Evaluation of the Traffic Noise Prediction Procedure

Transcription

1 Transportation Kentucky Transportation Center Research Report University of Kentucky Year 1973 Evaluation of the Traffic Noise Prediction Procedure Kenneth R. Agent Charles V. Zegeer Kentucky Department of Highays, Kentucky Department of Highays This paper is posted at UKnoledge. researchreports/1119

2 ELIJAH M. HOGGE SECRETARY COMMONWEALTH OF KENTUCKY DEPARTMENT OF TRANSPORTATION FRANKFORT, KENTUCKY 461 BUREAU OF HIGHWAYS JAMES E. GRAY COMMISSIONER November 3, 1973 WENDELL H. FORD GOVERNOR H.3.24 MEMORANDUM TO: J. R. Harbison State Highay Engineer Chairman, Research Committee SUBJECT: Research Report No. 379; "Evaluation of the Traffic Noise Prediction Procedure;" KYP-72-24; HPR-1{9), Part III. Report No. 375 {''Vehicle Noise Survey in Kentucky;" September 1973) presented analyses of more!ban 1, isolated vehicle noise measurements. The report no submitted presents corrections hich have been found to improve the accuracy of the "Procedure for Predicting Traffic Noise Levels" {Design Memorandum No. 1-72). These corrections are based on analyses of 27 noise-level measurements at 39 sites. It is recommended that the noise prediction procedure no in use be revised to include these corrections. They are applicable directly to "clear11 or "free field" situations and, so may be carried through the prediction procedure. This is our third report concerning noise; the first as a brief, literature revie (No. 322, February 1972). We have revieed draft reports of NCHRP Project 3-7, Phase III -- one volume of hich is expected to be published as Report 144 and hich ill contain corrections for the effects of barriers and obstructions in that portion of the prediction procedure. The reports revieed allude to the possible need for corrections to the 11free field" model but provide none. The reports also mentioned in a reminding ay that the original model (NCHRP Report No. 117) as developed from and is applicable to so-called "freeays;" and, so, e infer from this that our corrections should be most significant here traffic volumes are lo and hen the distance from the roaday is short. The noise generated by and( or) reflected by different types of pavements or surfaces offers some possibilities for further corrections and also the possibility of qualifying projects to meet noise-level restrictions by selection of pavement surface types. The adjustments alloed in the existing procedure appear to be too general and too subj'ective. In order to further define the effects of pavement surfaces in this ay, measurements have been made at several road sites (5-ft distance, same automobile, scheduled speeds) surfaced ith sand-asphalts, ith open-graded plant-mix seal, ith Class I, and ith portland cement concrete. It appears that porous bituminous surfaces produce less noise. The analyses and derived factors ill follo in a subsequent report. JHH:d Attachment cc's: Research Committee ectfully /itt/ -Y<---. H. Havens Director of Research ADDRESS RETURN TO: DIVISION OF RESEARCH, 533 SOUTH LIMESTONE, LEXINGTON, KY. 458

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4 TECHNICAL REPORT STANDARD TITLE PAGE 1. Report No. 2. Government Access'1on No. 3. Recipient's Catalog No L < Title and Subtitle 5. Report Date Evaluation of the Traffic Noise Prediction Procedure November! Performing Organiation Code 7, Authorfs) 8. Performing Organiation Report No. Kenneth R. Agent Charles V. Zegeer 9. Performing Orgoni olion Nome and Address 1. Work Unit No. Division of Research Kentucky Bureau of Highays 11 Contract or Grant No. 533 South Limestone KYP Lexington, Kentucky 458 T -,-, ē -fr;;;-d-- ō P c "----'' ''--,---c Sponsoring Agency Nome and Address Interim 379 e -,, -, - - d C, -, - e -,ēd Sponsoring Agency Code L Supplementary Notes Prepared in cooperation ith the US Department of Transportation, Federal Highay Administration Study Title: Noise Abatement 16. Abstract Approximately 27 noise-level recordings ere obtained at 39 highay sites and compared ith the noise-level predictions obtained by the procedure outlined in NCHRP Report 117. The me,asured noise levels ere computed in terms of the A-eighted L 1 value (level exceeded IC) percent of time) and then compared to the predicted noise levels. A significant discrepancy as found beteen predicted and measured noise levels; generally, the predicted values excceded the measured values. Average error per location as 4.8 dba; the maximum error as 13 dba. A nomograph as devised to correct the predicted value this nomograph involves observer-to-roaday distances, truck volumes, and automobile speeds. By applying correction factors, the average error as reduced to 1.9 elba, a 6-percent reduction in error. Based on these findings, it is recommended that the nomograph be used to correct noise predictions in Kentucky. 17. Key Words nomograph db A L 1 noise level prediction procedure 18. Distribution Statement 19. Security Clossif. (of this report) 2. Security Classif, (of this page) 21. No. af Pages 22. Price Unclassified Unclassified L L-----L---- Form DOT F 17.7 ta-b9l

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6 Research Report 379 EVALUATION OF THE TRAFFIC NOISE PREDICTION PROCEDURE KYP-72-24; HPR-1(9), Part III by Kenneth R. Agent Research Engineer and Charles V. Zegeer Research Engineer Associate Division of Research Bureau of Highays DEPARTMENT OF TRANSPORTATION Conunonealth of Kentucky The contents of this report reflect the vies of the authors ho are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official vies or policies of the Bureau of Highays. This report does not constitute a standard, specification, or regulation. November 1973

