California LTAP Center: Longitudinal Rumble Strips and Stripes on Two-Lane Roads
24 تشرين الأول (أكتوبر) أو تقنيةُ (حيلة) القطاع/ الشريط الطرقيّ المسبّب للضجيج. والأولى أفضل. Rumble device: a device designed to alert drivers by giving a vibratory. Rumble strips, also known as sleeper lines, alert strips, audible lines, sleepy bumps, wake up Shoulder and centerline rumble strips are used to reduce lane departure when conventional markings on flat surfaces can be difficult to see. .. not as a speed control measure but as a driver's attention-catching device.". Rumble strips, raised profile line markings or audio tactile profiled (ATP) road on wet nights when normal road markings can become extremely difficult to see.
Eventually, a width will be reached at which widening the median further cannot be justified because the improvement in safety is too small. Installing rumble strips on a highway with a high accident rate close to 27 should yield a relatively high accident reduction. This assumes that the road shoulder is adequate for a recovery, once a straying driver has been alerted by the rumble strips.
Types of rumble strips[ edit ] Continuous shoulder rumble strips CSRS [ edit ] Montana undertook an extensive year multi-site study of the effectiveness of CSRS on Interstate and primary highways both types are divided pavements. This study also investigated the severity of crashes, which sets it apart from previous studies.
It was found that "roll-overs" decreased in number, but increased in severity. The study only considered crashes in dry and wet conditions, not snow and ice.
The Illinois component indicated crash reduction from 7. The California component indicated crash reductions of 7. Centre-line rumble strips showed similar effects. However, it appears that there were other crash reduction initiatives that may have contributed to the relatively sizable results.
Apart from the safety benefits of providing a consistent road environment, continuous markings provide valuable alerts to drivers long before the more common crash spots. It includes the New York State Thruway and Pennsylvania Turnpike results which produced a skewed result non-representative of typical situations.
The collision reduction attributed to the installation of CSRS is mainly a function of stable shoulder width, crash rate and profile, climate and diminishing marginal returns.
Centerline rumble strips CRS [ edit ] Centerline Rumble Strips are applied to single-lane undivided highways to help prevent head-on collisions. When present, these are often milled into the pavement. However, this study did not investigate changes in crash severity, as did the Montana study. Ice and slush filled rumble strips can be a concern, particularly so for milled centerline rumble strips.
For this reason, some jurisdictions are reluctant to install them. These are typically a raised reflective system. Transverse rumble strips[ edit ] Transverse rumble strips TRS may be used to warn drivers: A Texas study concluded: There have been no studies that evaluate the reduction of excessive speeds.
The Texas indicated: The effectiveness of CSRS on the lower-standard primary highways that are also divided has not been given the same consideration as those on Interstate highways.
The Montana study suggested that CSRS on primary highways can result in either worsening or improvement of crash rates. This may be due to variation in recovery zone width and condition, and other factors. The study also stated that unprevented crash severity may worsen, and the overall results were inconclusive. The study suggested that the differences in rumble strip-related crashes between Interstate highways and primary highways were due to the primaries having smaller shoulders than Interstates.
The most serious problem would be an increase in crash severity. Also, there is the concern of drivers sometimes overreacting and crossing the centerline, resulting in a head-on collision. It appears that there may be no published before-and-after CSRS studies for single-lane highways.
In certain situations, such as an engaging single-lane highways that typically have narrow shoulders, high precipitation, in a northern climate with frequent freeze-thaw cycles, rumble strip effectiveness may be negative.
This may be due to the initial installations were on highways that had been identified as having very high accident rates due to inattention. Also, there may have been other accident reduction campaigns in concert with rumble strip programs. Shoulder road Research has found that on rural freeways, rumble strips are much more effective when placed at or near the edgeline than when placed closer to the shoulder edge.
