been determined
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6
)
to be highly correlated (r = 0.92) with measured subjective ride quality and to produce a low standard estimate of error (0.29 RN units) for the ride quality estimate.
5.2.2
The subjective ride quality estimates produced by this practice were found to be not significantly different with respect to pavement type, road class, vehicle size, vehicle speed (within posted speed limits), and regionality over the range of variables included in the experiment
(
1-
4
)
.
5.2.3
The subjective ride quality estimates produced by this practice have been found to be good predictors of the need of non-routine road maintenance for the various road classifications
(
3
)
.
5.3
The use of this practice to produce subjective ride quality estimates from measured longitudinal profile eliminates the need for expensive ride panel studies to obtain the same ride quality information.