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8 INTRODUCTION Policy and Procedure Memorandum 9-2 (I) of the Federal Highay Administration stated that after July 1, 1972, all highays constructed must conform to specific design noise levels. To predict future noise levels of highays, a noise prediction procedure has been employed. The procedure provides for the determination of the L 1 noise level (level exceeded 1 percent of the time) based on such factors as observer-roaday distance and shielding. The procedure has not been thoroughly validated, and questions remain as to its accuracy. If discrepancies do exist, adjustment factors may need to be applied to more accurately forecast noise levels. PROCEDURES To evaluate the presently used noise-prediction procedure, it as necessary to obtain field noise recordings and compare them ith noise levels estimated from the prediction model. All recordings ere taken at locations ith ero grade, ith the observer level ith the roaday, and ith no shielding in order to reduce the number of variables that might affect accuracy of the prediction. Figure 1 shos a typical recording site. It as considered essential that gradient, vertical elevation, shielding, element, and 11interrupted'' adjustments should be evaluated separately from the basic situation that is, a straight, level section of roaday on unobstructed terrain. The only exceptions to these criteria ere some locations in donton areas, chosen because of high volume, lo speed traffic, here it as necessary to use the interrupted adjustment because of the high number of traffic signals. Therefore, the only data required to predict noise level ere the distance from observer to roaday, surface type, and car and truck volumes and speeds. The predicted noise level as determined using the procedure outlined in NCHRP Report 117 (2). Basic tables and figures used in the prediction procedure are presented in APPENDIX A. This procedl!re is no being used by the Kentucky Bureau of Highays (3). Since only straight, level sections of roaday ere considered, Figures A2, A3, A4, AS, All, and Al2 ere the only figures used in the prediction procedure. Methods to predict the effectiveness of traffic noise reduction measures ould not alter the results of this study since they ere not considered. Revisions in Figure All have been suggested by others, but those minor changes ould have little effect on results of this study. Noise recordings ere made using a Bruel and Kjaer, precision sound-level meter, Type 223 (Figure 2), and a strip chart recorder, Type 235 (Figure 3). Noise recordings ere made (each recording as of 1 minutes duration) at locations listed in APPENDIX B. The A-eighting netork in the meter as employed. A total of 27 recordings ere obtained. Use of the strip chart recorder offered certain advantages. It enabled the observer to note effects of any unrelated influences such as ind, airplanes, etc. The observer could adjust or disregard the section of the measurement affected. Also, the observer could continually check for agreement beteen the meter indication and the recorded measurement. From the 1 Ominute recordings, noise levels at intervals slightly greater than one second ere determined in the laboratory utiliing a digital data reduction system, Gerber Model GDDRS-3B, as shon in Figure 4. The output as punched onto computer cards through direct coupling ith a card punch unit. By means of a simple computer program, the L 1 noise level as computed. The L 1 noise level is the standard for federal limitations on alloable traffic noise. The measured, L 1 noise level as then compared ith the predicted level. FINDINGS The primary objective of this study as to determine if a significant discrepancy exists beteen predicted noise levels and measured noise levels. Figure 5 clearly indicates the prediction procedure tends to yield higher values. The average error per location' as found to be 4.8 dba; the maximum error as 13 dba. The differences ere found to be significant at the.1 level ( 4 ). Details of statistical tests are presented in APPENDIX C. To determine the reason for this discrepancy, several computer plots ere prepared (presented in APPENDIX D); differences beteen predicted (uncorrected) and measured noise levels ere plotted against several variables hich affect noise level. An optimal linear fit as determined. Variables considered ere; observer-to-roaday distance (D N ), total volume, car volume, truck volume, car volume-truck volume ratio, car speed, truck speed, and percent trucks. The plots clearly indicate some relationships beteen several of the variables considered and the prediction procedure error. Figure 6 shos a relationship ith the observertoroaday distance. For short observer-to-roaday distances, the prediction procedure usually yielded higher values than measured values. As