Edgeline rumble strips can be expected to reduce crashes by On two-lane roads, there is little difference in effectiveness between edgeline and non-edgeline rumble strips, with crash reduction factors of Sometimes, the paved and gravel shoulders are combined as the "recovery zone" beyond the rumble strip. However, if the gravel is loose, soft, non-level, eroded, or there is an "edge-drop" from the pavement to the gravel, then the gravel shoulder portion will be ineffective for recovery, especially at highway speeds.
When a vehicle's tires sink into a soft shoulder, thus compromising vehicle handling, it is known as "vehicle tripping". Climate[ edit ] Traction sand filled shoulder rumble strip. The sand is "cemented" in-place and is not easily removed by truck traffic. Climate is another factor that affects the success of a rumble strips installation.
If they are installed in a northern climate, they may be filled or partially filled with a deicing salt and traction sand mixture.
They may also be filled with ice. This is a particular concern in regions with freeze-thaw cycles requiring frequent deicing.
What is a rumble device designed to
Furthermore, strips filled with water, snow, slush, and ice may cause or aggravate occasional accidents. Generally, air turbulence and vibration from passing large trucks keep rumble strips clear of debris and ice, but this process may take several days.
This is problematic on low-volume highways with frequent deicing, and can significantly reduce the effectiveness of rumble strips in winter months. When rumble strips are installed on a very narrow paved shoulder, sometimes sand and gravel can fill the rumble strip which is usually a problem in the winter and early spring.
If the snow-cover is substantial, then the shoulder including the rumble strip is usually partially snow-covered as the snowplow's wing-blade doesn't clear the entire shoulder. Vehicles going off the road usually collide with the shoulder snow bank or go into a snow-filled ditch which reduces the possibility of serious damage and injury. In these situations, the rumble strip effectiveness can be negated but the crash implications are mitigated by the snow bank.
Pavement deterioration[ edit ] An example of extensive cracking in rumble strips due to frost jacking on Interstate Highway 81 north of Syracuse.
These parallel cracks were sealed. There were other sections with grass and weeds growing up through the rumble strip cracks Generally, deterioration of the shoulder asphalt pavement due to rumble strip installation is not a problem. However, if the sub-grade under the CSRS is poorly compacted or has poor drainage characteristics; or the gravel shoulder has eroded, crack s may form in the CSRS.
Sand tends to fall into these cracks resulting in "jacking" of the cracks. Water percolates vertically down through the soil, but it also creeps horizontally under the paved shoulder. This may be a particular problem with narrow paved shoulders in regions with frequent freeze-thaw cycles that may result in frequent frost-heaving of the paved shoulder.
It is also recommended that rumble strips be inspected in summer months for cracking, potholing, water ponding, and snowplow damage. If necessary, structural problems should be repaired. The centerline of highway has a pavement joint and if milled CLRS are installed over this joint they will make pavement more vulnerable to deterioration.
Truckers have reported deterioration of the joint and the CLRS. Inthe town of Chapel HillNorth Carolinahad transverse rumble strips removed as the measured noise from nighttime traffic on the rumble strips exceeded the Town's Noise Ordinance. Sound level data were collected using the data acquisition system described above. Chen 48 collected sound level data using a 5 degree angle of departure, while Mak and Sick- ing 96 indicate that highest run-off-road encroachment angle probabilities are 7.
The roadway departure angles collected during experimentation ranged from 1 to nearly 10 degrees. Steeper angles were not possible because either shoulder widths were not wide enough or roadside hardware were adjacent to the shoulder, thus preventing maneuvers at larger angles.
In many cases, left-side encroach- ments over centerline rumble strips were limited to 5 degrees 0 1 2 3 4 5 6 7 8 9 10 60 70 80 Time [sec] Ch an ne l 0 [d bA ] 0 1 2 3 4 5 6 7 8 9 10 -5 0 5 Time [sec] Ch an ne l 1 [V ] 0 0 0. Typical sound level, sound intensity, and frequency spectrum. The data acquisition team manually recorded or validated the rumble strip pattern dimensions length, width, depth, and spacingrumble strip pattern type milled or rolledrumble strip location shoulder or centerlinepavement surface type concrete or asphaltand pavement surface condition dry or wet.