9 the distance increased, the error decreased until the predicted values ere belo measured values at greater distances. A nomograph as employed to correct noise levels obtained from the prediction procedure. A combination of variables should be considered hen making the corrections. For example, an observer-to-roaday distance of 5 feet (15 m) yields a predicted value hich is too high at locations having lo truck volumes, but it is accurate for locations having high truck volumes. The nomograph, of necessity, should permit a reduction of values for locations (observer-to-roaday distance of 5 feet (15 m)) having lo truck volumes, but no correction should be made for locations having high truck volumes. A small value should be added for very high volumes. Similar corrections should be made for other variables. Variables hich shoed a definite relationship to the prediction procedure error ere selected (APPENDIX D). These variables ere then used in various combinations for preparation of trial nomographs. The nomograph (Figure 7) hich yielded the best results (greatest overall reduction in error) involved observer-to-roaday distance, truck volume, and car speed. The procedure for using the nomograph is outlined in APPENDIX E. Correction factors ere obtained for each of the 27 recordings to determine the predicted (corrected) noise levels. Results are shon in Figure 8. The optimal linear fit of the points lies very close to the 45-degree line, hich represents the line here predicted noise levels equal measured noise levels. Plots ere also made of variables involved versus error in 11Corrected" noise levels. Figure 9 shos the error for the observer-to-roaday distance and the "corrected" noise level. As may be seen, the optimal linear fit line lies very close to ero error for all distances. Remaining plots are presented in APPENDIX F. The average error per location, after corrections ere applied, as 1.9 dba and represents a 6 percent reduction in error from the 11uncorrectedn predictions. This error reduction is significant at the.1 level. After correction, the residual error beteen measured and corrected values as found not being statistically significant at the.1 level, but significant at the.2 level. This remaining error might have been due to several factors. Imperfections in data collection are possible causes. The noise-level meter as calibrated each day before recordings ere made, and the strip chart recorder as continuously compared to the sound-level meter to insure accurate readings, but some degree of error might be expected. Variable pavement types can csuse variations in sound levels, and the adjustment for pavement type is probably inadequate 2 since it simply provides for an adjustment of plus or minus 5 dba for rough or smooth pavements, respectively. In addition, types of cars and trucks hich pass during recording periods vary. For example, the prediction procedure cannot provide for the percentage of tractor-trailer trucks hich might pass. For a particular location and a given truck volume, the noise level ill increase markedly as the percentage of tractor-trailer trucks increases. The prediction procedure also does not account for differences in noise levels of a particular type of vehicle. Therefore, if an abnormal number of quiet or loud vehicles passes hile the recording is being made, the measured noise level ould differ from the predicted noise level. Table 1 shos the distribution of differences beteen predicted and measured noise levels before and after corrections ere applied. The number of locations ith large errors as greatly reduced hen the predicted noise level as corrected. APPENDIX G lists results of a detailed evaluation of the prediction procedure errors for each of the variables considered. Tables G 1 through GS sho the range and distribution of the variables and the average error before,and after correction of the predicted noise level. A statistical test as performed to evaluate the variability hich remained after corrections ere applied. Results indicated error variabil.f},y before correction as significantly larger than error variability after correction to the.1 level of significance. CONCLUSIONS The objective of the study as met and folloing are conclusions dran from the analyses: 1. A significant discrepancy as found beteen predicted noise levels and measured noise levels. The average error as 4.8 dba. 2. A nomograph, developed for the correction of predicted noise, resulted in a significant reduction in errors. Significant corrections ere necessary for: A. short observer-to-roaday distance and lo truck volume (correction = 3 to 1 dba, depending on average car speed), B. short observer-to-roaday distance and lo mean car speed (correction = 5 to 1 db A depending on truck volume), and C. short observer-to-roaday distance, lo truck volume, and lo mean car

10 speed (correction 1 dba). 3. Although errors ere substantially reduced, remaining errors {an average of 1.9 dba) indicate further study of other variables should be made. In particular, more accurate adjustments are necessary. for various pavement types. Variations of noise levels emitted from different vehicles cause error beteen predicted and measured noise levels and further adjustments may be forthcoming. IMPLEMENTATION Presently-used noise prediction procedures yie14 results hich significantly differ from measured noise levels. Use of the nomograph significantly reduces error beteen measured and predicted noise levels. It is recommended that the nomogram be incorporated into Kentucky1s noise prediction procedure as a means of improving its accuracy. Figure I. Typical Recording Site. REFERENCES!. Policy and Procedure Memorandum 9-2, Federal Highay Administration, April 26, Gordon, C. G.; Galloay, W. J.; Kugler, B. A.; and Nelson, D. L.; Highay Noise -- A Design Guide for Highay Engineers, National Cooperative Highay Research Program Report No. 117, Highay Research Board, Procedure for Predicting Traffic Noise Levels, Design Memorandum No. 1-72, Kentucky Bureau of Highays, January 14, Experimental Statistics, National Bureau of Standards Handbook 91, August I, Figure 2. Bruel and Kjaer Precision Sound-Level Meter, Type

11 Figure 3. Bruel and Kjaer Strip Chart Recorder, Type 235. Figure 4. Gerber Model GDDRS-3B, Digital Data Reduction System. 4

12 85 <[ Ill " 77 ',.. -' > -' (/) f- a: Y=.83 X MEASURED NOISE LEVEL (dba) Figure 5. Predicted Noise Levels versus Measured Noise Levels. 16..J >..J j ' Y=-.156X ; l ' l : :. : U) ::>.. : Figure 6. Prediction Procedure Error versus Observer-to-Roaday Distance. -4 " ;:; : a_ OBSERVER- TO-ROADWAY DISTANCE (Ft.) OBSERVER-TO- ROADWAY DISTANCE (Meters) 5

13 .-----,-, 25 1 u; :: u u <>: 1-3 en en 1 CORRECTION FACTOR (dba) OR MORE 5 OR MORE i:'.::,.<!. '- Figure 7. Prediction Correction Factor. 6

14 <t 85.,...J >...J en f () a: a: () f (.) a: a. 45 Y=.895 X MEASURED NOISE LEVEL (dba) Figure 8. Predicted (Corrected) Noise Levels versus Measured Noise Levels. 8 <t ID.,...J > f- ()...J a: a: en () f- a: () :::> en <t a: fl. ::;; en :::> ::;; 4 I ' I i-. I } i : ' '! ' I : ', :. : y = x 1 o-4x Figure OBSERVER- TO-ROADWAY DISTANCE (Ft.) Predicted (Corrected) Noise Level Error versus Observerto-Roaday Oistance. OBSERVER-TO- ROADWAY DISTANCE (Meters) 7

15 TABLE 1 DISTRIBUTION OF ERRORS DIFFERENCE BEFORE CORRECTION AFTER CORRECTION BETWEEN PREDICTED PERCENTAGE PERCENTAGE AND NUMBER OF LOCATIONS NUMBER OF LOCATIONS MEASURED OF EXCEEDING OF EXCEEDING NOISE LEVELS LOCATIONS A GIVEN LOCATIONS A GIVEN (dba) NOISE LEVEL NOISE LEVEL I I.! I II