The portable data acquisition system recorded the time year, month, day, hour, minutelocation latitude and longitudetravel speed, angle of departure, ambient and max- imum sound levels, and duration and frequency of rumble strip noise generated in the vehicle.
This included measurements in Arizona, measurements in Colorado, measurements in Kentucky, measurements in Min- nesota, measurements in Pennsylvania, and measure- ments in Utah. Rumble strip locations, patterns, and dimensions. Analysis Approach In previous research Khan and Bacchus 97 used both linear and nonlinear regression models to estimate in-vehicle noise generated when traversing various rumble strip patterns. In the present study, ordinary least squares OLS linear regression was used to model sound level differences.
The OLS estimator assumes the following: As such, several diagnostic measures were applied to test the OLS assumptions. The Anderson-Darling test was used to test the normality assumption of the disturbances. This test compares the cumulative distribution of the residuals to those of a the- oretically normal distribution. The null hypothesis is that the residuals follow a normal distribution.
The autocorrelation assumption was tested using the Durbin-Watson statistic. The null hypothesis is that the residuals are not autocorrelated. VIFs are a measure of multicollinearity among the explanatory variables in a model; values exceeding 10 indicate that multicollinearity is present. The null hypothesis F test is that the model has no omitted variables.
When assumption violations result from the analysis, various treatments can be applied. These are discussed in the follow- ing section. The independent variables considered in the sound level difference model are as follows: The general model form used in the analyses was as follows: Using the general form shown in Equation 4several dif- ferent models were estimated.
These include an aggregate model using all data collected in the experiment with the rum- ble strip dimensions, speed, and departure angle all in con- tinuous form. Additionally, disaggregate models using only the milled rumble strip data were estimated.
The sound level difference was computed as the difference between the maximum sound level generated as the test vehicle traversed the rumble strip pattern minus the ambient sound generated in the passenger compartment of the test vehicle prior to encroaching the rumble strips. A model of the sound level difference is based only on a single distribution.
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Analysis Results The response and explanatory variables used in the sound level difference model, and their descriptive statistics, are shown in Table Nearly 44 percent of the sound level measurements were recorded on shoulder rumble strips. Approximately 8 percent of the sound level measurements were recorded on concrete pavement, while nearly 89 percent were recorded on the milled rumble strip pattern.
Modeling results are presented in Table Each of these variables was statistically significant in the model at the 10 percent confidence level.
The residuals generally appear normally distributed. The Durbin-Watson statistic was 1. This suggests that the disturbance terms are correlated. No data interpolation or extrapolation occurred so the likely reason for autocorrelation Variable name Minimum Maximum Mean Standard deviation Ambient noise level dBA Descriptive statistics of variables included in noise database. Regression model of sound level difference. To treat the problem of autocorrelation, the Newey-West method to obtain the standard errors was applied.
Rumble strip - Wikipedia
The results of the regression estimation, corrected for autocorrelation with a single lag, are shown in Table Based on the results shown in Tables 81 and 82, the results of the model can be interpreted as follows: Normal probability plot of sound level difference residuals.
Regression model of sound level difference with Newey-West standard errors. The adjusted R2 value of 0. Because interior vehicle noise is a complex measurement, there are several possible explanations for this low value, including the following: As noted in the Analysis Approach discussion above, addi- tional models of sound level difference were estimated using linear regression.
Can more of the variability of the data be explained by accounting for the use of different test vehicles in the different states, and 2. To determine statistical differences between certain rumble strip dimensions. Only data collected on milled rumble strips were considered in developing these additional models. Table 83 shows a model developed to account for the use of different test vehicles in different states.