16 APPENDIX A PROCEDURE FOR PREDICTING TRAFFIC NOISE LEVELS 9

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18 I. PROCEDURE FOR PREDICTING TRAFFIC NOISE LEVELS A. DEFINITIONS I. dba.. decibels on the "A" eighting netork. 2. L 5 noise level that is exceeded 5 percent of the time, or median noise level. 3. L 1 noise level that is exceeded I percent of the time. 4. Single-lane equivalent the single-lane representation of a roaday hich, to the observer, is acoustically similar to the real roaday. 5. D N -- distance beteen observer and centerline of the nearest lane. 6. Element section of roaday ith constant characteristics of geometry and vehicular operating conditions. 7. Finite Element -- hen an element starts and finishes ithin a length of 8 D N (see Figure AS). 8. Semi-Infinite Element -- hen an element extends across 4 D N in one direction but terminates ithin a length of 8 D N (see Figure AS). 9. Infinite Element hen the element length is greater than 8 D N (see Figure AS). B. RULES FOR ELEMENT IDENTIFICATION C. A/inernent (Curves): To satisfy requirements of a single-element definition, the element must be effectively straight. The folloing rules apply: I. Stretches of road separated by curves must, in general, be regarded as separate elements. 2. When the ratio of curve radius to observer distance exceeds 1 and hen the observer lies ithin the triangle formed by the normal intersects of the roaday at the curve tangency points, the curve itself should, be represented by a straight element to provide a "best ne' representation of the curve. 3. A roaflay having compound curves may be represented by a 'best fit" straight roaday as long as deviations from this representation do not exceed ± 2 percent of the mean observerdroaday distance. II. D. Gradients: To satisfy the requirements of a single.element definition, the element must not contain a change in grade of greater than 2 percent. E. Cross Section: To satisfy the requirements of a single-element definition, the cross section along the length of the element must be effectively unchanging. Significant changes are defined as follos: 1. a change in the differential in roaday elevation ith respect to the terrain (parameter H for elevated or depressed roadays) of more than ± 1 percent about the midpoint value, 2. a change in total roaday idth (including median) of more than ± 25 percent about the midpoint value, and 3. a change, on the observer side, of the roaday cut distance or the roaday shoulder distance, for depressed and elevated configurations, respectively, of more than ± 25 percent about the midpoint value. F. Traffic Flo: To satisfy the requirements of a single-element definition, the traffic flo conditions along the length of the element must be effectively constant. Significant changes are defined as follos: 1. a flo volume change of ± I percent, 2. an average speed change of± 1 percent, and 3. a change from uninterrupted to interrupted flo conditions. With regard to the last item, interrupted flo imposed by a traffic control signal is assumed to have an influence on the operating noise of a vehicle over a distance of 1. feet (3 m) centered at the signal. This length ould therefore define the element length. SELECTION OF THE REFERENCE L so AT 1 FEET (3 m) A. Using the given ADT as a base, calculate the number of vehicles per hour for the hours of the day desired. Figure A I gives the percent of ADT for the various times of day. II

19 Ill. B. Using the given auto/truck mix and the result from Step A, calculate the number of automobiles per trucks per hour. hour and the number of C. Using the given average speed and results from Step B, obtain L 5 for cars from Figure A2 and L 5 for trucks from Figure A3. D. Enter the results of Step C in Line I of the Noise Prediction Worksheet (Table AI). SELECTION AND CALCULATION OF THE PROPER ADJUSTMENTS A. Distance and Roaday Width In nearly all cases, the distance beteen the points in question ill be other than I feet (3 m ). Also, since Figures A2 and A3 ere developed using an "equivalent single lane11 concept, an adjustment is necessary for the number of lanes involved. Both adjustments may be accounted for simultaneously by using Figure A4. Enter that result on Line 2 of the Noise Prediction Worksheet. B. Element After separating the roaday in question into individual elements, classify each element as Type I, II, or III. If the element is Type I, there is no adjustment to be entered. If the element is Type II or Type Ill, measure the angle as shon in Figure 5 and use this in Figure A6 for a semi-infinite element or in Figure A 7 for a finite element to obtain the adjustment to be entered on Line 3 of the Noise Prediction Worksheet. C. Gradient Noise emission levels for automobiles are constant for any condition of gradient. Hoever, trucks emit higher levels of noise hen going up or don a hill. Obtain the proper adjustment for gradient from Table A2 and enter that number on Line 4 of the Noise Prediction Worksheet. D. Vertical When a roaday is depressed or elevated, its noise levels ill be reduced to some extent, depending on various factors. To obtain that adjustment, use Figure A. To determine the value of D E for use in Figure A9, use Figure IV. AS. Enter the adjustment obtained from Figure A9 on Line 5 of the Noise Prediction Worksheet. E. Shielding by vertical, roadside barriers In many cases, traffic noise levels may be reduced by placing a 11all" adjacent to a roaday. Use Figure AIO to determine the adjustment for a barrier extending the entire length of the element (or 8 D in the case N of an infinite element). For barriers that extend for more than to-thirds but not for the entire length of the element, deduct 3 db from the adjustment. For barriers hose length is from one-third to to-thirds that of the element, deduct 6 db from the adjustment. For barriers shorter than one-third the length of element, deduct I db from the adjustment. Enter that adjustment on Line 7(a) on the Noise Prediction Worksheet. F. Shielding by structures Subtract 3 db per ro of houses or structures, provided there is no direct lineofsight beteen the roaday and the observer. That adjustment should never exceed a maximum of 9 db. G. Shielding by plantings Subtract 5 db for every I feet (3 m) depth of plantings provided the plantings are at least I 5 feet (5 m) in height and sufficiently dense so that no direct line-of-sight exists beteen the roaday and the observer. That adjustment should never exceed I db. Enter the sum of shielding by structures and plantings on Line 7{b) on the Noise Prediction Worksheet. ADJUSTMENT FOR L IO A. After completing the addition as set forth on Lines 8 and 9 of the Noise Prediction Worksheet, it is no necessary make adjustments required to arrive at L. The 1 first step is to determine the (L L 1 sol adjustment. Use Figure Al l ith A v VDdS, V number of vehicles per hour, I2

20 D E equivalent lane distance (ft), and S average speed (mph). Enter the result on Line 1. B. When continuous traffic flo is interrupted by a stop sign or signal, the median noise level, L 5, is not significantly changed. Research has shon that some of the louder vehicles ill sho an increase in noise output. Therefore, use Table A3 henever interrupted flo conditions exist. Enter that result on Line 11 on the Noise Prediction Worksheet. Complete the addition indicated on Line 12. V. CALCULATING TOTAL NOISE LEVELS A. Lines 9 and 12 on the Noise Prediction Worksheet are subtotals hich should be totaled to determine the correct traffic noise level at a given location. The procedure for that totaling is as follos: 1. Do NOT add numbers directly. Noise levels are logarithmic in nature and must therefore be added logarithmically. Figure Al2 has been prepared for this purpose. Complete the folloing example problems as a familiariation ith Figure Al2: 45 dba + 48 dba = 49.8 dba =5 dba, 49 dba + 49 dba 52 dba, and 51 dba + 57 dba = 58 dba. 2. With use of Figure Al2, add the auto and truck levels for each element and enter those results in the appropriate L 5 or L 1 blocks on Line Again ith the use of Figure Al2, add the element totals for L 5 and L 1 on Line 13. The sums result in grand totals for L 5 and L 1 as called for on Line 14. Results are noise levels used as design criteria. 13

21 TABLE Al NOISE PREDICTION WORK SHEET Road Element Number Type " ::1 Time Interval Vehicle Type Auto Truck Auto Truck Auto Truck Auto Truck I 2 '---- 3, J g 8.a u - 9 u "" 1 II 12 Reference at I feet Lso Distance Element Gradient "l Vertical "" Surface Shielding (') Barriers Total Adjustment (b) (Sum of Lines 2 through 7) L5 at Observer (Line I plus Line 8) L1 - L so Adjustment Interrupted Adjustment L1 at Observer (Sum of Lines 9, 1, and 1 I) Structures & Plantings Element Total Lso L!O 14 Grand Total L s o - db A L IO - db A 15 L - Lso ' dba 14

22 TABLE A2 ADJUSTMENT FOR GRADIENT (FOR TRUCKS ONLY) TABLE A3 INTERRUPTED FLOW ADJUSTMENT GRADIENT (PERCENT) VEHICLE ADJUSTMENT (dba) FOR ADJUSTMENT TYPE L so L!O (dba) Automobile +2 Truck Cl <{ LL. 1- (.) a::: a_ AM.,.Mi--- PM ---iooloolj HOUR OF DAY Figure AL Percent of ADT and Hour of Day. 15

23 -;;;..J >..J :::> ({) " " 3 " 2 9 mph SPEED m/s 3 L_----L ! 1, HOURLY AUTO VOLUME (vph) 1 Figure A2. Plot of L5 for Automobiles as a Function of Volume and Average Speed ' > -' 7 :::> ({) 6 m/s 9 mph 2 " 5 " " 27 " L L_ L , HOURL Y TRUCK VOLUME (vph) Figme A3. Plot of L5 for Trucks. 16

24 1 ROADWAY WIDTH FEET NO. OF METERS LANES 5 Ol '"CI : IJJ ::!!: tn ::>.., <t L L , OBSERVER- NEAR LANE DISTANCE, DN (ft ) OBSERVER- NEAR LANE DISTANCE, O N (m) Figure A4. Distance Adjustment to Account for Observer-Near Lane Distance and Widtb of Roaday. 17

25 DN i OBSERVER (o) INFINITE ELEMENT TYPE I B (-)..._j..., (+) I (b) SEMI-INFINITE TYPE If ELEMENT NOTE' The Angle Fl Can Be(+) or(-) Depending If It Is Measured To The Right or Left. (c) FINITE ELEMENT TYPE m Figure AS. Dlustrations of Element Types. 18

26 1 Ill " c: I- 2 ::2E I- (/) ::::J..., Cl <( ol _l L -J L e (in degrees) Figure A6. Adjustment to Account for Semi-Infinite Element Length. 5 Ill " c: I ::2E I- (/) -1 ::::J..., Cl <( e (in degrees ) Figure A7. Adjustment to Account for Finite Element Length