Table 83 shows the parameter estimates with Newey-West standard errors to correct for autocorrelation. All other assumptions of the lin- ear regression model were met. The signs of the parameter Table Linear regression with state indicator variables. State effects in the table should be interpreted using Kentucky and Colorado as a baseline. State effects with a negative sign are expected to have lower sound level differences than the baseline, while state effects with a positive sign are expected to have higher sound level differences than the baseline.
The magnitudes of the parameter estimates are also similar. Wet pavement in Arizona and Utah may explain the large parameter estimates for these state indicators when compared to the baseline of Kentucky and Colorado both set to zero. When interpreting the meaning of the state indicator variables, the intention is that states would not have to select a given state i.
By including these different vehicles in the model, more of the variability in the data can be explained, so there is greater reliability in the predictions.
A rumble device
Efforts were also made to use indicator variables to determine the relative effects of different rumble strip dimensions on sound level difference. To create the dimension indicator vari- ables, construction tolerances were considered.
For example, if a state standard indicated a milled rumble strip pattern of 16 in. As such, efforts to group dimen- sions into bins based on tolerances were undertaken. At least 10 percent of the observations for any binned dimension cate- gory were sought.
The descriptive statistics for the binned dimension data are shown in Table A linear regression model was estimated using the categor- ical dimension data. State indicator variables were not con- sidered because of the multicollinearity problems created by the including both state and dimensions indicators in the same model.
Several dimensions were unique to a single state; thus perfect multicollinearity a linear regression assumption violation resulted. All remaining regression assumptions were met using the categorical dimension data, except the auto- correlation assumption. As such, the standard errors were estimated using the Newey-West method.
The regression model estimates are shown in Table Interpretation of the parameter estimates in Table 85 indi- cates the following: This indicates that longer rumble strips are associated with a higher sound level dif- ference than shorter patterns. Rumble strips with length dimensions less than or equal to 14 in. However, the interaction between the width and depth dimension indicators is highly significant and negative, suggesting that width and depth are jointly associated with sound level difference.
For a given milling machine, cutting heads are a given diameter so increasing the width of a rum- ble strip consequently increases the depth of the rumble strip as well, and vice versa. As noted previously, however, the depth- width interaction has a negative parameter estimate. Descriptive statistics of categorical rumble strip dimension data. The decision was made to model the difference between the ambient sound level while traveling in the travel lane and the maximum sound level generated while traversing the rumble strips either on the shoulder or on the centerline.Adorably confused baby meets twins
This decision was based on the fact that the sound level distribu- tions for the ambient sound levels and the maximum sound levels were different. Several models were developed but are not included here within the report that predicted ambient sound levels and maximum sound levels separately.
These models explained approximately 26 to 32 percent i. These models provide credibility to the data collection effort indicat- ing that the data were collected in a reasonable manner and the correct data were collected. These models also illustrated the complexity in modeling the sound level difference between the interaction of a passenger car, its tires, the pavement sur- face, and the rumble strip dimensions.
Application of the Noise Models This section provides several examples of how the noise prediction models developed as part of this research can be used to establish rumble strip dimensions for different types of rumble strip applications. The examples demonstrate how to use the noise prediction models presented in Tables 82 and The advantage of using either of these models is that the rumble strip dimension variables are included as continuous variables.
Therefore, agencies can perform sensitivity analyses by varying the rumble strip dimensions to determine desirable or optimal dimensions for their policies. The disadvantage of using the noise prediction model from Table 83 is that an agency has to assume whether its roads are most like the states of Kentucky and Colorado i.
A simple recommendation on how agencies should assess which state their roads most closely resemble cannot be pro- vided because there is much information that is confounded within this indicator variable such as a the differences in the individual cars used to collect data within that given state; b Arizona was the only state where data were collected during wet pavement conditions; and c the condition of the rumble strips in the varying states i.
Because of the type of information confounded within the state indicator variables, unless an agency is from one of the four states represented in the model, it is recommended that the agency assume the base conditions when using the model from Table Three examples are presented below. The third example makes use of the noise prediction model in Table