27 183 6 e /J (.) 1/J (.) 35 1 <(!/) 1-8 is 1/J 6 1/J <(.J 4 <(.J 1-1/J.J 1-1/J.J 2 ::> ::> 3 1 1/J 1/J I 8 ::: ::: 1/J 1/J 6 > ::: 6; 1/J 1/J 4!/)!/) Ql Ql 2 ROADWAY WIDTH FEET NO. OF METERS LANES,o , OBSERVER- NEAR LANE DISTANCE, O N (f1) 3 3 OBSERVER- NEAR LANE DISTANCE, O N (m) 35 Figure AS. Observer Equivalent Lane Distance as a Function of Near-Lane Distance and Width of Roaday. 2

28 1 * CD " <: -... :::ie... en ::::> --, <t -1-2.I PARAMETER A ( FT} PARAMETER A (METERS} PARAMETER A = Hr 1 Ds " PARAMETER B = Hf /(D E -Ds}. I : DBSERVER LOCATION EQUIVALENT LANE "lil"--r:_o:bserver HEIGHT (a) ELEVATED HIGHWAY PARAMETER A= H 2 1 (D E -Del PARAMETER B = H 2 /Dc EQUIVALENT LANE H -i=::/ll= = =:l,...oase v LOCATION (b) DEPRESSED HIGHWAY * FOR TR UCKS ADD +5 DB TO VALUE GIVEN BY FIGURE **HEIGHT OF ELEVATED FRE.EWAY ABOVE OBSERVER (H I ) Figure A9. Adjustment for Elevated and Depressed Roaday. 21

29 e EQUIVALENT LANE OBSERVER m..., - \ H2/Ds 1- Ill ::IE (f) :::>..., <I:.3 \. _:, H21 (DE-Dsl (ft) O.o3 H2 1(DE-Ds) (m) figure AlO. Adjustment for Roadside Barriers. 22

30 Ill c: I PARAMETER Av Figure All. Adjustment to L5 to Obtain L 1. 23

31 NUMERICAL DIFFERENCE BETWEEN TWO LEVELS BEING ADDED ( DECI BELS) I II r- \ \ 2 "- \ " lc-- I 3 4 """ "" _......_,_ --..._-L_ I I I I I I I I I I 5 s r a (D ECIBELS) NUMERICAL DIFFERENCE BETWEEN TOTAL AND SMALLER LEVELS Figure Al2. Procedure for Adding Noise Levels. 24

32 APPENDIX B LOCATIONS OF TRAFFIC NOISE RECORDINGS 25

33 l 75 l 75 I 75 l 75 l 75 I 75 I 75 I 75 l 64!64 I 75 I 264 us 421 us 27 us 68 us 421 us 68 us 25 us 6 us 25 us 6 us 6 us 6 us 6 us 6 us 6 us 421 us 6 us 27 us 68 us 27 us 27 KY 4 KY 922 KY 4 KY 4 KY 4 KY rrriles (3.2 krn) south of Georgeton exit MP 17.5 rrrile (.8 km) north of White Hall exit.75 mile (1.2 km) north of Delaplain Road 2. miles (3.2 km) south of Mt. Vernon MP mile (.8 km) north of MP 16.5 rrrile. (.8 km) south of rest area, Boone County 1. rrrile (1.6 km) est of Depot exit 1. rrrile (1.6 km) east of Mountain Parkay exit Fayette County Watterson Expressay, Louisville Leeston Pike, approximately 1.5 miles (2.4 km) north of Lexington Nicholasville Road, near Devondale Baptist Church, Lexington Harrodsburg Road, 1.5 miles (2.4 km) est of KY 4, Lexington Leeston Pike, 1. mile (1.6 km) north of KY 4, Lexington Harrodsburg Road, near Turfland Mall, Lexington Richmond Road, near Shriner's Hospital, Lexington LO mile (1.6 km) east of I 64, Franklin County Richrnond Road, near Idle Hour Shopping Center, Lexington Versailles Road, Woodford County Versailles Road, near Bluegrass Parkay approximately 5 rrriles (8 km) est of Versailles approximately 4 rrriles (6 km) east of Frankfort 2. rrriles (3.2 km) est of US 62 approximately 7 miles {II km) est of Versailles approximately 3 rrriles (5 km) south of Lexington Versailles Road, near Parkay Golf Course South Limestone Street, Lexington South Broaday, Lexington South Limestone, near Division of Research Laboratory, Lexington South Limestone, nea.r Central Baptist Hospital, Lexington across from Quantrell Cadillac, Lexington Neton Pike, near IBM, Lexington near IBM, Lexington.5 mile (.8 km) north of Harrodsburg Road, Lexington LO mile (1.6 km) south of Versailles Road, Lexington Tates Creek Road, Lexington Cooper Drive, Lexington 26

34 APPENDIX C STATISTICAL TESTS 27

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36 STATISTICAL TESTS Four statistical tests ere performed in this study. They ere as follos: 1. comparison of predicted (uncorrected) noise levels ith measured noise levels, 2. comparison of predicted noise levels (corrected) ith measured noise levels, 3. comparison of percent error of the uncorrected noise levels ith the percent error of the corrected noise levels, and 4. comparison of variability of percent error of uncorrected ith corrected noise levels. Percent error as used instead of dba units because percent error gives a value relative to the magnitude of each measured value. Also, percent error values ere used for these statistical tests even though noise levels are logarithmic. Thus, care should be taken in the interpretation of these test results. Percent error values ere calculated for each of the 27 measured n;ise levels. For example, a measured L 1 value as 75 dba, the predicted value as 85 dba, and the predicted (corrected) value as 77 dba. The error beteen the measured and predicted value as 1 dba, a 1 x 1/75 or 13.3 percent error, used in the first statistical test indicated above. The error beteen measured and predicted (corrected} noise levels as 2 dba or 2.7 percent, used in the second statistical test. The difference in percent error as also computed for each location and used in the third statistical test. For this example, that difference ould be = 1.6 percent. In making the statistical comparisons, the folloing definitions of terms ere used: n number of noise measurements, x d average difference in percent error for the noise levels being compared, standard deviation in percent error for the 27 values, a level of significance of the test, J.l a constant = t (l.. 5 al S d / y'r;: percentile of the t distribution, standard deviation of percent error before correction, standard deviation of percent error after correction 2 a constant = S 8 Js 2 A and a constant value for n A-1, n B-1 degrees of freedom. I. FIRST STATISTICAL TEST a O.Dl.xct 5.67 s d n 27 Vn t = (from Hest chart) J.l (2.576) (15.14)/(16.43) = 2.37 Since X d > p, there is a significant difference beteen the predicted (uncorrected} and measured noise levels at the.1 significance level. 2. SECOND STATISTICAL TEST a.1 x d o.61 s d 6.38 n 27 Vn t 1.96 (from!-test chart) J.l (1.96) (6.38)/(16.43) =.76 Since 11 > X d, there is no significant difference. Choose a =.2, t (from Hest chart) s <i = 6.38 Vn = J.l (1.282) (6.38)/(16.43) =.5 Since X d > Jl, there is a significant difference. Therefore, no significant difference exists beteen the corrected and measured values at the.1 level, but the difference is significant at the.2 level. 3. TIDRD STATISTICAL TEST a =.1.x = d 3.85 s d 6. n = 27 Vn = t = (from!-test chart) J.l (2.57) (6.)/(16.43) =.94 Since X d > Jl, there is a significant difference. Thus, a significant reduction in error as achieved by the correction nomograph at the.1 significance level. 4. FOURTH STATISTICAL TEST a.1 F 1-a 1. (from table for percentiles of F distribution) F s8 2 2 /S A = a, the variability of error as reduced significantly by the correction nomograph at the.1 level. Since F > F 1 29

37

38 APPENDIX D PLOTS OF PREDICTION PROCEDURE ERROR VERSUS SEVERAL VARIABLES 31

39

40 16 -' > -' : 4 : ". :'.. '.:...:....: '.".. Figure Dl. Prediction Procedure Enor versus Total Volume. f.- " Y=4.64 x lo-sx t Figure 2. TOTAL VOLUME IVPHI Prediction Procedure Error versus Car Volume. -' 12 > _J :. :. 8 => " 4 3 " 1 :.!.; ;: '!...,, "- -8 Y= 3.37 xlo-4 x ' > -' CAR VOLUME (VPH) 4 5 "! 8 '.. => " : ;; 4 Figure D3. Prediction Procedure Error versus Truck Volume. -4 f.- "- -8 Y= X TRUCK VOLUME ( VPH) 33

41 16 16 <( -' > -' "1 " <( " '..... _::. ::.. :.... -' > -' :> <( " " " " i '..!! I : ''. ' f: ' :. ; ' ' : ;.,, :,' -4,_ '-' Y=.149 X t 2.31 "- - 8 '----'----'---'-----' CAR/TRUCK RATIO -4,_ '-' 6 " Y= X MEAN CAR SPEED (mph) Figure 4. Prediction Procedure Error versus CarTruck Ratio.! MEAN CAR SPEED {m/sl 16 Figure 5. Prediction Procedure Error versus Car Speed. <( :"! -' > -' 12 8 :> <t '" " 4 :> ;:.. '.!.. '.! i '..! " -' > -' :> <( " =... ':-, =:. 4,., I :: ;:, ,_ -4 " Y=-.292X MEAN TRUCK SPEED (mph) :> ",_ '-' " Y=-.161X MEAN TRUCK SPEED ( m/s) PERCENT TRUCKS Figure 6. Prediction Procedure Error versus Truck Speed. Figure 7. Prediction Percent Trucks. Procedure Error versus 34

42 APPENDIX E USE OF NOMOGRAPH TO DETERMINE CORRECTION FACTORS 35

43

44 USE OF NOMOGRAPH TO DETERMINE CORRECTION FACTORS To determine correction factors from the nomograph, the folloing must be knon: 1. observer-to-roaday distance (ft), 2. truck volume (vph), and 3. average car speed (mph). The folloing example illustrates use of the nomograph in Figure Dl. A level, stn1ight, four-lane roaday ith a "normal" surface has a truck volume of 15 vph, car volume of 5 vph, average truck speed of 4 mph (18 m/s), and mean car speed of 5 mph (22 m/s). Noise readings are taken <Jt 2 feet (61 rn), and there are no barriers or traffic interruptions (such as traffic signals). The prediction procedure yields a final L 1 value of 7.X dba. To determine the correction from the nomograph, first find the distance of 2 feet (61 m) on the scale in the upper left-hand corner of the nomograph. Dra a horiontal line until it intersects the curved line. Then dm a vertical line donard to the lines hich represent truck volume. Where the vertical line intersects the point hich represents the truck volume of 15 (interpolation ill be necessary in many cases), a horiontal line is then dran to the lines representing mean car speed. Where the horiontal line intersects the line for car speed of 5 mph (22 m/s) (interpolation ill again be necessary in many cases), dra a vertical line until it intersects the scale hich provides the correction factor. Read the correction factor of -3.2 dba and add it (algebraically) to lhc 7.8 db A hich as obtained from the prediction procedure. Thus, the corrected value is 67.6 dba. 37

45 .-----,-, 25 1 Ci) :: 5 1- f-- :: (f) ll 75 <t 1- (f) CORRECTION FACTOR (dba) OR MORE 5 OR MORE -4Q. '- c> " "I" 11 <Po '- Figure El. Prediction Procedure Correction Factor. 38

46 APPENDIX F PLOTS OF PREDICTION PROCEDURE (CORRECTED) ERROR VERSUS SEVERAL VARIABLES 39

47

48 " " <D " Q -' > >- -' <r <r s >- <r -4 ".. <r "- " -8. ;-:-....:: _.:,:- '.. 1 :..... Y= 1.58 x 1 4 X " " :: -' > >- -' <r <r 6 >- <r ".. <r "- " ' \.. Y=-1.71 x IQ- 4 X TOTAL VOLUME (VPH) CAR VOLUME (VPH) Figure Fl. Predicted (Corrected) Noise Level Error versus Total Volume. Figure F2. Predicted (Corrected) Noise Level Error versus Car Volume. " <D " :: -' Q >- > -' <r <r s 6 >- <r ".. <r "- " Y=2.77x I-4X L _L----L " " <D " 2 Q -' >- > -' <r <r '" s 6 >- <r s " <l <r "- " 8 Y -1.46xto 3xtD L _l TRUCK VOLUME ( VPH } CAR I TRUCK RATIO Figure F3. Predicted (Corrected) Noise Level Error Figure F4. versus Truck Volume. Predicted (Corrected) Noise Level Error versus Car/Truck Ratio. 41

49 " ;; " ;:r u 8 -' 4 > >- " -' " >- " ".. " ; ' ' '! '! ' ' ' Y= X t ! Figure F5. Predicted (Corrected} NoiJ;e Level Error versus Car Speed. MEAN CAR SPEED (mph) MEAN CAR SPEED (m/ s) 8 Figure F6. Predicted (Corrected) Noise Level Error versus Truck Speed. ".. ;; u " 4 -' > >- " -' - -4 >- u " i5.. "- " '. '... Y= X I 2.59 : i j 6 68 MEAN TRUCK SPEED (mph) MEAN TRUCK SPEED ( m/ s) 3 8 t i5 8' ' Y= x IQ3x +.36 Figure F7. Predicted (Corrected) Noise Level Error versus Percent Trucks PEA CENT TRUCKS 42

50 APPENDIX G TABLES OF MEAN ERROR BEFORE AND AFTER CORRECTION FOR SEVERAL VARIABLES 43

51

52 TABLE Gl MEAN ERROR BEFORE AND AFTER CORRECTION FOR OBSERVER-TO-ROADWAY DISTANCE NUMBER MEAN ERROR MEAN ERROR DISTANCE OF BEFORE AFTER MEAN ERROR LOCATIONS CORRECTION CORRECTION REDUCTION (FEET) (METERS) (dba) (dba) (dba) ! I ! OTHER TABLE G2 MEAN ERROR BEFORE AND AFTER CORRECTION FOR TOTAL VOLUME NUMBER MEAN ERROR MEAN ERROR TOTAL OF BEFORE AFTER MEAN ERROR VOLUME LOCATIONS CORRECTION CORRECTION REDUCTION (VPH) (dba) (dba) (dba) < >

53 TABLE G3 MEAN ERROR BEFORE AND AFTER CORRECTION FOR CAR VOLUME NUMBER MEAN ERROR MEAN ERROR CAR OF BEFORE AFTER MEAN ERROR VOLUME LOCATIONS CORRECTION CORRECTION REDUCTION (VPH) (dba) (dba) (dba) < > 3 II TABLE G4 MEAN ERROR BEFORE AND AFTER CORRECTION FOR TRUCK VOLUME NUMBER MEAN ERROR MEAN ERROR TRUCK OF BEFORE AFTER MEAN ERROR VOLUME LOCATIONS CORRECTION CORRECTION REDUCTION (VPH) (dba) (dba) (dba) >

54 TABLE GS MEAN ERROR BEFORE AND AFTER CORRECTION FOR CAR - TRUCK RATIO NUMBER MEAN ERROR MEAN ERROR CAR - TRUCK OF BEFORE AFTER MEAN ERROR RATIO LOCATIONS CORRECTION CORRECTION REDUCTION (dba) (dba) (dba) > TABLE G6 MEAN ERROR BEFORE AND AFTER CORRECTION FOR CAR SPEED NUMBER MEAN ERROR MEAN ERROR CAR SPEED OF BEFORE AFTER MEAN ERROR LOCATIONS CORRECTION CORRECTION REDUCTION (mph) (m/s) (dba) (dba) (dba)

55 TABLE G7 MEAN ERROR BEFORE AND AFTER CORRECTION FOR TRUCK SPEED NUMBER MEAN ERROR MEAN ERROR TRUCK SPEED OF BEFORE AFTER MEAN ERROR LOCATIONS CORRECTION CORRECTION REDUCTION (mph) (rn/s) (dba) (dba) (dba) < 3 <! ! " 4 16 " " " " " " 6 25 " TABLE G8 MEAN ERROR BEFORE AND AFTER CORRECTION FOR PERCENT TRUCKS NUMBER MEAN ERROR MEAN ERROR PERCENT OF BEFORE AFTER MEAN ERROR TRUCKS LOCATIONS CORRECTION CORRECTION REDUCTION (dba) (dba) (dba) II >